Here’s an irony for you. My job brings me to Las Vegas all the time and I don’t gamble.

Not much, anyway, and certainly not as much as MSPs must in these still early days of AI. As the folks at Nerdio and The ASCII Group can tell you, more or less all of them know they should add customer-facing AI services by now. The hard part is determining which ones.

“Everyone is calling this the era of AI and they’re not wrong, but there’s a big difference between naming an era and determining what to build in it,” observed Colin Blair, vice president of cybersecurity and emerging technologies at distributor D&H, during the company’s NEXT+ Summit in Austin, Texas last week.

It’s a question made harder by the constant evolution of AI technologies, harder still by the endless variety of ways to use those technologies, and perhaps hardest of all by the fact that few of the services you can invest in today will pay off for you today as well.

Indeed, by Blair’s calculations, there’s some $2.61 trillion of capital committed to AI at present, a giant number up $100 billion just in the last 45 days. Yet only 20 to 25 percent of that money’s committed to services, and most of that will flow to global system integrators like Accenture and Deloitte.

“How much of that spend is reaching you? How much of that spend is reaching your customers?” asked Blair (pictured) of the SMB and mid-market IT providers in his audience. “The honest answer is not a lot.”

Or rather, not a lot yet. “It’s coming,” Blair added.

Predicting where it will land when it arrives, however, is a bit like placing a high-stakes wager involving plenty of risk and uncertain reward right now. MSPs who make the right bet on the right services will be building their way to a prosperous future. Those who make the wrong bet on the wrong services, Blair warns, will be building their future on sand.

“And sand does not compound,” he says.

End users, not coincidentally, are playing the same game at present. Whether to invest in AI is not at issue. How best to do so very much is.

“Interest is everywhere. Scale is rare,” writes Forrester in a recent blog post. “The reasons are stubbornly consistent, and they start with money. ROI uncertainty traps enterprise ambition in pilot mode because most companies can’t justify production beyond narrow efficiency gains.”

In reality, however, most businesses are less uncertain about ROI on AI spending than unhappy about it. Only 29% of organizations surveyed by enterprise AI platform vendor WRITER have gotten significant return on their genAI investments so far and nearly 70% of executives polled by HR software maker Globalization Partners are prepared to scale back next year’s AI budget if this year’s goals remain unmet.

“Everybody in the world is struggling to quantify AI ROI,” observes John Harden, founder and CEO of AI transformation startup Lemhi.

As regular Channelholic readers know, Harden is a one-time MSP and former founder of Saaslio, a SaaS management vendor acquired by Auvik in 2022. His new venture, officially launched last week, is based on insights gleaned from 100 conversations with MSPs in a roughly 120-day span. Over and over again, he says, people referenced two ways they’re gambling on AI services at present. One is performing AI readiness chores like cleaning data, implementing security measures, and drafting acceptable use policies for customers. The other is designing and deploying custom agentic AI solutions for them.

“They’re saying, ‘let’s find a $200,000 workflow in your business. Let’s charge you $40,000 to solve it, and then we’ll get maybe a $4,000 a month retainer after that to keep maintaining it,’” Harden says.

Both motions are producing good project revenue, but only for the subset of customers willing to pay either for decidedly unsexy prep work or complex, and therefore expensive, automation work. Neither looks to be a good bet for achieving sustainable AI success.

The Lemhi moment

Which brings us to the “Lemhi moment” MSPs find themselves in, according to Harden, and the inspiration for his new company’s name and mission. The name is a reference to the Lemhi Pass, the point in their journey across North America where Lewis and Clark, expecting swift passage through the Rockies to the Pacific, discovered “immence ranges of high mountains still to the West of us” instead.

“The maps were wrong,” Harden (pictured) explains during an interview on the podcast I co-host, which left the two explorers with a decision. “They could either traverse the mountains moving forward and chart a new path or they could turn back and go home.” They moved forward, obviously, and Lemhi’s mission is helping MSPs who’ve followed flawed maps to sluggish, non-recurring AI revenue do the same.

“We believe that the industry has to chart a whole new path forward,” Harden says.

Lemhi’s platform is designed to guide MSPs along that path, prescriptively and automatically, toward an end state in which they’re rolling out client-facing AI services “repeatably, responsibly, and at scale,” Harden says. The scale part, he continues, comes from the solution’s exclusive focus on AI-enabling the Microsoft software almost every SMB uses. The responsibly part comes from ensuring that every AI rollout begins with governance, security, and policy setting.

But then doesn’t end there. As we’ve seen, governance and security on their own leave business owners yawning, so Lemhi makes them a relatively small part of a much larger conversation about something far likelier to excite customers—making and saving money.

Engage, Lemhi’s first solution module, is designed to provide a repeatable structure for holding that conversation. The system guides a client’s leaders and employees through a survey process that (like similar products) covers technical readiness but also (unlike competing products) a wide range of non-technical topics, such as how comfortable they are with AI at present, how often they use it, and how they’d like to use it in the future.

“Would you benefit from more research, or having automated research? Would you benefit from being able to do Excel insights and analysis quicker? Would you benefit from being able to recap your day and have meeting recaps sent to you on the fly?” Harden says.

Most importantly, he continues, the survey asks users to estimate how much time the items on their AI wish list would save them. The goal is to establish a set of baseline metrics and ROI targets specific and compelling enough to get business managers interested. The output is a detailed roadmap that begins with technical readiness, governance, and security but moves quickly past them to an implementation and training process informed by best practices from the likes of McKinsey and Forrester.

“We have a 30/60/90 day sprint of work to clean up and then we’re going to help you with an adoption sprint,” Harden says.

That in turn is followed by a regular series of “re-pulse” surveys to assess usage, measure impact, and provide advice for increasing both. If Lemhi’s software and the MSPs using it both do their job right, the client should see measurable productivity gains worth paying handsomely for.

“Would you give me $3,000 a month if I could help activate nine hours a month for every one of your employees?” Harden asks.

Or how about nine hours a week, which is what the business leaders surveyed by WRITER say their most AI-savvy employees are saving on average, 4.5x the two hours a week AI laggards are freeing up. Just over half of all laggards and leaders alike at the big businesses Boston Consulting Group surveyed recently are saving eight hours a week, and 67% report higher job satisfaction. MSPs who bring similar results to SMBs can charge appropriately for them.

“The margin should be really high,” Harden says.

And it’s ongoing. After that first roadmap is complete, Harden says, MSPs can offer clients virtual chief AI officer services. “You’re coming in and you’re offering a monthly or quarterly session dedicated to AI and strategy with their business.” Compass, a forthcoming Lemhi module due to reach early design partners this summer and everyone else in the fall, is designed to facilitate those engagements.

“It’ll be the natural extension of continued ROI visibility, continued roadmap implementation, continued governance and security over the whole AI transformation journey,” Harden says.

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One last note

And an apt one as I make my way today to Pax8’s 2026 Beyond conference, where agents and agent marketplaces are sure to figure prominently on the agenda: None of what Lemhi’s building involves agentic AI.

“I believe deeply in the fact that there is no agent that you can build for any small or medium business today that will outweigh the value created if you activate the entire workforce with AI,” Harden says.

More about Lemhi straight from its founder

The rest of that interview I referenced with Harden is available on the latest episode of the MSP Chat podcast. Ready when you are right here.

D&H rides the advanced solutions train

Lemhi may not be thinking much about agentic AI yet, but D&H sure is.

“This is what’s emerging for us,” Blair says. “62% of organizations are experimenting with AI agents. There’s a lot of work to be done here.”

It’s going to be a while before most businesses and IT providers are ready to do it though. “Three-quarters of enterprise leaders tell us they’re adopting agentic AI. Only a small minority have it running in meaningful production beyond ‘agentish’ chatbots, and true scaled multiagent systems are rarer still,” writes Forrester in a recent blog post, mostly because the technical sophistication and organizational readiness necessary to implement them are equally rare.

“The technology is a runaway train,” the post says. “The enterprise is the heavy load it has to pull.”

Fortunately, D&H has plenty of room to make money in big, fast-growing markets like cloud computing and security in the meantime. Indeed, the whole point of NEXT+ was to get partners excited about joining the distributor’s effort to expand beyond its traditional focus on PCs and conference room gear into advanced solutions as well.

“When you look at D&H for the last 15, 20, 30 years, we’ve really focused on selling to VARs and system integrators,” says Adam Crockett (pictured), senior director of services in the company’s Advanced Solutions+ business unit. “We’re kind of known as the end user compute distributor.”

It’s been a great role to play in the channel too. “We’ve grown the company over the last 10 years from a little over $3 billion to over $7 billion, which is 3x the growth of North American distribution,” said Jason Bystrack, D&H’s SVP of cloud and Advanced Solutions+, during a keynote presentation, noting that the company grew $260 million more just in May, the first month of its new fiscal year. D&H wants to extend that momentum now from the front office to the back office.

“When it comes to distribution and total available market, we’ve had a very large share of the desktop, laptop, and end user compute space, but we’ve had a small market share when it comes to advanced solution technology manufacturers,” Crockett says. “All of our growth over the next 10 to 15 years is going to come from advanced technology vendors, because that’s where we’re so under indexed.”

Several of those vendors, including AMD, Extreme Networks, Fortinet, and HPE, made general session presentations at NEXT+. D&H itself made a point of underscoring its ability to wrap assessment, implementation, and management support around the products those companies sell for partners new to them.

“The mid-market partners we’ve grown up with and helped mature along the way may not have a deep bench of technical resources in a specific product line,” Crockett notes. “We just want to help them be able to deliver on the associated services that would go along with an advanced solutions purchase.” The idea, he continues, is to help partners add profitable new revenue streams faster and with fewer upfront investments by embracing a “borrow, not build” model.

“The professional services growth that we’ve had in the last couple of years has been based on that,” Crockett says. “Borrow our facility, we’ll do the pre-deployment work. Borrow our technical resources, we’ll do the onsite installation.”

Helping partners enter unfamiliar markets rapidly is a priority for D&H in areas beyond services too.

“We need to be able to provide them vendor-agnostic consultative pre-sales enablement, technical resources, people who know the OEM programs, how to apply for the best economics, how to make sure they take advantage of all their backend programs and post-sales service and support,” Crockett says, “all the things they need to learn about manufacturers that are new to them.”

Share

Remember that whole managed services thing?

Interesting fact about those end user compute partners at NEXT+: A lot of the same ones intrigued enough about advanced solutions to make the trip to Austin are also intrigued about managed services. Blair said as much during his keynote while citing data showing that 75% of IT spending is now on operational versus capital expenses.

“If I would have shown you the OpEx to CapEx ratio a couple of years ago, this would have been swapped. So it would have been 40% OpEx and 60% CapEx,” he said. As a result, he added, “many of you that were in the traditional VAR/resell model are becoming MSP-like. It’s because you’re paying attention to how your customer is buying.”

And still learning how to accommodate that demand, he could have added, which is why D&H recently launched its Success Path to MSP Toolkit, a series of live and on-demand webinars offering detailed guidance on the nuances of launching a managed services practice.

“You don’t want to build out a service desk and a NOC or a SOC without understanding how you need to thoughtfully consider changing compensation models for your sales organization to drive that behavior” for example, Crockett says. “You’ve got to be a little more methodical, a little more coordinated about making that leap.”

The kit includes additional information about automating and scaling managed service offerings, adding managed security capabilities, zero trust, cloud security, and more.

“We found that many of our partners who are somewhere on that journey of transitioning from more of a VAR or a system integrator into becoming a managed service provider need a kit that brings all these fragmented tool sets and processes and different software options out there into some sort of coordinated discussion,” Crockett says.

The toolkit’s useful in a further, less intentional way as well for those of us who’ve been covering the shift from VAR-based business models to managed services for over two decades now. Cycles like the AI one just getting underway take a very long time to play out, it shows. There will probably be partners gratefully consuming Success Path to AI Toolkits many years from now.

Over on The Business of Tech

Host Dave Sobel is getting ready for his upcoming SMB Online Conference, which runs noon to 3:30pm Eastern each day June 23-25.

The theme is “Profitable is Enough,” the content’s aimed at independent MSP owners more focused on running sustainable, profitable businesses than chasing growth at any cost, and the speakers include Jay McBain, Tiffani Bova, Arlin Sorensen, Rayanne Buchianico, James Kernan, Amy Babinchak, and Sobel himself.

Registration is $399 for the general public and zero for members of Sobel’s Small Biz Thoughts community. Learn more at www.smbonlineconference.com

Also worth noting

• GTIA Presents, a brand-new podcast from GTIA, bills itself as the place “where member insight turns resources into real business results.” New episodes on YouTube and wherever else you get your pods.

• Mere weeks after its launch, Veeam’s added new operational privacy, governance, and control capabilities to its DataAI Command Platform.

• The 20 MSP, which you’ve encountered here on Channelholic before, has acquired four more MSPs, raising the total size of its portfolio to 48 companies.

• Jim Fanning is the new (and first) president of Hatz AI.

• Cisco’s new Cloud Control platform is designed to help organizations build, manage, and secure AI agents that can operate and defend critical IT infrastructure at machine speed.

• Speaking of Cisco Cloud Control, Auvik’s network intelligence capabilities are now available to AI agents in that platform.

• Portal26 now offers a free version of its AI governance, security, and token control platform for business users of Anthropic’s Claude.

• Yet more agent control: Noma’s new Agentic Access Control is designed to help organizations manage and secure AI agents and MCP servers across the enterprise.

• Insight’s new Managed Exposure Defense service combines continuous threat exposure management, patch execution, XDR, and 24x7 monitoring.

• More reasons to make AI governance a priority, from Ivanti: While 85% of organizations have AI policies or oversight mechanisms in place, only 42% say accountability for AI decisions is clear, and just 24% say AI policies are followed very consistently in day‑to‑day work.

• Bad news from IRONSCALES: Phishing now costs businesses a little under $52,000 a year per security analyst. Good news from IRONSCALES: AI-powered defenses cut the cost of dealing with a phishing email by 12%.

• Benji Pays has a new integration with Elavon Payment Gateway designed to give users additional payment processing options.

Lemhi may not be thinking much about agentic AI yet, per a recent post, but D&H sure is.

“This is what’s emerging for us,” Colin Blair, the distributor’s vice president of cybersecurity and emerging technologies, says. “62% of organizations are experimenting with AI agents. There’s a lot of work to be done here.”

It’s going to be a while before most businesses and IT providers are ready to do it though. “Three-quarters of enterprise leaders tell us they’re adopting agentic AI. Only a small minority have it running in meaningful production beyond ‘agentish’ chatbots, and true scaled multiagent systems are rarer still,” writes Forrester in a recent blog post, mostly because the technical sophistication and organizational readiness necessary to implement them are equally rare.

“The technology is a runaway train,” the post says. “The enterprise is the heavy load it has to pull.”

Fortunately, D&H has plenty of room to make money in big, fast-growing markets like cloud computing and security in the meantime. Indeed, the whole point of NEXT+ was to get partners excited about joining the distributor’s effort to expand beyond its traditional focus on PCs and conference room gear into advanced solutions as well.

“When you look at D&H for the last 15, 20, 30 years, we’ve really focused on selling to VARs and system integrators,” says Adam Crockett (pictured), senior director of services in the company’s Advanced Solutions+ business unit. “We’re kind of known as the end user compute distributor.”

It’s been a great role to play in the channel too. “We’ve grown the company over the last 10 years from a little over $3 billion to over $7 billion, which is 3x the growth of North American distribution,” said Jason Bystrack (pictured at top of post), D&H’s SVP of cloud and Advanced Solutions+, during a keynote presentation, noting that the company grew $260 million more just in May, the first month of its new fiscal year. D&H wants to extend that momentum now from the front office to the back office.

“When it comes to distribution and total available market, we’ve had a very large share of the desktop, laptop, and end user compute space, but we’ve had a small market share when it comes to advanced solution technology manufacturers,” Crockett says. “All of our growth over the next 10 to 15 years is going to come from advanced technology vendors, because that’s where we’re so under indexed.”

Several of those vendors, including AMD, Extreme Networks, Fortinet, and HPE, made general session presentations at NEXT+. D&H itself made a point of underscoring its ability to wrap assessment, implementation, and management support around the products those companies sell for partners new to them.

“The mid-market partners we’ve grown up with and helped mature along the way may not have a deep bench of technical resources in a specific product line,” Crockett notes. “We just want to help them be able to deliver on the associated services that would go along with an advanced solutions purchase.” The idea, he continues, is to help partners add profitable new revenue streams faster and with fewer upfront investments by embracing a “borrow, not build” model.

“The professional services growth that we’ve had in the last couple of years has been based on that,” Crockett says. “Borrow our facility, we’ll do the pre-deployment work. Borrow our technical resources, we’ll do the onsite installation.”

Helping partners enter unfamiliar markets rapidly is a priority for D&H in areas beyond services too.

“We need to be able to provide them vendor-agnostic consultative pre-sales enablement, technical resources, people who know the OEM programs, how to apply for the best economics, how to make sure they take advantage of all their backend programs and post-sales service and support,” Crockett says, “all the things they need to learn about manufacturers that are new to them.”

Share

Remember that whole managed services thing?

Interesting fact about those end user compute partners at NEXT+: A lot of the same ones intrigued enough about advanced solutions to make the trip to Austin are also intrigued about managed services. Blair said as much during his keynote while citing data showing that 75% of IT spending is now on operational versus capital expenses.

“If I would have shown you the OpEx to CapEx ratio a couple of years ago, this would have been swapped. So it would have been 40% OpEx and 60% CapEx,” he said. As a result, he added, “many of you that were in the traditional VAR/resell model are becoming MSP-like. It’s because you’re paying attention to how your customer is buying.”

And still learning how to accommodate that demand, he could have added, which is why D&H recently launched its Success Path to MSP Toolkit, a series of live and on-demand webinars offering detailed guidance on the nuances of launching a managed services practice.

“You don’t want to build out a service desk and a NOC or a SOC without understanding how you need to thoughtfully consider changing compensation models for your sales organization to drive that behavior” for example, Crockett says. “You’ve got to be a little more methodical, a little more coordinated about making that leap.”

The kit includes additional information about automating and scaling managed service offerings, adding managed security capabilities, zero trust, cloud security, and more.

“We found that many of our partners who are somewhere on that journey of transitioning from more of a VAR or a system integrator into becoming a managed service provider need a kit that brings all these fragmented tool sets and processes and different software options out there into some sort of coordinated discussion,” Crockett says.

The toolkit’s useful in a further, less intentional way as well for those of us who’ve been covering the shift from VAR-based business models to managed services for over two decades now. Cycles like the AI one just getting underway take a very long time to play out, it shows. There will probably be partners gratefully consuming Success Path to AI Toolkits many years from now.

It takes conviction, I’d argue, to launch a service desk automation application right now, like the company you’ll read about later in this post, given how many other vendors are doing the same thing.

It takes something altogether different, however, to fund the creation of an entire managed services suite out of your own pocket and then launch it into a market full of brand-name incumbents with broad, deeply entrenched user bases and heaps of private capital to draw on.

Courage? Craziness? Perhaps, but I’m going to go with audacity.

Meet IgnitHQ, an upstart MSP platform maker with audacious ambitions to beat the likes of ConnectWise and Kaseya at their own game by offering the kind of solution it contends both vendors would be selling if they were starting from scratch instead of burdened by legacy code.

“The incumbents are describing where they want to go,” says IgnitHQ founder and CEO Yaron Baitch (pictured). “We are already there.”

Where that is more specifically is a solution generally available for a few weeks now with five core attributes:

1. It’s expansive. Surprisingly so, in fact, given its youth. Developed over the last two years, the solution includes more than 80 modules spanning from RMM, PSA, compliance, and documentation to quoting, billing, and beyond.

“No additional functionality outside of our platform is required aside from endpoint protection and backup,” Baitch says. “We’re not going to touch those two things because very clearly there are unbelievable products out there that are really good.”

2. It’s built atop a single, unified database. According to Baitch, this is one of the product’s most critical design principles.

“We have one database that everything lives out of,” he says. “We want to make sure everything is managed with a single source of truth.” That’s something market leaders often claim to provide but don’t, Baitch contends, mostly because they built much of their platforms through acquisitions.

“They have a core system and then they bring another component on and then throw an API on it and a logo, and that’s called integration,” he says. “That’s not integration. In essence, that’s still a separate, disparate database.”

3. It’s AI-native. Unlike ConnectWise and Kaseya, which are both in different ways adding autonomous AI to existing platforms, IgnitHQ built AI into its solution from the start.

“Built-in beats bolted-on every time,” Baitch says, mostly because it provides visibility and control that solutions with layered-on AI and fragmented data can’t mimic.

“Our AI engine is called Duke, and Duke is basically completely cross-corpus aware of the whole platform,” Baitch says. “No matter where you are, Duke knows and it’s able to reference data from the other parts.”

4. It’s affordably priced. According to Baitch, this too is a core design principle, and one that gives IgnitHQ an edge over legacy alternatives.

“Their cost is so expensive and changing is so expensive and their long-term contracts are so expensive,” he says. “We wanted to level the playing field.”

Pricing for IgnitHQ starts at a flat $499 a month for a Starter plan with support for up to 10 technicians and 500 managed endpoints. The more feature-rich Professional plan with unlimited managed clients and techs sells for $999 a month.

5. It’s scalable. One of the system’s early adopters, in fact, brought roughly 897,000 tickets along with them, and the company has tested the solution in the lab against as many as 5 million.

“We still had sub-60ms response time,” Baitch says.

That makes the solution appropriate for large as well as small MSPs, he adds, noting that a private equity-backed rollup with an MSP portfolio “in the high double digits” is about to begin piloting it.

Baitch is well aware, of course, that convincing people to take a chance on an untested newcomer won’t be easy despite all of that. To de-risk the process, IgnitHQ features a “dual-write bridge” that saves data simultaneously to its own database and an MSP’s current tool stack.

“It allows you to use your existing platform and IgnitHQ at the same time” and then pick whichever you prefer without losing anything added during the evaluation process, Baitch says.

Whether that will be enough to drive serious adoption is anyone’s guess. A bootstrapped company with essentially no brand equity at present, IgnitHQ can’t afford giant marketing campaigns. Though who knows, Baitch notes. Maybe that will change some day.

“We’re being very selective about what type of conversations we want to have,” he says, “but there are basically people knocking on our door to help us fund this.”

GenticFlow says trust in us for help desk automation

I rolled the dice last November and predicted that trust will be the word of the year in technology for 2026. It’s looking like a safer and safer bet all the time.

The particular technology I had in mind at the time, of course, was AI, and for obvious reasons. As more and more of what software does happens autonomously, out of view, and very, very rapidly, questioning the safety and efficacy of that software’s output is all but inevitable. And sure enough, study after study after study published in the months since my prediction has revealed the gap between the spending AI is inspiring on the one hand and the uneasiness it’s creating on the other. The gap’s so big, in fact, that Veeam is betting its future around closing it.

So to a great extent is GenticFlow, an AI-powered help desk automation startup that’s as serious about earning the trust of its users as it is about enabling better, faster resolution of technical issues.

“The number one issue that we have to address head-on is trust,” says Marius Mihalec, the company’s founder and CEO. “You break the trust, you break everything.”

The lengths to which GenticFlow goes to avoid that fate are apparent throughout the product. Like solutions you’ve read about here before and others you haven’t yet, the system automatically diagnoses end user help desk requests. Unlike at least some such systems, however, it addresses those requests without human oversight only in limited cases authorized ahead of time, generally in response to the simplest of issues, like password resets and printer restarts.

“Every workflow has an approval policy you assign where one or multiple team members get to approve before certain steps that carry risk can be executed,” Mihalec says. “I don’t think it’s very responsible for anyone to say autonomous anything.”

Approvals are based on detailed diagnostic information collected directly from the endpoint by a lightweight, RMM-like agent and inserted automatically in the ticket, Mihalec adds.

“What makes that useful, and different from tools that manage the ticket, answer the user, summarize the thread, or route the request, is that it is connected to real-time device investigation and action,” he says.

To further build trust, Mihalec notes, GenticFlow carefully documents every action it takes in formats MSPs can both inspect easily themselves and share easily with compliance auditors and cyber insurers.

“Everything is fully logged,” he says, creating a “proof layer” that work done quickly and invisibly was also completed responsibly and effectively.

Not to mention affordably. At a time when only 8% of organizations are extremely confident they understand what running AI services costs them and unpredictable usage-based AI billing is rapidly becoming the norm, GenticFlow makes a point of providing thorough reporting and forecasting data on token consumption.

“We’re very transparent about that,” Mihalec says.

It’s reflected in the system’s pricing too. Each of the product’s two base plans comes with a monthly allowance of tokens sufficient to process several hundred tickets.

“If you’re a light to medium user, that’s enough,” Mihalec notes, adding that heavier users can either pay GenticFlow $1 for every additional million tokens they consume or buy and bring their own tokens from the third-party LLM of their choice.

GenticFlow, which currently has about 30 users, is the second solution Mihalec has sold to MSPs. The first, called Pulseway and fully owned by Kaseya as of a year ago after years of partnering, had already established a foothold as a cloud-first, mobile-first alternative to legacy RMM/PSA platforms when I first wrote about it nearly a decade ago. The new solution aims to offer a similar alternative not only to old school management tools but to fully autonomous ones as well.

“GenticFlow is AI-first, but not AI-only,” Mihalec says.

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Over on the Business of Tech

Host Dave Sobel spoke last week about Veeam’s big new data and AI play, equally big channel plays from Anthropic and OpenAI, and why MSPs aren’t providing the AI governance help SMBs so badly need with … me. Listen in here.

Learning from the AI collective

It’s best to avoid generalizations as a rule, but I’d say it’s generally true nonetheless that taking on a challenge all by yourself is a bad idea for entrepreneurs, and the harder the challenge, the truer that is.

That’s worth keeping in mind if you provide IT services to SMBs, because according to Jerry Koutavas, CEO of MSP community The ASCII Group, the challenges you face at present adjusting to the rise of AI may be your toughest ever.

“It’s a significant pivot, something that’s more difficult than the transition from break-fix to being an MSP,” said Koutavas on the sidelines of last week’s ASCII Edge event near Seattle. Think about it, he continued.

“When people moved from break-fix to becoming an MSP, it was in their economic interest to drive their customers to that model,” Koutavas (pictured above) notes. “It was a means for them to grow, smooth out cash flow, and service customers in a unique way.”

This transition is different. Your clients will profit from the AI services you provide them if you do your job right, but you might not.

“Everything is individualized,” Koutavas observes. “If I go into a particular client and they have interest in AI, it’s unique to them, it’s unique to their business, unique to their problems.” How’s an MSP supposed to scale an answer to something like that, especially given that any answer they arrive at this month could be obsolete next month. There was a time when prompt engineering services looked like a good money maker, for example.

“That’s dead in the water today,” Koutavas says. “The technology is shifting and changing so fast that it’s hard to stabilize on a strategy.”

And therefore hard to blame people who successfully made the change from break-fix to managed services and then from on-prem to SaaS for bowing out now rather than reinvent themselves yet again.

“There’s conversations taking place behind closed doors that we’re going to lose 20 to 30 percent of the MSPs that aren’t going to pivot, and it’s sort of startling to hear that from people that are in the industry as long as I have been and it’s a reality check,” said Koutavas during a keynote presentation.

A worrying one too, obviously. The more Koutavas thinks about it, however, the less worried he becomes.

“Sure, there’s going to be some MSPs that have reached a certain point in their business that they’re going to say, ‘OK, I’m going to retire and that’s all.’ But what’s great about this industry is that we learn from each other,” he says.

Great and defining. For as long as managed services as we know them have existed, which is to say over two decades now, MSPs have been freely sharing knowledge with actual or potential competitors. That’s easy to take for granted if you’ve spent as much time in the industry as I have, but it absolutely floored Manny Rivelo when he became CEO of ConnectWise.

“This is a unique community,” Rivelo said during a conference in London last year. “This is a community that helps each other drive success. You tell each other your best secrets and how to increase your profitability, how you drive your revenue.”

Good luck finding that in any other service industry. “MSPs can say, ‘I have a client that’s experiencing this. I’m thinking about that solution or this solution. What have you guys heard and what have you tried?’ You’ll get a dozen answers inside of ten minutes,” says Brad Gross, an attorney who serves MSPs, during an episode of the podcast I co-host. “That doesn’t exist for doctors. It doesn’t exist for lawyers or accountants.”

And it’s why Koutavas believes the MSP community will weather this latest, hardest transition successfully. “Members are going to teach members what they’ve done and how it impacted their business, and that’s going to be the catalyst to help our community move ahead,” he says.

It’s happening already, in fact. “The collaboration that’s taking place is a lot stronger than I’ve ever seen from a community perspective,” Koutavas says. “We just had a member meeting here, and we had a couple members talk about what they’re building internally for the organization and I’m absolutely blown away.”

The ASCII Group’s trying to facilitate more such exchanges through its AI Collective program.

“It’s a peer initiative,” Koutavas says. “We’re basically gathering members that have built specific tools around AI and allowing them to teach other members about those particular services.” The result, he adds, is classic community.

“Everyone moves forward.”

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Cracking the Level 3 training conundrum

My previous post, which discussed the mystery of where tomorrow’s Level 3 technicians will come from once AI’s doing all the Level 1 and 2 work, mentions a thought on the matter by Joshua Skeens, CEO of mega MSP Logically. Hiring people with high potential but no experience and then training them for a year, he said last July, might be the only solution to the puzzle.

Well, Skeens has had more time to ponder the topic since then, and he dropped me a line in email to share his current view, which is that the same AI making L1 and L2 jobs a thing of the past can theoretically prepare people for L3 positions in way less than a year.

“With AI’s current abilities, I believe that if you find the right individuals, you can actually ramp employees quicker from an L1 to L2 to L3 model than has ever been possible before,” Skeens writes. Building a repeatable process for that will take effort, he continues, but he’s done similar things in the past.

“Before AI, we took entry-level employees, who would normally not be providing actual customer support for 100 to 180 days, and had them on the phone in under 2 weeks and very operational in 30 days,” Skeens says. “This was a very structured training we put them through, but it worked extremely well and actually made the employees have greater job satisfaction because they felt more like contributing members of the team almost immediately. Leveraging AI, I believe you can do the same, but not only ramping employees but jumping them levels faster.”

It’ll help, he adds, that tomorrow’s Level 3s, unlike today’s, will be thoroughly familiar with AI.

“A 10yr old by the time they enter the workforce would have spent their entire life using technology and over half of it using AI,” Skeens writes, noting that vocational programs tailored specifically to the needs of MSPs and MSSPs could give future L3s a head start too.

“I can see a world where we hire an L1 candidate, and they work ½ days and then bootcamp for ½ days with very specific training and testing for the first 30 days. At the end of day 30, you likely have an L2 employee moving towards an L3 with more training.”

But enough about AI. Let’s talk security.

I’m not the only one who thinks LLMs like Anthropic’s Mythos make left-of-boom prevention more important than before relative to right-of-boom detection and response. ThreatLocker CEO Danny Jenkins does too, and he explains why in the latest episode of MSP Chat, the podcast I co-host. Tune in here.

Also worth noting

• Food for thought, MSPs: You don’t have to be as big as ePlus to launch a private AI infrastructure managed service.

• Sherweb and HaloPSA have a new integration designed to automate cloud billing workflows.

• Proofpoint’s new Active Exploits Protection is designed to detect and block attacks exploiting vulnerabilities before patches are available or applied.

• Proofpoint’s new 365 Total Protection platform, meanwhile, aims to help MSPs deliver integrated Microsoft 365 security services.

• CrowdStrike’s newly expanded Project Quiltwork employs alliances with leading cyber insurers to mitigate financial and security risks associated with frontier AI technologies.

• Check Point’s new Agentic Exposure Validation offering is designed to help defenders spot the kind of vulnerabilities advanced AI models can now uncover before attackers do.

• Jonathan Berger is the new SVP of global channels and alliances at SonicWall.

• HYCU’s new AI Resilience (aiR) solution aims to turn backup data from dozens of applications into a live, actionable intelligence resource for security, compliance, and IT teams.

• Reinvent Telecom’s new MyCloud Managed Security service lets MSPs and resellers deliver 24/7 threat monitoring, vulnerability management, and managed XDR.

• APX Net is partnering with AVANT to give the latter’s partners access to the former’s carrier-agnostic fiber and dedicated internet solutions through a single-source procurement, billing, and support model.

It’s best to avoid generalizations as a rule, but I’d say it’s generally true nonetheless that taking on a challenge all by yourself is a bad idea for entrepreneurs, and the harder the challenge, the truer that is.

That’s worth keeping in mind if you provide IT services to SMBs, because according to Jerry Koutavas, CEO of MSP community The ASCII Group, the challenges you face at present adjusting to the rise of AI may be your toughest ever.

“It’s a significant pivot, something that’s more difficult than the transition from break-fix to being an MSP,” said Koutavas on the sidelines of last week’s ASCII Edge event near Seattle. Think about it, he continued.

“When people moved from break-fix to becoming an MSP, it was in their economic interest to drive their customers to that model,” Koutavas (pictured above) notes. “It was a means for them to grow, smooth out cash flow, and service customers in a unique way.”

This transition is different. Your clients will profit from the AI services you provide them if you do your job right, but you might not.

“Everything is individualized,” Koutavas observes. “If I go into a particular client and they have interest in AI, it’s unique to them, it’s unique to their business, unique to their problems.” How’s an MSP supposed to scale an answer to something like that, especially given that any answer they arrive at this month could be obsolete next month. There was a time when prompt engineering services looked like a good money maker, for example.

“That’s dead in the water today,” Koutavas says. “The technology is shifting and changing so fast that it’s hard to stabilize on a strategy.”

And therefore hard to blame people who successfully made the change from break-fix to managed services and then from on-prem to SaaS for bowing out now rather than reinvent themselves yet again.

“There’s conversations taking place behind closed doors that we’re going to lose 20 to 30 percent of the MSPs that aren’t going to pivot, and it’s sort of startling to hear that from people that are in the industry as long as I have been and it’s a reality check,” said Koutavas during a keynote presentation.

A worrying one too, obviously. The more Koutavas thinks about it, however, the less worried he becomes.

“Sure, there’s going to be some MSPs that have reached a certain point in their business that they’re going to say, ‘OK, I’m going to retire and that’s all.’ But what’s great about this industry is that we learn from each other,” he says.

Great and defining. For as long as managed services as we know them have existed, which is to say over two decades now, MSPs have been freely sharing knowledge with actual or potential competitors. That’s easy to take for granted if you’ve spent as much time in the industry as I have, but it absolutely floored Manny Rivelo when he became CEO of ConnectWise.

“This is a unique community,” Rivelo said during a conference in London last year. “This is a community that helps each other drive success. You tell each other your best secrets and how to increase your profitability, how you drive your revenue.”

Good luck finding that in any other service industry. “MSPs can say, ‘I have a client that’s experiencing this. I’m thinking about that solution or this solution. What have you guys heard and what have you tried?’ You’ll get a dozen answers inside of ten minutes,” says Brad Gross, an attorney who serves MSPs, during an episode of the podcast I co-host. “That doesn’t exist for doctors. It doesn’t exist for lawyers or accountants.”

And it’s why Koutavas believes the MSP community will weather this latest, hardest transition successfully. “Members are going to teach members what they’ve done and how it impacted their business, and that’s going to be the catalyst to help our community move ahead,” he says.

It’s happening already, in fact. “The collaboration that’s taking place is a lot stronger than I’ve ever seen from a community perspective,” Koutavas says. “We just had a member meeting here, and we had a couple members talk about what they’re building internally for the organization and I’m absolutely blown away.”

The ASCII Group’s trying to facilitate more such exchanges through its AI Collective program.

“It’s a peer initiative,” Koutavas says. “We’re basically gathering members that have built specific tools around AI and allowing them to teach other members about those particular services.” The result, he adds, is classic community.

“Everyone moves forward.”

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I rolled the dice last November and predicted that trust will be the word of the year in technology for 2026. It’s looking like a safer and safer bet all the time.

The particular technology I had in mind at the time, of course, was AI, and for obvious reasons. As more and more of what software does happens autonomously, out of view, and very, very rapidly, questioning the safety and efficacy of that software’s output is all but inevitable. And sure enough, study after study after study published in the months since my prediction has revealed the gap between the spending AI is inspiring on the one hand and the uneasiness it’s creating on the other. The gap’s so big, in fact, that Veeam is betting its future around closing it.

So to a great extent is GenticFlow, an AI-powered help desk automation startup that’s as serious about earning the trust of its users as it is about enabling better, faster resolution of technical issues.

“The number one issue that we have to address head-on is trust,” says Marius Mihalec, the company’s founder and CEO. “You break the trust, you break everything.”

The lengths to which GenticFlow goes to avoid that fate are apparent throughout the product. Like solutions you’ve read about here before and others you haven’t yet, the system automatically diagnoses end user help desk requests. Unlike at least some such systems, however, it addresses those requests without human oversight only in limited cases authorized ahead of time, generally in response to the simplest of issues, like password resets and printer restarts.

“Every workflow has an approval policy you assign where one or multiple team members get to approve before certain steps that carry risk can be executed,” Mihalec says. “I don’t think it’s very responsible for anyone to say autonomous anything.”

Approvals are based on detailed diagnostic information collected directly from the endpoint by a lightweight, RMM-like agent and inserted automatically in the ticket, Mihalec adds.

“What makes that useful, and different from tools that manage the ticket, answer the user, summarize the thread, or route the request, is that it is connected to real-time device investigation and action,” he says.

To further build trust, Mihalec notes, GenticFlow carefully documents every action it takes in formats MSPs can both inspect easily themselves and share easily with compliance auditors and cyber insurers.

“Everything is fully logged,” he says, creating a “proof layer” that work done quickly and invisibly was also completed responsibly and effectively.

Not to mention affordably. At a time when only 8% of organizations are extremely confident they understand what running AI services costs them and unpredictable usage-based AI billing is rapidly becoming the norm, GenticFlow makes a point of providing thorough reporting and forecasting data on token consumption.

“We’re very transparent about that,” Mihalec says.

It’s reflected in the system’s pricing too. Each of the product’s two base plans comes with a monthly allowance of tokens sufficient to process several hundred tickets.

“If you’re a light to medium user, that’s enough,” Mihalec notes, adding that heavier users can either pay GenticFlow $1 for every additional million tokens they consume or buy and bring their own tokens from the third-party LLM of their choice.

GenticFlow, which currently has about 30 users, is the second solution Mihalec has sold to MSPs. The first, called Pulseway and fully owned by Kaseya as of a year ago after years of partnering, had already established a foothold as a cloud-first, mobile-first alternative to legacy RMM/PSA platforms when I first wrote about it nearly a decade ago. The new solution aims to offer a similar alternative not only to old school management tools but to fully autonomous ones as well.

“GenticFlow is AI-first, but not AI-only,” Mihalec says.

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OK, I lied.

I said in my last post that I’d be taking the week off. And I did in fact just finish a gloriously indulgent vacation (photographic evidence above) involving a lot of eating, snoozing, and sunbathing. But I’m not taking the week off exactly, because my vacation reading sparked a few wee thoughts worth spending my long trip home to Seattle getting down into words.

Now let’s stipulate upfront that your idea of vacation reading may not be the same as mine. But no kidding, I really did read this wonderfully nerdy academic paper poolside last week, months after first coming across it and wishing I had time to give it a thorough look. It covers a lot of ground and I encourage you to skim read the whole thing. But the nub of its argument is that the rapidly growing sophistication of agentic AI is creating a:

“…collision of two racing cost curves: an exponentially decaying Cost to Automate (cA), driven by compute and accumulated knowledge, and a biologically bottlenecked Cost to Verify (cH), bounded by humantime and embodied experience. This structural asymmetry widens a Measurability Gap (Δm) between what agents can execute and what humans can afford to verify, and determines the verifiable share of deployment (sv) that separates truly productive agentic output from merely plausible output.”

In other words, as AI becomes increasingly capable of labor only humans could perform before, the role of humans shifts from doing work to validating that the work agents do on their behalf is accurate and effective. Which is a conundrum, of course, because the more agents come to dominate certain tasks, the harder it will be to find humans qualified to assess whether the agents’ output is any good.

And obviously, when I refer to “certain tasks” here, I’m thinking mostly about help desk tasks, the work that service desk automation systems are getting better and better and better and better at all the time. As I’ve written before, the ability to transfer lower-value administrative chores from people to bots is both a blessing (MSPs using service desk automation software are experiencing 5% to 25% technician productivity improvement, according to Omdia) and a curse, in that people are going to play an indispensable role in Level 3 work at a minimum for a long time to come and no one (like, no one) seems to know where tomorrow’s Level 3s will come from once AI makes human Level 1s and 2s obsolete.

Hence the “biological bottleneck” identified in the research paper. We can’t, or shouldn’t, adopt AI that we can’t validate, we can’t validate AI without deeply experienced humans, and we’re slowly beginning to burn through our supply of deeply experienced humans.

The closest I’ve ever come to an answer to this dilemma is when Joshua Skeens, CEO of mega MSP Logically, speculated that he’ll eventually need to hire bright, young people with L3 potential (referred to as “innate aptitudes” in the research paper) and spend a year plus a whole lot of money training them to do L3 work.

OK, but how. The paper vaguely yet repeatedly suggests “AI-driven synthetic practice,” as in using software to do help desk work on a kind of AI-powered simulator.

Which brings me to the fairly obvious poolside thought that came to mind reading this paper. We’re going to need Level 3 technicians for some time to come. On-the-job training isn’t where we’re going to get them. Training newbies to hold L3 jobs is the best available answer to that problem so far. And “AI-driven synthetic practice” solutions are what we’ll use to provide that training.

Except that there aren’t a whole lot of AI-driven synthetic practice solutions for MSPs out there at the moment. Empath’s software could potentially do the job, as could Virti’s with some customizing. But it seems like vendors ought to be moving as swiftly as possible to create more such solutions given that the total addressable market for them is basically every MSP on earth, and probably every corporate IT department to boot.

More reasons to get smart about token spending sooner versus later

Ready for another good beach read? Try this. It’s a terrific take on the token economics issue I discussed in a somewhat different context a few weeks ago. My point back then was that producing strong, steady margins on AI services is going to be hard for MSPs given that upstream AI companies increasingly employ usage-based billing schemes that make costs hard to predict and downstream end users want predictability in their IT spending.

And to say that AI companies are increasingly charging for consumption is to understate things. In just the six weeks since that first post of mine went live, GitHub and Anthropic have both gone all-in on usage-based billing.

For a very good reason, of course. The data centers that host AI software are extremely expensive and the LLM makers spending absurd amounts of money to build more of them can’t afford to sell tokens for less than they cost to manufacture anymore.

As it happens, that same dynamic plays into a phenomenon Anton Leicht discusses in the blog post I linked to up above. While token costs have been dropping in aggregate over time, they’re actually rising for the newest, most powerful models. To cite the latest example, Gemini 3.5 Flash may well do what used to take a developer days “in a fraction of the time, often at less than half the cost of other frontier models,” per Google’s claim, but it costs more than earlier versions of the Flash family, not less.

Meanwhile, as the newest models get to be really powerful, a la Anthropic’s Mythos, both cyber security and national security concerns will limit who gets access to them and when.

Which suggests that we’re entering a have-and-have-not era in AI in which businesses with big budgets, big brands, and political pull get the premium tokens and everyone else will make do with what’s left. Further suggesting that businesses with modest budgets, obscure brands, and no political pull (like SMBs) will badly need MSPs capable of doing two things:

1. Provide actionable guidance on balancing cost against performance when deciding which version of which model to apply against each of their workloads.

2. Wring as much impact as possible out of every sub-premium token they have access to and can afford.

Could be wrong, but sounds like another area where a new class of software products, or at least features, could be extremely useful.

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Meet Virtua’s excuse eraser for managing Macs

But then again, why spend a lot of time mastering the arcana of a brand new field evolving rapidly in real time when there’s an easier way to burnish customer loyalty and expand your top line? Heck, if you’re reading this on your phone you might be holding the modest little goldmine I’m referring to in your hand right now.

I’m talking about Apple device management. To be sure, managing endpoints is about as commoditized a service as an MSP can offer, but as long as businesses still use endpoints and endpoints still experience downtime and security breaches, businesses are going to need someone to manage their devices, and if it can’t be in-house IT it’ll be an MSP instead.

Yet, according to Justin Esgar, CEO of New York City-based Apple support and solution specialist Virtua Computers, most MSPs studiously blinder themselves to the existence of Macs, iPhones, and iPads in the environments they’re responsible for.

“The PC MSPs just don’t want to talk about it or deal with it,” says Esgar (pictured), noting that one reason he knows this to be the case is how often an MSP calls him in to manage the five Macs in a 100-endpoint office they support.

“They’re leaving money on the table,” Esgar observes. Or worse yet, he adds, subtracting money from their top and bottom lines.

“They’re harming their relationship with their customers,” says Esgar, an Apple Premium Technical Partner with 18 years of experience who also co-hosts the reliably excellent All Things MSP podcast. “To say, ‘We don’t do that because it’s a Mac or an iPhone or an iPad,’ is a really damaging line for an MSP to say to a customer. So they’re either going to lose money straight up by not supporting it, or they’re going to lose the customer and then lose money.”

Maybe a lot of money at that. Apple products currently account for 12.6% of global desktop/laptop market share (23.9% in the U.S.), according to StatCounter, and 21% of global smartphone share, according to IDC. The numbers are even higher in specific verticals, Esgar notes.

“Doctors use iPhones. Truck drivers use iPads. Those devices need proper management,” he says. “These MSPs are often ignoring 10 to 30 percent of a client’s fleet because it’s Apple.”

He knows why they’re not supporting all that hardware, too. “They don’t know how. They don’t have the bandwidth to learn.” And besides, no one needs to worry about Apple devices anyway, right?

“They’re fed a lot of information from Apple like Macs are secure, so it should just be fine, but it’s not,” Esgar says.

Indeed, turns out security incidents involving Apple devices really are a thing. And while software for mitigating that thing is available from Microsoft, via Intune, Jamf, and Addigy, among others, deploying a tool doesn’t necessarily close an MSP’s Apple management skills gap.

That realization is a big part of the thought process that led Esgar to envision an outsourced Apple management service for MSPs that don’t have Apple skills, don’t use Apple tools, don’t wish to change either fact, but do wish to manage Apple devices and make money doing so. Called VirtuaCare, the service provides either white-label or sub-agent Apple management support on a 24/7 basis. You keep the relationship, we handle the Apple stuff, Esgar says.

Partners pay by the hour rather than monthly subscription fees. “We don’t want to lock you into a per-client, per-device thing,” Esgar says. “We know PC MSPs have a lot of clients, and maybe this person has two Macs and that client’s got four iPads, or whatever.”

Partners can buy hours at $200 apiece in five-, 10-, 15-, or 20-hour blocks. The more hours you buy, the more ancillary benefits (like Slack channel access and monthly strategy calls) you get, and the shorter your guaranteed response time.

From Esgar’s perspective, though, VirtuaCare’s most significant ROI, which you get no matter how many hours you buy, is the satisfaction of knowing you’re doing the job you aspire to do for all of your clients all of the time.

“If you’re a PC MSP and the customer says, ‘Jim’s computer isn’t connecting to the network,’ you would never say, ‘We don’t do firewalls.’ That’s not a thing we do as MSPs, right? We want to make sure the whole thing works,” Esgar says. “PC MSPs, Mac MSPs, we need to just start being MSPs.”

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You certainly can, per a separate post, spend a lot of time mastering the arcana of a brand new field evolving rapidly in real time. But why bother when there’s an easier way to burnish customer loyalty and expand your top line? Heck, if you’re reading this on your phone you might be holding the modest little goldmine I’m referring to in your hand right now.

I’m talking about Apple device management. To be sure, managing endpoints is about as commoditized a service as an MSP can offer, but as long as businesses still use endpoints and endpoints still experience downtime and security breaches, businesses are going to need someone to manage their devices, and if it can’t be in-house IT it’ll be an MSP instead.

Yet, according to Justin Esgar, CEO of New York City-based Apple support and solution specialist Virtua Computers, most MSPs studiously blinder themselves to the existence of Macs, iPhones, and iPads in the environments they’re responsible for.

“The PC MSPs just don’t want to talk about it or deal with it,” says Esgar (pictured), noting that one reason he knows this to be the case is how often an MSP calls him in to manage the five Macs in a 100-endpoint office they support.

“They’re leaving money on the table,” Esgar observes. Or worse yet, he adds, subtracting money from their top and bottom lines.

“They’re harming their relationship with their customers,” says Esgar, an Apple Premium Technical Partner with 18 years of experience who also co-hosts the reliably excellent All Things MSP podcast. “To say, ‘We don’t do that because it’s a Mac or an iPhone or an iPad,’ is a really damaging line for an MSP to say to a customer. So they’re either going to lose money straight up by not supporting it, or they’re going to lose the customer and then lose money.”

Maybe a lot of money at that. Apple products currently account for 12.6% of global desktop/laptop market share (23.9% in the U.S.), according to StatCounter, and 21% of global smartphone share, according to IDC. The numbers are even higher in specific verticals, Esgar notes.

“Doctors use iPhones. Truck drivers use iPads. Those devices need proper management,” he says. “These MSPs are often ignoring 10 to 30 percent of a client’s fleet because it’s Apple.”

He knows why they’re not supporting all that hardware, too. “They don’t know how. They don’t have the bandwidth to learn.” And besides, no one needs to worry about Apple devices anyway, right?

“They’re fed a lot of information from Apple like Macs are secure, so it should just be fine, but it’s not,” Esgar says.

Indeed, turns out security incidents involving Apple devices really are a thing. And while software for mitigating that thing is available from Microsoft, via Intune, Jamf, and Addigy, among others, deploying a tool doesn’t necessarily close an MSP’s Apple management skills gap.

That realization is a big part of the thought process that led Esgar to envision an outsourced Apple management service for MSPs that don’t have Apple skills, don’t use Apple tools, don’t wish to change either fact, but do wish to manage Apple devices and make money doing so. Called VirtuaCare, the service provides either white-label or sub-agent Apple management support on a 24/7 basis. You keep the relationship, we handle the Apple stuff, Esgar says.

Partners pay by the hour rather than monthly subscription fees. “We don’t want to lock you into a per-client, per-device thing,” Esgar says. “We know PC MSPs have a lot of clients, and maybe this person has two Macs and that client’s got four iPads, or whatever.”

Partners can buy hours at $200 apiece in five-, 10-, 15-, or 20-hour blocks. The more hours you buy, the more ancillary benefits (like Slack channel access and monthly strategy calls) you get, and the shorter your guaranteed response time.

From Esgar’s perspective, though, VirtuaCare’s most significant ROI, which you get no matter how many hours you buy, is the satisfaction of knowing you’re doing the job you aspire to do for all of your clients all of the time.

“If you’re a PC MSP and the customer says, ‘Jim’s computer isn’t connecting to the network,’ you would never say, ‘We don’t do firewalls.’ That’s not a thing we do as MSPs, right? We want to make sure the whole thing works,” Esgar says. “PC MSPs, Mac MSPs, we need to just start being MSPs.”

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Editor’s note: Even certified channelholics need a break now and again, which is why the one responsible for this publication will be vacationing rather than writing next week. We’ll be back in two weeks with our next edition.

Big swing.

They’re the first two words that popped into my head when an analyst attending Veeam’s annual VeeamON conference last week asked me what I thought about the keynote CEO Anand Eswaran had concluded minutes earlier. Because Eswaran hadn’t just announced a new or updated product. He had unveiled something intended to define an entirely new product category.

Or more than that, really. Veeam says it’s pioneering an entirely new platform category in response to a fact of life about data in the age of AI that like “big swing” boils down to two words:

Shit happens.

Or “things go wrong,” as Veeam might more delicately put it. Which they have for a long time where data’s involved, of course. Ransomware may be a growing problem, but it’s certainly not a new one, nor are plain old accidental file deletions. But with AI, those are only two of many ways things can go wrong. These days, data also gets inadvertently exposed to people who shouldn’t see it, hallucinated into existence by overeager chatbots, and deleted by well-intentioned but utterly incompetent agents.

“You can Google ‘AI agent going rogue’ every day, and you’re going to find a new news article about it deleting a database, deleting a file, deleting your email, etc., etc.,” notes Brad Linch, director of enterprise strategy at Veeam.

And that’s true today, six-ish months after IDC pegged the global population of agents at about 28.8 million. Hard to imagine how much havoc agents will be wreaking in 2030 when there will be 2.3 billion of them, including at least 1 billion just at SoftBank, assuming its CEO has his way. They’ll all be moving very, very rapidly 24/7, largely out of view and often with privileges they shouldn’t have.

“The new failure isn’t just a breach,” Eswaran (pictured) says. “It’s actually a wrong decision which you take executed at machine speed before anyone notices.”

And given that AI is only as good as the data it draws on, much of that data isn’t terribly good right now, and AI itself is corrupting the rest, wrong decisions are apt to be pretty common.

“You can’t deploy AI safely if you’re feeding it inaccurate or old or stale data,” Linch observes.

Or if you don’t even have all your data under control. According to Eswaran, the average organization has 106 SaaS applications.

“Every one of them is siloed. Every one of them has their own permissions. Every one of them has their own copy of the truth,” he says. “AI just unlocked all of it instantly because agents don’t click through interfaces or UXs. They reach directly into every single system of record.”

On the surface, all of that looks like a series of discrete issues. In reality, Eswaran says, it’s one issue—trust—with multiple dimensions and we’re not ready for it.

“The questions we face now about trusting AI, trusting autonomous action, governing, and recovering at machine speeds are not the questions the industry has trained for and businesses are built for.”

Which is why answering them, Veeam believes, requires a whole new kind of unified platform purpose-built for the security, backup, governance, privacy, and compliance challenges of managing data in the age of AI.

“In the rest of the industry, these live as five separate categories, five separate vendors, five separate dashboards, five different tools,” Eswaran says. “In Veeam’s platform, they unify, they operate together because the only way to close this trust gap is if every domain knows what all the other domains know.”

Building the DataAI Command Platform, as Veeam calls it, involved converging the data protection software the company is still best known for with functionality it acquired last year through its acquisition of data security vendor Securiti AI. The result of that effort is an offering capable of performing four tasks almost every business currently needs to do, given that 97% of them use AI at present, according to Dun & Bradstreet but only 5% think their data is fully AI-ready:

1. Create a comprehensive data map. “Not just at a database level or an S3 bucket level, but at a granular data element level,” Eswaran says.

2. Catalog the permissions and policies associated with that data.

3. Enforce those permissions and policies, in real time and before an agent gone rogue has a chance to violate them.

4. Remediate problems when shit happens, as it inevitably will, with surgical precision.

“When things go wrong, you can’t recover to the last known safe state three days back,” Eswaran says. “When you have 250,000 agents acting in your enterprise on average, that is going to kill your business. Remediation needs to be precise. You must be able to undo just those five seconds of agent action, just that one element in a file which got changed.”

Differentiated margins

We don’t yet know, of course, how well Veeam’s DataAI Command Platform will really do that. For the moment, the precision remediation feature is pretty much limited to Microsoft 365 data, for example, and agents respect no such limits.

But if Veeam delivers everything it’s promising, it’ll have pulled off a kind of ingenious pivot. Rather than get stuck in a dead end offering stand-alone backup to buyers who prefer security platforms or launch a security platform and then play catchup with the likes of CrowdStrike and Palo Alto, Veeam has opted instead to invent a new kind of platform that’s true to its data protection roots yet suited to a new, urgent, and nearly universal set of data-related needs.

It could pay off for Veeam’s partners as well as Veeam itself too. Backup is a thoroughly commoditized service. Helping businesses embrace AI safely isn’t.

“The downside risk of an SMB customer not modernizing is pretty high. The downside risk of it not going well is higher still,” says Shiva Pillay (pictured), Veeam’s general manager and SVP of the Americas. “Our focus is ensuring that data’s trusted so that when you apply AI the benefits that come from AI are exponential.”

Partners who share that focus can set themselves apart from the competition, adds Tony Colon, Veeam’s chief customer officer.

“It’s actually creating a whole new opportunity to differentiate them from the MSPs who are not thinking this way,” he says. “They still want to keep the old school way of running their business. The ones that we’re seeing get the new customer base are the ones that are leading with AI but then showing value around how they protect a customer.”

And charging the kind of premium rates associated with a consultative offering, adds Veeam’s Emilee Tellez, field CTO and director of product strategy.

“This is an opportunity for that partner or that managed service provider to sit down with the customer, really understand what is it that they’re trying to achieve and their overall outcome, and then [show] how you leverage a data and AI trust company to help you get to where you’re trying to go,” she says, noting that the Data and AI Trust Maturity Model Veeam published last week can help structure that conversation.

It’s a conversation likely to yield plenty of project work, adds Linch. “I think there’s a whole lot of opportunity here from an MSP perspective in terms of you plug in a tool that’s going to analyze your data and there’s going to be no shortage of security posture findings,” he says. “The remediation actions that have to happen is where I see a huge opportunity for service providers to assist their end users.”

Acquiring the skills and confidence to do that work shouldn’t be a leap for most MSPs either, according to Pillay.

“If you get into specialized data security posture management, that’s a discipline that might require some effort, but a lot of our MSPs are not only providing data recovery, they’re providing security services as well,” he says. “I don’t think it’s too heavy a lift.”

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Auvik’s see, tell, do roadmap has arrived at do

It’s striking how similar Veeam and Auvik are in their thinking about the relationships linking data, AI, and trust. Veeam believes that acquiring a complete understanding of your data is a precondition to embracing AI with confidence. So does Auvik, albeit in a somewhat different way.

Auvik’s take on the matter begins with a finding by analyst firm EMA that only 44% of IT organizations have complete confidence that their network data is solid enough to support AI-driven network management. Doug Murray (pictured), Auvik’s CEO, thinks he knows why.

“Many organizations lack full visibility,” he says. “They don’t fully understand what’s in their environment—devices, SaaS tools, even shadow AI usage.” Auvik has been providing that visibility since its inception some ten years ago, Murray adds, and building acceptance among users for more ambitious functionality along the way.

“Once they see their environment mapped—devices, configurations, versions—that becomes the baseline for trust and management,” he says.

Auvik is now drawing on that trust to take the last step on the “see, tell, do” roadmap it’s been following since its birth. “See” is the visibility the company’s cloud-based network mapping functionality provides. “Tell” is the alerting capability the company subsequently added; Auvik’s 6,000 customers currently receive over 30 million alerts a year.

That just left “do,” as in the ability to remediate alerts rather than simply issue them. Auvik’s had enough data to support that kind of automation for a while, Murray says, noting that the company has information about 12 million devices, 300 million device configurations and over 500,000 applications on file. What it lacked was a means of putting that data to work in ways that meaningfully raise technician productivity and shorten resolution times.

“If we were to have had this exact conversation three years ago, we might have talked about how we have all of this data and we’re working on an automation strategy. It just so happened that we were remarkably fortunate with the way the world has evolved over the last three years,” Murray says.

He’s referring, of course, to the rapid evolution of first generative and then agentic generative AI, technologies that underpin the functionality in Auvik Aurora, the company’s recently released automated network management, troubleshooting, and optimization capability.

In real time, Auvik says, the new system correlates and prioritizes alerts, identifies where issues are likely occurring and why, and provides customized remediation guidance based on live network data. Users have the flexibility to decide how autonomously the system then acts on that guidance.

“For example, they may create a policy that says if an access point is down and the remediation is to reboot it, then just automatically do that,” Murray explains. Conversely, he continues, they may prefer to address newly reported firewall vulnerabilities themselves.

“It is not full self-driving, network-based infrastructure quite yet,” Murray says.

As the “quite yet” there suggests, though, that’s likely to change over time, as is much else about Aurora.

“You can envision a roadmap where a new Aurora-based feature comes out every month between now and December,” Murray says.

One last note about all that data Auvik’s amassed

For reasons we’ve noted here recently, large volumes of data tend to exert large amounts of gravitational pull in the channel. Auvik sees no reason why it should be an exception to that new law of digital physics.

Though he isn’t specific about plans or timing, Murray clearly envisions a future in which Auvik is the managed services world’s definitive system of record for networking, serving up data to third-party applications and making itself indispensable to a lot of people other than MSPs in the process. Unlike vendors such as Kaseya and ConnectWise with similar ambitions for device and ticketing data, moreover, Auvik thinks it has the network layer to itself.

“Other vendors play roles in RMM, PSA, etc. We integrate with them rather than compete,” Murray says, adding that Auvik’s “superpower” is network visibility and management.

“We aim to be Switzerland in the ecosystem.”

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Also worth noting

• I’m still playing with the new Claude for Small Business, but deeply skeptical that it’s as drop-dead easy as Anthropic claims. AI service opportunity for MSPs?

• Managed services-only investor Top Down Ventures has closed its oversubscribed $28 million Founders Fund I. You’ve read about some of the companies on the receiving end of that money here before.

• Huntress and Acrisure are partnering to offer no-deductible cyber insurance coverage to users of Huntress managed security services.

• ThreatDown Identity Threat Detection and Response, from Malwarebytes, is designed to help security teams detect suspicious activity, misconfigurations, and active attacks targeting user accounts and privileges.

• SonicWall’s new NSv XS virtual firewall extends its Gen 8 platform to cloud environments.

• Fortinet’s using NVIDIA AI platforms and software to deliver GPU-accelerated security across any deployment model through its FortiAIGate solution.

• Arctic Wolf has unveiled a new exposure management platform designed to help organizations identify and prioritize AI-accelerated vulnerabilities faster.

• Thanks to its admission to Anthropic’s Cyber Verification Program, IRONSCALES now has access to frontier AI capabilities purpose-built for adversarial defense.

• The new workflow feature in Keeper Security’s KeeperPAM is designed to let organizations enforce approval-based access controls and time-limited checkout policies for privileged resources.

• A new integration between HackerOne and Wiz feeds the former’s findings directly into the latter’s cloud and AI security platform.

• Rapid7 is offering early access to a new cyber governance, risk, and compliance platform designed to unify security telemetry, risk context, and compliance workflows.

• Scality’s new Autonomous Data Infrastructure aims to help businesses power multiple AI workloads, defend against threats, and maintain sovereign control over data all at once.

• Blumira says that Kindling Pilot, its new agentic AI-powered auto-triage capability, can reduce security alert volumes by 30x to 50x.

• Robert Johnston, who formerly ran N-able’s Adlumin unit, is now its chief innovation officer. Nicole Reineke, who’s responsible among other things for N-able’s new MCP server, is now the company’s chief AI officer.

• Wendy Welch is the new SVP of public sector sales at TD SYNNEX.

• Reinvent Telecom has introduced REVIVE, a unified digital command center for partners to manage their Reinvent-powered technology businesses.

• HPE is now going global with just two distributors: Ingram Micro and TD SYNNEX.

It’s striking how similar Veeam and Auvik are in their thinking about the relationships linking data, AI, and trust. Veeam believes that acquiring a complete understanding of your data is a precondition to embracing AI with confidence. So does Auvik, albeit in a somewhat different way.

Auvik’s take on the matter begins with a finding by analyst firm EMA that only 44% of IT organizations have complete confidence that their network data is solid enough to support AI-driven network management. Doug Murray (pictured), Auvik’s CEO, thinks he knows why.

“Many organizations lack full visibility,” he says. “They don’t fully understand what’s in their environment—devices, SaaS tools, even shadow AI usage.” Auvik has been providing that visibility since its inception some ten years ago, Murray adds, and building acceptance among users for more ambitious functionality along the way.

“Once they see their environment mapped—devices, configurations, versions—that becomes the baseline for trust and management,” he says.

Auvik is now drawing on that trust to take the last step on the “see, tell, do” roadmap it’s been following since its birth. “See” is the visibility the company’s cloud-based network mapping functionality provides. “Tell” is the alerting capability the company subsequently added; Auvik’s 6,000 customers currently receive over 30 million alerts a year.

That just left “do,” as in the ability to remediate alerts rather than simply issue them. Auvik’s had enough data to support that kind of automation for a while, Murray says, noting that the company has information about 12 million devices, 300 million device configurations and over 500,000 applications on file. What it lacked was a means of putting that data to work in ways that meaningfully raise technician productivity and shorten resolution times.

“If we were to have had this exact conversation three years ago, we might have talked about how we have all of this data and we’re working on an automation strategy. It just so happened that we were remarkably fortunate with the way the world has evolved over the last three years,” Murray says.

He’s referring, of course, to the rapid evolution of first generative and then agentic generative AI, technologies that underpin the functionality in Auvik Aurora, the company’s recently released automated network management, troubleshooting, and optimization capability.

In real time, Auvik says, the new system correlates and prioritizes alerts, identifies where issues are likely occurring and why, and provides customized remediation guidance based on live network data. Users have the flexibility to decide how autonomously the system then acts on that guidance.

“For example, they may create a policy that says if an access point is down and the remediation is to reboot it, then just automatically do that,” Murray explains. Conversely, he continues, they may prefer to address newly reported firewall vulnerabilities themselves.

“It is not full self-driving, network-based infrastructure quite yet,” Murray says.

As the “quite yet” there suggests, though, that’s likely to change over time, as is much else about Aurora.

“You can envision a roadmap where a new Aurora-based feature comes out every month between now and December,” Murray says.

One last note about all that data Auvik’s amassed

For reasons we’ve noted here recently, large volumes of data tend to exert large amounts of gravitational pull in the channel. Auvik sees no reason why it should be an exception to that new law of digital physics.

Though he isn’t specific about plans or timing, Murray clearly envisions a future in which Auvik is the managed services world’s definitive system of record for networking, serving up data to third-party applications and making itself indispensable to a lot of people other than MSPs in the process. Unlike vendors such as Kaseya and ConnectWise with similar ambitions for device and ticketing data, moreover, Auvik thinks it has the network layer to itself.

“Other vendors play roles in RMM, PSA, etc. We integrate with them rather than compete,” Murray says, adding that Auvik’s “superpower” is network visibility and management.

“We aim to be Switzerland in the ecosystem.”

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Here’s the latest evidence that AI scrambles everything: people are increasingly using it instead of lawyers to represent them in court.

Well, not exactly, but according to a recent academic paper the percentage of federal civil cases in which someone represents themselves rather than hire an attorney rose by an unprecedented 50+% last year. And yes, AI is at least partially responsible: The number of documents filed in the first 180 days of self-represented cases is up 158% over pre-ChatGPT norms, according to the study, which says that “a large and growing share” of those documents appear to be AI slop generated.

Good news, I suppose, if you hate lawyers but terrible news if you are a lawyer suddenly facing competition from Claude & Gemini LLP. Not to mention rising expectations from your clients, 58% of whom say the technology standards they hold law firms to has risen in the last two years, according to new data from mega mega MSP Integris.

Not unexpectedly, those higher expectations are flowing downstream to MSPs. When asked by Integris to name the biggest challenges they face with their current IT services provider, 30% of law firms cited AI implementation and management, behind only budget and roadmap misalignment.

Could it be that MSPs are moving a little too slowly on AI, and not just in the legal vertical? I mean, they are moving. Per data from GTIA shared here two months ago, 71% of technology partners expect AI to be a growing revenue source in the next two years. Yet only 28% expect that growth to be significant, suggesting that most IT providers are still mastering the technical demands and business implications of what might be the most profound paradigm shift in the history of our industry.

That’s certainly consistent with what Microsoft cloud management vendor Nerdio is witnessing, based on conversations with its leaders at last week’s NerdioCon event in Palm Springs. Though relatively few MSPs consider AI an overhyped fad anymore, according to Will Ominsky (pictured), the VP and GM in charge of Nerdio’s MSP business, only an equally modest number have a repeatable, scalable plan for making money on it. Everyone else is stuck somewhere in between.

“Most MSPs realize they need a strategy,” Ominsky says. “I think the difficulty there is figuring out what’s the winning strategy.”

It’s a legitimate difficulty. “AI is moving so fast,” Ominsky says. “What’s working today, what’s the best model today, might not even be a thing six months from now.”

And we’re not even talking about keeping up with one thing working for one kind of customer, he continues. “I have healthcare, I have legal, I have all these different [industries], and they’re all going to use AI maybe in different ways.”

Placing bets amid all that flux is inherently risky. “You might spend time building out some amazing MCP server or some skills for AI that might be obsolete in six months because there’s some new model or some new kit on the block,” Ominsky observes.

Which is, for sure, a real and potentially expensive danger. But here’s why letting it paralyze you could be dangerous: While you’re noodling your way toward a strategy for profiting from frontier AI technologies, the companies responsible for those technologies are getting a tad impatient.

I’m thinking, of course, about Anthropic and OpenAI, both of which are racing to drive AI adoption, grow revenue, and seize market share ahead of much-anticipated IPOs, and both of which made headlines last week in connection with the launch of services businesses involving a who’s-who of investment world heavyweights ranging from Goldman Sachs, Blackstone, and Apollo Global Management, to TPG, Bain Capital, and Sequoia.

Anthropic’s venture is rumored to have $1.5 billion at its disposal. OpenAI’s is believed to have $4 billion behind it. And unlike the Frontier Alliances program OpenAI announced in February or the Claude Partner Network that Anthropic poured $100 million into in March, the target for these new businesses isn’t giant system integrators and their big business clients.

It’s the M in SMB.

“The organization will work with mid-sized companies across sectors to bring Claude into their most important operations,” an Anthropic blog post reads. And not just on deployment and prompt engineering.

“Applied AI engineers from Anthropic will work alongside the firm’s engineering team to identify where Claude can have the most impact, build custom solutions, and support customers over the long term.”

If that sounds similar to what Shield Technology Partners is doing, with direct support from OpenAI no less, that’s because it is, right down to the fact that OpenAI and Anthropic are both expected to staff their ambitious new businesses via acquisitions of IT services firms.

More on that in a future post. For now, I trust, it’s enough to say that there’d be no need to put $5.5 billion into AI solution building if MSPs were doing it. But they’re not.

“Companies from community banks to mid-sized manufacturers and regional health systems stand to gain from AI, but lack the in-house resources to build and run frontier deployments,” Anthropic writes. And since no one else is stepping up quickly to fill that void, the company implies, we, OpenAI, and most of Wall Street are doing it ourselves.

It’s not just huge, heavily funded service businesses that MSPs have to worry about either. They’re already fighting off the AI consultancies we wrote about last year, and are likely to face competition from a new, nimble generation of AI-native MSPs soon too, Ominsky predicts.

“The barrier to entry to become an MSP is already really low,” he says. “With AI and all of this other stuff, there’s essentially zero barrier to entry. I can go spin up an app, I can go sign up with a few vendors, I can go build an AI strategy, and I don’t have that tech debt and the culture debt that all the existing MSPs out there have.”

The “culture debt” part of that quote alludes to a phenomenon that Rob Rae, corporate vice president of community and ecosystems at Pax8, talked about onstage at NerdioCon. MSPs, he noted, are creatures of habit.

“We do not like change, and this is a significant change,” Rae said. “A lot of MSPs, especially some of the older MSPs, are like, ‘I really don’t want to go through this again.’ But it’s something that’s going to be completely inevitable and I think we’re all just going to have to.”

Go governance

All right, must go faster. But where? Nerdio has a suggestion for getting started directly linked to the thing that all AI users need and few MSPs currently provide: governance.

“MSPs know their customers are using off-the-shelf products. They’re using Claude, they’re using ChatGPT,” says Vadim Vladimirskiy (pictured), the company’s CEO. “They know that’s happening. I’m not sure any are doing much about it.”

That’s partly due to a shortage of AI governance tools at present, he continues. But according to Ominsky, MSPs can get a lot done anyway with tools they already use.

“Every end customer has a Microsoft 365 license. MSPs know how to manage M365, typically Business Premium or higher,” he says. Those SKUs come with solutions like Intune, Defender, and Purview that MSPs can use to deliver governance services unlikely to go out of style no matter how fast or how much AI evolves.

“That’s never going to change,” Ominsky says. “You’re still going to need to secure the user. You’re going to need to secure the data. You’re going to need to secure the device, no matter what it is. That’s something that you as an MSP can spend time on today and it’s not going to be obsolete in six months.”

In the meantime, he adds, Nerdio’s augmenting its solutions with governance-relevant functionality like the new Purview solution baselines and policy management feature in Nerdio Manager for MSP 7.0, which shipped during NerdioCon.

There could be more coming in keeping with Nerdio’s long-time mission to ease the complexity of Microsoft’s latest cloud innovations for people looking to scale and run quickly, Vladimirskiy hints.

“If Microsoft has Copilot agents that MSPs are responsible for deploying, managing, governing, securing, monitoring, etc., that would be a realm where we potentially could play a very significant role to help MSPs manage that very wild, wild west world of AI enablement,” he says.

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Over on The Business of Tech

Host Dave Sobel has thoughts about AI governance too, or more specifically agentic AI governance:

The mechanism is straightforward: the moment AI stops being “a feature you use” and becomes “a thing that acts,” the operational problem shifts from prompt quality to permission design. Agents connect to systems, assume identities, receive scopes, and execute actions—so the real question becomes: what can it touch, what can it change, and what can you roll back quickly if it’s wrong? When organizations can’t answer those questions fast, they buy tooling and services that make the environment enumerable and auditable again.

More here.

Remember the cloud?

Agent management help from Nerdio, if it comes, is a forward-looking prospect. There are plenty of ways for Nerdio partners to make money in the Microsoft cloud today though, Vladimirskiy insists.

“The opportunity for MSPs has been great and it continues to be great and it continues to expand, because the Microsoft ecosystem, which is a core technology stack for many of your, if not all of your, customers grows at a very rapid rate,” he said during a NerdioCon keynote.

Indeed, Microsoft’s Productivity and Business Processes segment, which includes Microsoft 365 and Windows 365, grew revenue 17% year over year in the company’s most recent quarter, and its Intelligent Cloud segment, where Intune and Azure Virtual Desktop reside, reported an even more impressive 30% uptick.

Not surprisingly, given the role Microsoft 365, Windows 365, Intune, and Azure Virtual Desktop all play in its product strategy, Nerdio has racked up good numbers recently too.

“Nerdio’s MSP user base more than doubled since the last NerdioCon,” Joseph Landes (pictured), the company’s president said during a keynote appearance. “The number of AVD tenants that we manage grew by over 80%, which is far ahead of the growth rate of the overall AVD market, which is quite large by now. And our M365 user base grew by over 300%.”

There’s plenty of upside ahead too, he thinks, thanks in part to huge demand by AI data centers for components PC makers rely on.

“Memory and storage costs are expected to rise further and more steeply than previously assumed from Q2, squeezing PC vendor gross margins and forcing them to pass costs through to channel partners and end-customers,” writes Omdia in its latest endpoint forecast. That’s a problem if you manufacture PCs or are planning to buy one for one of your employees.

“But you know what you could do?” asks Landes, slyly, during the latest episode of the podcast I co-host. “You could use the existing hardware and spin up a Windows 365 virtual PC and the user is off and running.”

The story is similar for businesses unwilling or unable to go online only as Windows 365 demands, he continues. “Now Microsoft has AVD Hybrid for those users as well where they can run AVD on existing hardware.”

All bullish signals for Microsoft partners more focused on today’s endpoint products than tomorrow’s AI systems, Landes contends. “I only see the TAM, or the total addressable market, continuing to increase for desktop virtualization.”

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Speaking of the podcast I co-host…

The latest episode features the entire interview with Landes I just quoted from, plus some early thoughts from yours truly on that Anthropic services venture I mentioned earlier. Tune in here.

Microsoft is still interested in MSPs

Regular readers may recall encountering Intune, which I just referenced, and Ominsky, who I’ve quoted extensively, in a story from September about Microsoft’s #IntuneForMSPs program. Launched in collaboration with Nerdio and inforcer, which both make multi-tenant tooling for Intune, the initiative is aimed at boosting Microsoft 365 use among SMBs by boosting Intune use among MSPs.

“They need to drive more of the higher [M365] SKUs into SMB, Copilot, etc.,” Ominsky says. “The only way they’re going to do it is by working with MSPs, because almost every SMB is buying licensing through their MSP.”

NerdioCon seemed like an excellent place to see if #IntuneForMSPs is producing results eight months since its introduction. Ominsky says it is.

“We’ve seen some really, really good uptake,” he reports. “Every single month, literally every single month, we are breaking records in the number of MSPs that are coming into using Nerdio to manage Intune and the rest of the Microsoft 365 stack.”

It probably says something about the results Microsoft is seeing from the program that it now includes AvePoint, CyberDrain (makers of the CIPP Microsoft cloud management app), and SoftwareCentral (which makes a Microsoft cloud management tool called Tenant Manager). The initiative could see further momentum starting in July, moreover, when the Intune Suite officially becomes part of the Microsoft 365 E3 and E5 SKUs.

“That’s a game changer,” said Lior Bela, Microsoft’s Intune business director, during a NerdioCon speaking appearance. “Why? Because if you already own E3 and E5, you don’t have to pay a dime more for the Intune Suite. Those capabilities are coming to your tenant.” Which means you’ll have access to advanced analytics, remote connectivity, privilege management, and other features that cost extra before.

All very good, but what I really wanted an update on is the degree to which the newfound fire for MSPs within Microsoft discussed in my first #IntuneForMSPs story is still burning.

According to Ominsky, it is. People including the VP atop the Intune product group continue to pay close attention to the program and its MSP members. “There is really senior buy-in and they’re engaging with us and engaging with our partners as part of this program,” he says. “It does feel like a genuine step change with the way that Microsoft’s engaging.”

Landes agrees. Back when he and Vladimirskiy co-founded Nerdio in 2018, he says, few people at Microsoft knew what an MSP is or does. “Now more and more and more, there are people at Microsoft who believe in the MSP community and who are excited about it.”

Nerdio partners are experiencing some of that excitement too, according to Ominsky. “We’re very, very obviously closely aligned with Microsoft, but we’re hearing from MSPs who never had the ear of Microsoft before that they’re feeling some of that love,” he says.

More specifically, at least some of them are getting asked for Intune roadmap suggestions by Microsoft, and seeing some of their suggestions become part of the product.

“It’s a really important thing for MSPs to be able to engage with Microsoft, because it’s been probably a decade of feeling like they just can’t speak to anyone,” Ominsky says.

It’ll be interesting to see if they still have Microsoft’s ear in September, when #IntuneForMSPs should be celebrating its first birthday. The company has gone hot and cold on MSPs through the years, after all. Ominsky, at any rate, thinks the attention Nerdio and its partners have seen to date is only the start of what’s likely to be a long, slow process at Microsoft of figuring out what makes MSPs tick and then acting on what it learns.

“It takes a little while for them to make changes,” he says. “They’re a very, very big company.”

Also worth noting

• Congrats to everyone on the newly named 2026-2027 GTIA board of directors.

• Atera now guarantees users that its autonomous IT agent will independently resolve 50% of Tier 1 and Tier 2 tickets within the first 90 days of onboarding.

• The latest release of CloudBolt CMP includes MCP connectivity, contextual user experiences, and support for public cloud, private cloud, and emerging neocloud platforms.

• Huntress, which signed its first distribution agreement last October, has signed four more with Ingram Micro, Vertosoft, Liquid PC, and QBS Software.

• SMB security software from Guardz is now available on the Syncro Marketplace.

• CrowdStrike’s Amanda Adams, last seen here on Channelholic, has been promoted to senior vice president of global alliances.

• More news from CrowdStrike: Jet, its new mobile app for partners, is designed to bring deal origination, closure, rewards, and enablement into a single, real-time experience.

• AgentSkope, newly launched by Netskope, is an agentic AI-powered data loss prevention analysis and insider threat triage tool.

• Agents behave a lot less predictably than humans, yet 66% of organizations grant them equal or greater system access anyway, according to JumpCloud.

• 89% of IT leaders struggle to manage expanding identity footprints as AI adoption accelerates, according to new research from Keeper Security.

• Fleet Manager, from Object First, is designed to simplify management of distributed backup storage environments.

• Insurer/MDR vendor Coalition is now Allianz’s exclusive global partner for cyber insurance across all commercial segments.

• Frank Koelmel is the new Business Solutions Group CRO at Bitdefender.

• Chung Ip is the new CFO and Lisa O’Reilly is the new VP of Marketing at ThreatDown.

• Jeremy Powell is the new CISO and Ben Cody is the new SVP of product management at Sumo Logic.

• MSPAlliance’s new Cyber Verify service aims to simplify compliance reporting processes.

Joe Smolarski, who’s been CEO of security vendor WatchGuard since last November, regrets nothing about the years he spent at Kaseya before that. On the other hand, it sure does sound like he was ready for a change.

“After nearly a decade at Kaseya as president and COO and running the majority of that company, WatchGuard’s been a breath of fresh air,” he says. “I’m six months in and I’ve had zero escalations hit my plate in terms of product quality. Zero. I used to get them every six minutes at my former company.” Partner complaints have been pretty rare too so far.

“That’s not a luxury I had in the past,” Smolarski says. “I was constantly battling friction, friction, friction.”

The new battle he’s fighting is overcoming outdated perceptions of WatchGuard among current and potential partners more familiar with the company’s name than with its multi-year expansion beyond its roots in network security.

“We have a challenge of making sure that the rising MSP community knows who WatchGuard is and knows that we’re not just the company from 30 years ago with a firewall, that we have a complete cybersecurity platform,” Smolarski says.

And not a new one either. WatchGuard has been assembling the pieces of its platform since at least 2017 through acquisitions of companies like MFA vendor Datablink, DNS security vendor Percipient Networks, endpoint protection vendor Panda Security, and MDR vendor ActZero, not to mention cloud application security vendor Perimeters.io earlier this week.

“Our firewalls protect almost 900,000 networks in the world, which is amazing,” Smolarski (pictured) says, “but we’re also protecting 10 million endpoints with our EDR endpoint solution. We also have an agentic SOC that is growing 300% year over year that’s just doing phenomenal things with a six-minute response time.”

Now the company just needs to make MSPs aware of all that, he continues, along with the differentiating attributes that he believes set WatchGuard apart in a field crowded with security platforms. Those, in his view, include the vendor’s long, stable track record. There are younger, flashier brands in the industry, Smolarski concedes without naming names, but many are burning through venture capital and others will be swallowed up eventually by private equity or a bigger peer.

“We’ve been around for 30 years and we’ll be around for another 30 years,” he declares, adding that the company has sold exclusively through partners across that entire span.

“We’re 100% dedicated to the MSP space,” Smolarski says, drawing a contrast between WatchGuard and competitors that also sell direct to big businesses. “They start to prioritize enterprise over the MSPs, and MSPs will always lose.”

WatchGuard solutions are priced for SMBs rather than enterprise buyers too, he adds, noting that the company introduced an affordably priced endpoint security offering just before he stepped into his new job and a new endpoint detection and response licensing model aimed at further lowering cost barriers last month.

“We’re affordable,” Smolarski says. “Sometimes people are afraid to say that, but I think in the MSP space that remains a critical component.” Mostly because high prices can discourage small businesses from buying products they need to stay safe but won’t stop them from blaming their MSP when the inevitable happens.

“If you’re an MSP and your end clients are rejecting your platinum packages and the necessary level of cybersecurity, whether you like it or not, they’re still going to hold you accountable if an event occurs,” Smolarski notes.

Last but not least and in contrast with companies like Kaseya, Smolarski adds, WatchGuard’s platform is dedicated solely to security.

“I don’t believe that you can be best in class in every single category under the sun,” he says. “You’ve got to choose what you are, a jack of all trades and a master of none or an expert in one particular area.”

There is one thing WatchGuard and Kaseya have in common, though: a newly introduced AI platform. WatchGuard’s, unveiled Wednesday and inspired by the dominant color in the company’s brand, is called Rai, as in red AI.

“We’re famous for red,” says Smolarski, noting that RAI isn’t so much new tech as a new name for existing tech that no one knew was there.

“We have great AI embedded in our platform, but it’s not visible,” Smolarski says. “People don’t see it.” Launching Rai is designed to get WatchGuard credit for functionality it’s been embedding across its portfolio for years.

And it matters that Rai is embedded too, in Smolarski’s view. “It’s built into the core of our SOC, it’s built into the core of our endpoint solution, and we have it throughout the firewall,” he says. “You could always bolt something on and get some value-add there, but it’s different when it’s built into the core.”

If that bit about built-in being superior to bolted-on sounds familiar, it’s because Kaseya CEO Rania Succar said the same thing about that company’s embedded AI platform, Kaseya Intelligence, during the vendor’s recent Kaseya Connect event, shortly before telling Channelholic that leaning harder into security solutions is a core part of her near-term growth strategy. Are Smolarski and his former boss on a collision course for security mind and market share?

Not as far as he’s concerned, anyway.

“It’s an area where there’s plenty for all of us to get,” Smolarski says of the security market. “It just depends on what you’re trying to accomplish.”

I interview a lot of security vendors. Trust me when I tell you that even if their target market is the smallest S in SMB they never call their functionality anything less than enterprise-grade.

Unless they’re CyberFOX, a privileged access management, password management, and DNS security specialist that from the very beginning has built its strategy around offering MSPs and their SMB clients 80% of what a complex product from a name-brand vendor would give them at 90% of the price.

CyberFOX calls that undeniably contrarian formula the 80-90 rule, and it appears to be working. In the few short years since its founding early this decade, the company has grown ARR 20x and amassed over 4,000 customers, a track record strong enough to have won it a “nine-figure growth investment” led by Level Equity three months ago.

Now it’s putting some of that capital to work via a new effort aimed at expanding beyond SMBs and MSPs to a bigger class of customer and wider range of partners. On the customer side, that means mid-market enterprises big enough to handle IT without outsourced help. On the partner side, it means solution providers, distributors, and hyperscalers in addition to MSPs.

Osman Haque, who became CyberFOX’s first full-time channel chief in January, is responsible for bringing much of that vision to life. And yes, he says, it involves selling direct to end users, though not at the expense of current or future partners.

“Tie goes to the runner at any point with our MSPs,” says Haque (pictured), a former ConnectWise executive. “There’ll be no stepping on toes.”

To support what will be a more diverse channel going forward, Haque has spent much of his early months on the job constructing CyberFOX’s first formalized partner program. Like CyberFOX’s software, it’s inspired by a K.I.S.S. philosophy.

“It’s the simplest partner program possible,” Haque says. “We’re not even doing tiers.”

It won’t be huge either. “We’re not looking for hundreds of partners,” Haque says. “We’re looking for two or three really good ones for every channel that we have.”

MSPs, meanwhile, can potentially get in on some of those direct sales to larger buyers. “I am setting up the structure so that resell is available as long as they have the skillset and the ability to sell it the right way,” Haque says. “They have to add some level of value, whether it’s from a consultative perspective or tangential technologies that fit well.”

And they have to do it in a way true to the 80-90 rule, which Haque insists isn’t going anywhere despite everything else changing at CyberFOX these days.

“We’re not deviating from that core,” he says.

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Patience has long been Pia’s hallmark. One of the earliest names in service desk automation software for MSPs, the vendor has carefully held autonomous ticket closing powers in reserve to avoid pushing MSPs outside their gradually expanding comfort zone.

Too often in AI, explains David Schwartz, the company’s CEO, “it feels like you just set out to go climb to the peak of Everest and the reality is you don’t have a map, you don’t have a compass, you don’t have your stops along the way. It’s just get to the top. We’ve been very purposeful in saying that doesn’t work.”

One step at a time does, he continues. The company’s latest step, announced during pre-day activities at Kaseya’s recent Connect event, aims to make resolving a service issue less painful for both the client experiencing it and the MSP addressing it. Called Pia Chat, the new feature lets end users report a problem via natural language chat from directly within Microsoft Teams.

“You don’t have to leave that tool that you’re used to using every day,” Schwartz says.

Neither do help desk technicians on the receiving end of a ticket, who can close the ticket based on detailed contextual information collected automatically by Pia from inside their PSA system—if they need to touch the ticket at all. The system can resolve simple issues like password resets on its own, sometimes within seconds.

“Most Level 1 requests can absolutely be done without any human in the loop,” Schwartz (pictured) says.

That step forward in Pia’s steady march toward fully automated ticket resolution comes in response to the growing acceptance of autonomous AI among MSPs signaled, among other things, by their increased use of the company’s AI AutoStart feature.

“It does a lot of the troubleshooting on endpoints and other work that a tech would normally have to do,” Schwartz says. “We are now seeing more partners leverage it.”

That increased willingness to let AI do unsupervised help desk work is new since the last time Schwartz spoke with Channelholic at Kaseya’s DattoCon event last October. “There’s been a noticeable change,” he says. “There’s an understanding that we want to move into this agentic world, but we want to know that it’s guardrailed.”

Pia is similarly cautious about autonomous AI. “If it’s used right, it’s a force multiplier. If it’s used wrong, it’s just fast-tracking to a bad result,” Schwartz says.

Pia Chat, he continues, is an example of AI done right, as well as an illustration of Pia’s belief that “practical AI” is better than AI features that look impressive but have little impact on MSP workflows.

“It’s not AI for the sake of being AI,” Schwartz says of Chat. It’s AI designed to provide a specific outcome with a measurable impact on both technician productivity and end user satisfaction. More such features that reach beyond the basic blocking-and-tackling of closing tickets to help MSPs forge stronger client relationships are currently on the roadmap.

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Like Pia, covered here recently, CloudCapsule strives to make a practical impact on MSP productivity. Unlike Pia, it strives to do so by eliminating the need for tickets rather than helping technicians close them more quickly.

“We started CloudCapsule really to solve this problem of preventing breaches before they happen,” says Nick Ross, the company’s CEO.

That was in 2024, shortly after Ross (pictured above) had exited senior leadership roles with multiple MSPs following a five-plus year stint in various capacities at Pax8. “I was spending about four to six hours doing manual security assessments and producing reports,” he recalls. “It was a very tedious process and not really something you could do in a non-linear fashion.”

With that experience in mind, Ross and Michael Dehmlow, previously Pax8’s CTO and then COO, decided to create a solution that would radically accelerate an otherwise time-consuming process.

“We’re in the cloud security posture management space, which is really young for SMBs and MSPs,” Ross says. Wiz, the security vendor Google acquired for $32 billion in a deal that closed earlier this year, is its inspiration.

“They did this for enterprise and did this really well,” Ross says. “Wiz is kind of who we want to be when we grow up, but for SMB and for MSP.”

Called Analyze, the company’s first product performs heavily automated security assessments of Microsoft 365 tenants. That was a natural fit for Ross, who in his spare time is a Microsoft MVP and host of T-Minus365, a YouTube series and accompanying blog with some 33,000 subscribers.

“We collect over 200 data points across the Microsoft 365 ecosystem, and we map those to a variety of compliance frameworks like CIS and NIST automatically,” Ross says. “The time to value is about 60 seconds.”

The system fills a service gap for many users as well. “Most times we find that the MSP is either not doing this today as part of their security practice or not actively going and running assessments on a regular basis,” Ross says. “It’s very ad hoc.”

And usually inefficient as well, he adds. “We’re saving them a ton of time on that effort that you would go in and spend to perform this manually.”

Reporting functionality in the system then lets users present assessment results in terms customers will understand. “It’s client facing out of the box so you don’t have to translate the lexicon of Microsoft speak or security speak,” Ross says.

In a brief time, he continues, the solution has attracted over 300 partners in more than 42 countries. The company’s second product, called Manage and launched on Tuesday, is designed to help those partners implement needed changes uncovered during assessments.

“The biggest piece of feedback since we’ve been in market is, ‘I see all these changes now, I have great context into what’s going wrong, but now I want to be able to scale fixing this.’”

Together, Analyze and Manage let them do so in a single workflow encompassing assessment, remediation, proof of completion, and audit reporting.

“We do the scan, we show you what’s wrong in red, you have the button to click it and make it green, and you get an immediate feedback loop,” Ross says. “It’s really that basic.”

Manage also monitors a scanned environment continuously after remediation is complete. “If it ever drifts outside of compliance again or somebody tampers with it maliciously or accidentally, we’ll show you that too,” Ross says.

Analyze currently sells for a flat $250 per month with unlimited scans. “You can add all of your tenants,” Ross says. Manage covers an initial 250 managed users for another $250 a month. Additional users cost $1 each from there.

According to Ross, real-time alert logging in PSA systems is on the roadmap for future functionality updates, along with expansion beyond the Microsoft ecosystem.

“Ideally, in timelines like the end of this year, we’ll be extending ourselves into other cloud-based environments like Google, but also more of the MSP tool stack that they’re typically using for security products, like SentinelOne for EDR or a third-party email security tool,” he says.

Raffael Marty has bad news for a lot of companies in our industry now: The thing you seem to think will best set you up to be among the software world’s next great success stories won’t.

“The winners are less likely to be those with the loudest AI messaging and more likely to be those with the strongest combination of data, workflow ownership, and commercial leverage,” says Marty, currently an operating advisor to security startups and formerly head of ConnectWise’s security product unit, in a recent blog post.

Or to state the matter sequentially, more data yields better workflows yields more customers, partners, and profits, along with the kind of defensible, durable commercial leverage software companies crave at a time when AI-native startups and frontier model makers both pose existential threats.

“This is not just a consolidation story. It is a data gravity story,” Marty writes, and it compounds upon itself.

“The vendor that sees more telemetry, sits in more workflows, and becomes harder to dislodge can improve models faster, distribute new capabilities faster, and defend retention more effectively.”

Marty’s describing the flywheel effect Kevin Lancaster of BetterTracker discussed with me earlier this year. Lancaster was talking about MSPs, but the core lesson applies to legacy software companies too: everything good these days flows downstream from data.

Rania Succar (pictured) knows it too, which explains what caught her eye when she became Kaseya’s CEO last June.

“The first thing I saw was the most extensive network of data about small and mid-market businesses when it came to IT and security,” she said last week during a keynote presentation at Kaseya’s 2026 Connect conference in Las Vegas. “There is not a network of data like this anywhere else.”

Hard to verify, but she may be right. Kaseya has 3 billion gigabytes of backup data on its servers today, plus all of the facts, figures, and notes associated with 1 billion help desk tickets. It’s currently supplementing all that with data from 44.4 billion backup jobs, 1.2 billion patch applications, and 16.9 billion security events every year too.

If data, as we’re all fond of saying, is AI gold, that data repository is Kaseya’s answer to the N.Y. Fed basement.

“This is the backbone of intelligence,” Succar said as she introduced the world to Kaseya Intelligence, the company’s new cross-product, cross-workload agentic AI engine. “Only when you have data this rich can you let the system be autonomous. Only then can you trust it to get to the right decision.”

Hence the energy Succar, per an interview last August, devoted early in her time on the job to consolidating and cleaning all that data. But AI’s not the only way data is useful to Kaseya, and arguably not even the way it’s most useful. That mass of data is an immense potential source of gravitational magnetism for both MSPs and other software companies, especially other AI software companies.

Actually, scratch the potential part of that statement. During an interview with Channelholic at Connect, Succar said she met last year with the founder of an unnamed AI automation startup akin to the ones I’ve been profiling in recent months.

“He said, ‘can you please open up IT Glue for us? We need it.’” Other vendors have made similar requests, she adds.

“They’re constantly knocking down our doors saying, ‘can you open the API?’”

Which she has to an initial degree, per a little noticed press release published early in February offering a progress report on the unexpected pledge Succar made during a keynote at last fall’s DattoCon event to turn Kaseya into an “API-first” company.

That promise grabbed my attention at the time but didn’t come fully into strategic focus until now. Indeed, despite what the headlines told you, I’d argue that the most significant announcement out of Kaseya Connect last week wasn’t the launch of Kaseya Intelligence so much as the forthcoming launch in July of a new family of unified APIs. According to Succar, they’ll first pay off by helping Kaseya integrate the many solutions in its product portfolio more deeply.

“Historically at Kaseya, we’ve been loosely connected as a platform, but with these APIs we’ll be fully connected,” she says. That’s only benefit number one, though, she adds.

“The next benefit is partners can then tap into the API, in and out, to get their own use cases, however they want to use it,” Succar says. “We’re an open platform and we want our customers to be able to use it whatever way they need to.”

Now, theoretically, of course, that’s a risky thing to want because it means companies Kaseya competes with could soon be helping themselves to all that gold in the company’s basement. Then again, that cuts two ways, doesn’t it? What’s to stop Kaseya from enriching its own data with data from its API partners?

Nothing apparently, because it’s already happening, per a keynote comment about the new API family from Kaseya CTO Pratik Wadher. “It brings together data from 60 different data sources across the ecosystem outside Kaseya, third-party data. It puts it in one place. It starts to analyze it, look for anomalies, and then starts to surface it very quickly.”

And that’s just the beginning. All those vendors Kaseya foresees using its system of record to power their systems of action will also be making Kaseya’s data mass more massive, more valuable, and more gravitationally irresistible in the process.

“We expect more consolidation onto the Kaseya platform,” says Succar of the API initiative. “We’ll get more share of wallet.”

They’ll also, per Marty, get harder to dislodge. Yes, competitors will ship copycat versions of Kaseya’s new ticket triage agent, noted Paul Burke, who runs the company’s agentic “digital workforce” platform, during a main stage appearance. But they’ll be starting from zero.

“Your Kaseya digital workforce will have months of proprietary intelligence specific to you and impossible to replicate,” Burke said. “This is not a feature. This is a moat that grows daily.”

It’s also why we’ll win, he predicted. Succar agrees, specifically with respect to companies like the AI-native startup that pleaded with her for IT Glue access last year.

“Most of them will not succeed,” she says. “They have nothing. They have no moat. They have nothing unique.”

Built in, not bolted on

You’ll be unsurprised to learn that David Schwartz, CEO of AI-for-MSPs vendor Pia, begs to differ. He can think of at least two things vendors like his have to offer that Kaseya doesn’t, starting with the kind of experience and know-how that come from focusing solely on AI in managed services for an extended period.

“It’s not a new product,” Schwartz (pictured left) says of Pia’s solution. “It’s been designed and built over the course of six or seven years at this point.”

It’s also platform-agnostic and hence free from vendor lock-in, adds Pia CRO Nic Ferraro (pictured right). “MSPs don’t want to get stuck in an ecosystem,” he says.

There’s a benefit to getting your service delivery automation software from the same company you buy the rest of your service delivery stack from, though, Succar argues, which is why the second thing that grabbed her attention upon becoming CEO after the data was Kaseya’s end-to-end suite of MSP line-of-business offerings. Data only makes powerful workflows possible, she argues. “To complete the workflow, you need the entire platform, and we have that.”

The AI-native startups Kaseya competes with don’t, Succar continues, which puts them at a long-term disadvantage.

“AI is going to move from being bolted onto platforms to being built in, and that’s where we’ll see its profound power,” she told her Connect keynote audience. “When it’s bolted on, AI is reacting to problems. When it’s built in, it predicts them. It fixes them. It eventually prevents them. When it’s bolted on, it’s like you have a generic consultant automating your workflows. When it’s built in, you have specialized models that deeply understand the domain and have the data to get you secure outcomes.”

Companies like Pia aren’t Kaseya’s only rivals in AI, of course. There are also companies like ConnectWise, which would probably tell you that its platform combines a data lake as deep and broad as Kaseya’s with Pia’s AI-specific depth, thanks to its acquisition earlier this year of AI-native startup zofiQ.

Succar, for her part, says not buying a company like zofiQ gives Kaseya an edge. “We looked at a ton of these AI startups that were building automation engines,” she says. “We realized that the easy thing to do would be to go buy a partner, but it wouldn’t get you the scale and the impact that we could get if we built it this way.”

Meaning entirely in house using “the very best technologists” in the industry, as in the same kind of top-tier engineers Shield Technology Partners, Titan, and Treeline have all hired to build their cutting-edge AI platforms. Kaseya’s been going head-to-head with those companies for AI talent, in fact, since it added a Silicon Valley R&D office in San Jose earlier this year.

“We opened the office just two months ago,” Succar said during her Connect keynote. “Two months later, we’re out of space.”

And presumably accumulating a giant new payroll burden too given how expensive Silicon Valley AI researchers are. Succar’s happy to cover the tab.

“The people we’ve recruited are extraordinary and we couldn’t get them unless we had a presence there,” she says, noting that the company will soon open a similar facility in Toronto and others in “various parts of the world” where extraordinary AI coders live. It’s the kind of investment few vendors can afford to make, Succar asserts.

“That’s what’s going to set us apart.”

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Four final notes from Kaseya Connect

1. We’ve not entered the Kaseya Twilight Zone, but it sure feels that way sometimes. This will be obvious to fellow long-time Kaseya watchers, but hearing the company’s CEO tout its “open platform” and its CTO speak of sharing data with “the ecosystem” is a slightly head-spinning experience.

Traditionally, it’s been ConnectWise and N-able that lead with openness and ecosystem. Kaseya, by contrast, has been eager to sell you everything you need itself, and supported API connections to its software, per multiple comments through the years from former CEO Fred Voccola, because it would be “suicide” for a company like Kaseya not to given how many MSPs prefer customized, multi-vendor tool stacks. That Succar has done a 180 on openness and ecosystem tells you exactly how large data gravity looms in the strategy she’s pursuing.

2. Kaseya Intelligence is Kaseya’s Intel Inside. It’s a good rule of thumb in my experience to assume that wherever tech goes, it will find Omdia’s Jay McBain waiting for it with a grin on his face.

Kaseya’s AI strategy is no exception. McBain predicted that AI would ultimately become something software makers build into solutions rather than sell as a solution unto itself during a conversation with me some two and a half years ago in connection with this article.

“It’s going to be a feature, not a product,” he said.

And that’s more or less exactly how Kaseya is positioning Kaseya Intelligence. “This is a platform, not a product,” said Burke during his keynote appearance at Connect, meaning you won’t so much buy it as get it as a built-in part of more and more Kaseya solutions.

That said, Kaseya wants you to know it’s there, which is why we’ll increasingly see Kaseya Intelligence show up as a sort of sub-brand of the company’s product brands.

“We’d love it to ultimately be ‘powered by Kaseya Intelligence’ as the way that the brand recognizes value,” Succar says. “When it’s got Kaseya Intelligence inside, you know that this is exceptionally accurate and reliable and non-fragile automation that works.”

3. Cyber resilience is Succar’s next big play. Accurate, reliable, non-fragile automation is especially useful in situations that require a system of speed rather than action, like security. Kaseya intends to capitalize on that fact.

“As part of our Kaseya platform strategy, we’ve built a fabric that connects every Kaseya product, allowing us to weave all of our solutions together,” said Dave Baggett (pictured), formerly CEO of INKY, the email security vendor Kaseya bought last October, and now the SVP in charge of Kaseya’s security suite, during a product keynote appearance last week. “This means that from now on each security component will share real-time event data with other components, connecting the dots in a transformative way.”

Look for that transformative power to be Succar’s next strategic move now that the launch of Kaseya Intelligence is behind her.

“We’ll increasingly become a security player,” she told me last week. “We’re leaning heavily towards cyber resilience and cybersecurity, and that will be our edge over time, and that also will create that valuation as we go forward.”

4. MCP and AI-as-a-service still to come? Two topics that came up during my first conversation with Succar last August failed to come up during Connect last week. One (much to the disappointment of this MSP, who I ran into at Connect) is the MCP support we discussed. I didn’t get a chance to ask her about it this time around, but given that she’s into APIs and data gravity, one assumes letting people interface with Kaseya data via their favorite chatbot remains on the roadmap.

The other topic is Kaseya’s eventual role in helping MSPs move from deploying AI internally to selling AI solutions to their customers. This one I did bring up, and yes, it’s still in the cards.

MSPs want to provide AI services to end users, she said. “They’re experimenting, but they’ve yet to have significant breakthrough success. They need help with that. It’s our ambition to help them.”

But only after the company completes two higher priorities. “Right now, our number one focus is to get to autonomous IT and security,” Succar says.

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As long as we’re talking about AI and security…

One of the nice things about going to conferences is that they give you a chance to speak face-to-face with other conference-goers. My co-host and I took advantage of one such chance at Kaseya Connect last week by interviewing David Primor, CEO of vCISO software maker Cynomi, on MSP Chat, our podcast. If, like me, you’re curious about how autonomous vCISO services will eventually get with help from AI, the interview in our latest episode is a great place to start.

We need a service desk automation benchmark, people

If you’re an MSP eager to capitalize on the productivity-boosting power of AI automation (and if you’re not, you might want to get eager to avoid falling way behind your peers), there have never been more options for realizing that goal. Which is a blessing, of course, but also a curse, because the people responsible for those options at companies ranging from Kaseya and ConnectWise to Pia and Thread and way, way beyond all say their AI automation is the best.

And they can’t all be right, so how do you make a choice? Build a lab and test them all out in an endless series of in-house bake-offs? Flip a coin and hope for the best? This is something that’s been on my mind for months, and the launch of Kaseya Intelligence is as good a reason as any to bring it up here.

I think we need a benchmark.

Now, I say this knowing that AI benchmarks are flawed. They can be gamed for one thing, they create perverse incentives to “write to the test” rather than build what people need, and they’re not always easy for laypeople to understand fully.

On the other hand, assuming it’s designed and maintained by a neutral third party, a benchmark is objective, and it gives MSPs otherwise stuck with hunches and guesswork something to go by when evaluating solutions. Having one specifically for service desk automation would, I think, be helpful.

It’s also something I truly, deeply don’t know how to create. So I’m just putting this out there in the hopes that someone who agrees that a service desk AI benchmark would do more good than harm will build one.

I promise to write all about it here in Channelholic if you do. Writing I mostly know how to do.

Over on the Business of Tech

Host Dave Sobel does the math on the AI spending black hole I wrote about recently:

Imagine you’ve got a 120-user client at $150 per user. That’s $18,000 a month. Now the client rolls out agents and automation and they “need fewer seats.” They drop to 85 users. Your seat-based revenue just fell to $12,750 — same environment, fewer licenses.

But your AI costs don’t shrink with seat count. They move with activity. So now you’ve got usage fees, API calls, agent runs, and premium tiers that can easily turn into $1,500, $3,000, $5,000 a month in consumption — and it spikes when projects spike.

That’s the squeeze: the old revenue proxy shrinks, while the new cost line becomes variable and harder to predict.

More here.

Also worth noting

• Remember the 40% quarter-over-quarter increases in paid monthly active users that Google’s Gemini Enterprise has been enjoying, per my last post? The streak continues.

• Cynet has enhanced its CyAI engine to continuously improve detection and response capabilities via self-learning.

• 89% of SMBs employ at least one victim of credential compromise at any given time, according to Guardz.

• Breach Secure Now’s new AI Risk to Adoption program aims to help MSPs guide SMB customers from unmanaged AI use toward secure, scalable adoption.

• The newest version of MSP360 Backup features extended backup immutability support across major cloud storage providers.

• Agentic email security vendor Sublime Security has launched a new channel partner program for MSPs and resellers.

• JumpCloud’s new Agentic IAM solution is designed to extend identity and access management controls to AI agents, models, and workflows.

• Joining OpenAI’s Trusted Access for Cyber TAC initiative has given Cato Networks access to advanced models like GPT‑5.4‑Cyber.

• Keeper Security has introduced Verify Mode and new browser controls to protect users from phishing and credential misuse.

• Keeper Security has also released Agent Kit to secure AI coding workflows by protecting secrets and credentials used by AI agents.

• A new connector has extended real-time scam detection and threat intelligence from Malwarebytes to Claude AI conversations.

• Bishop Fox has launched AIMap, a platform designed to help organizations identify and manage AI-related security risks.

• GMO GlobalSign has launched TLS Connect, a solution designed to automate certificate lifecycle management for SMBs.

• Pax8 has partnered globally with NinjaOne to expand unified IT operations and cybersecurity offerings for MSPs.

• LogicMonitor says its latest release turns its AIOps platform into an “AI-first platform for Autonomous IT”.

• 95% of MSPs agree automation is no longer optional, according to new research from Rewst. Only 4% consider themselves fully mature at it.

• AvePoint has added new agentic AI and multicloud resilience capabilities to its Confidence Platform in a bid to enhance security, governance, and operational continuity.

• It takes a gutsy company to launch a brand new managed services tool suite right now, especially in the middle of a Kaseya conference. I had a chance to meet one such company, called IgnitHQ, at the show and will be writing more soon.

• 10ZiG and Nerdio have expanded their partnership to reduce total cost of ownership and simplify deployment of Azure Virtual Desktop and Windows 365 environments. Bound to come up at NerdioCon, the conference I’m flying to right now as I write this.

• GTIA says channel partners are hedging bets amid uncertain Q1 economic conditions, balancing cautious spending with growth investments.

• MSP-as-a-Service, a new venture from Summit Holdings you read about here recently, now has a strategic go-to-market alliance with Kaseya.

• Kamiwaza AI has launched Kamiwaza 1.0, a secure AI orchestration platform tailored for regulated industries.

If you’re an MSP eager to capitalize on the productivity-boosting power of AI automation (and if you’re not, you might want to get eager to avoid falling way behind your peers), there have never been more options for realizing that goal. Which is a blessing, of course, but also a curse, because the people responsible for those options at companies ranging from Kaseya and ConnectWise to Pia and Thread and way, way beyond all say their AI automation is the best.

And they can’t all be right, so how do you make a choice? Build a lab and test them all out in an endless series of in-house bake-offs? Flip a coin and hope for the best? This is something that’s been on my mind for months, and the launch of Kaseya Intelligence is as good a reason as any to bring it up here.

I think we need a benchmark.

Now, I say this knowing that AI benchmarks are flawed. They can be gamed for one thing, they create perverse incentives to “write to the test” rather than build what people need, and they’re not always easy for laypeople to understand fully.

On the other hand, assuming it’s designed and maintained by a neutral third party, a benchmark is objective, and it gives MSPs otherwise stuck with hunches and guesswork something to go by when evaluating solutions. Having one specifically for service desk automation would, I think, be helpful.

It’s also something I truly, deeply don’t know how to create. So I’m just putting this out there in the hopes that someone who agrees that a service desk AI benchmark would do more good than harm will build one.

I promise to write all about it here in Channelholic if you do. Writing I mostly know how to do.

Some numbers are big even for a company the size of Google.

Like 1 trillion, as in the 330 businesses Google says consumed over 1 trillion LLM tokens each over the past 12 months, or the 35 businesses that gobbled up 10 trillion or more over that span.

Or how about 16 billion, which is the average volume of tokens Google currently serves up per minute via direct API use, a figure that has soared by 60% in the last quarter alone.

And then there’s 750 million. Let’s put a pin in that one and return to it after discussing a much smaller figure, 32,000, which is the approximate number of attendees at last week’s Google Cloud Next conference in Las Vegas. Google doesn’t know for sure how many were SMBs, except that it was in the thousands and significantly larger than in years past.

“It’s just really nice to have so many small to medium businesses here at Next,” says Sharon Prosser (pictured), Google’s vice president of Google Cloud SMB sales and scaled acquisition.

It’s also no coincidence. According to Prosser, Google went out of its way to grow SMB attendance. “We built a 13-session track for SMBs so that they felt like they could have a tailored experience,” she says, and devoted far more time than usual to showcasing SMB growth opportunities and success stories.

“We’re trying to give them some of the limelight,” Prosser explains.

For a very good reason. Though it’s outgrowing them both at the moment, Google trails AWS and Microsoft by double digits in cloud infrastructure market share, according to the latest figures from Omdia. And while its Workspace apps have 3 billion users globally, just 11 million of them are paying customers. Microsoft, by contrast, reported over 450 million paid Microsoft 365 seats in its most recent quarterly financials, up 6% year over year thanks primarily to strong adoption of its SMB and frontline worker offerings.

That’s cloud, however, a rapidly growing yet relatively mature market. AI is comparatively in its infancy and agentic AI’s so young that even the forward-looking folks in venture capital only really climbed on board in a big way last year, as the chart at the bottom of this page makes clear.

“Three quarters ago, companies were talking about how to use GenAI to improve a process,” says Phil Larson, managing director of the Google Cloud Partner Network. “Now it’s increasingly, ‘how can I rethink my business and rebuild it in an agentic way so that these processes are running independently?’” They’re looking to IT providers for answers, he continues, “so the partners are thinking through how their business models need to change.”

All of which tells Google that businesses and their partners are very much up for grabs in AI right now, especially in agentic AI and especially at the smaller end of the spectrum.

“If you think about enterprise organizations, they’ve been at this for several years,” Prosser observes. SMBs are just getting started. Indeed, though 76% of small businesses are currently using AI, according to Goldman Sachs, just 14% have fully embedded it in core operations and 73% want greater access to training and implementation assistance.

“This is going to be the next big frontier for AI adoption,” says Prosser of SMBs, adding that for Google it already is. “We’ve seen this hockey stick adoption of Google Cloud AI tools that we’re trying to keep up with.”

I know many people (the leadership teams at Nerdio and at Syncro come immediately to mind) who will scoff at the thought, but Google thinks it has an extremely legitimate shot at turning that early momentum into enduring SMB leadership.

Hear them out. They have a case.

Comprehensive and open

It begins with the company’s deep, and deeply integrated, AI stack. “No other hyperscaler can bring the hardware all the way up to the AI tooling to the customer base, and this is across small businesses as well as enterprise,” Prosser says.

Brooks Borcherding agrees. “It’s the most comprehensive toolkit for us as a services partner,” says Borcherding (pictured), who was once CRO at Datto and is now CEO of Google partner Pythian. “They have everything from infrastructure all the way up to the chat agents itself.”

They also own the infrastructure part along with the custom processor and server architecture it runs on, and have adequate supply—now, when the AI opportunity is at its ripest—not to mention the free cash flow to build more. Anthropic, by contrast, is so compute constrained that it’s selling equity to Google in exchange for chips it badly needs and doesn’t make, while OpenAI needs obscenely large funding rounds to rent capacity from companies that haven’t yet built a lot of it. Neither company is even close to profitable.

Unlike Microsoft, meanwhile, which relies chiefly on models from OpenAI and Anthropic, Google also owns Gemini, one of the industry’s most advanced LLMs. That’s a potentially big advantage for reasons the folks at Kaseya have been talking about for years: native integration eats external API integration for lunch.

“Google owns from top to bottom and can make sure each of the layers is actually working well together,” says John Campbell, SVP of Google solution sales at services giant Insight.

That includes the productivity layer, Workspace, which has come with embedded Gemini for over a year and gained even more AI smarts last week. Insight clients are switching from alternative productivity suites (presumably including M365) to Workspace as a result, Campbell says. Businesses want to use Gemini without turning sensitive data into training fodder, he notes. “The easiest way to do that is typically to procure Workspace.”

Workspace is often the gateway drug to the rest of Google’s AI offerings, moreover. “From there, they’re going into tools within Gemini Enterprise,” says Prosser, citing Agent Designer, a no-code, drag-and-drop agent writing platform launched last year as an example.

“I can’t emphasize enough the day one value, the ease of use,” she says. “Those have to be first order principles when we’re building products and thinking about small to medium businesses,” including products like the newly introduced and far more expansive Gemini Enterprise Agent Platform.

Solutions like that are paying off, apparently, and not just with SMBs. According to Google Cloud CEO Thomas Kurian in a recent interview with Ben Thompson, Gemini Enterprise revenue has grown 40% sequentially quarter-over-quarter. Google is using Gemini behind the scenes to make its AI software more secure as well, he adds.

“We’ve introduced Gemini inside our threat intelligence tools,” Kurian tells Thompson. “It’s 98% accurate and has processed 3.9 million threats in the last year, so that’s an example of Gemini being used as an embedded capability.”

It’s also not the only advantage Google has over rivals in security, says Campbell, noting that along with an AI infrastructure and models Google owns Wiz, Mandiant, and Chronicle, or Google Security Operations as it’s been known since Google parent Alphabet converted the system from a stand-alone “moonshot” project to part of the Google Cloud security portfolio in 2019.

“Those are all leading in the space, and I think that allows them to have a really good understanding of what they need to do to basically make sure [AI] compliance, governance, security are all there and working properly,” Campbell says.

They’re exhibiting interest in letting other companies in on that understanding too, according to Ingram Micro CISO Forrest Smith. “I’m seeing hints and signals that they’re looking at security very broadly,” he says. “They’re looking at, can I do security across Gemini and Anthropic and GPT?”

Which gets to another Google strength, in its own eyes and that of its partners—an openness to peaceful co-existence with AI products from other companies.

“On any transformation of this magnitude, you have to come to customers where they are, not where you wish they might be,” Larson says. “There’s going to be a bunch of models that do very, very targeted things extraordinarily well, and we embrace customer choice in that.”

Borcherding likes that about Google’s AI stack. “It’s open,” he says, citing Google’s Model Garden as an illustration of that philosophy in action. “It doesn’t restrict us from still deploying what would be the best model in the best scenario.”

Sanjib Sahoo, president of Ingram Micro’s global platform group, appreciates Google’s willingness to play well with others too. “It’s cloud agnostic,” he says of the company’s AI platform, and even more so since last week’s release of a new cross-cloud Lakehouse that federates data from Google and non-Google sources in a single repository. Xvantage, Ingram’s AI-forward, next-gen platform, runs almost entirely on Google Cloud, Sahoo notes, but interfaces with a variety of other systems as well. Google’s openness makes that easier.

“They’re trying to play the connector, not just an individual cloud provider, which is, I think, really smart, because more and more you have to be cloud agnostic and you have to be solution agnostic,” Sahoo says.

Microsoft partners intrigued by Gemini Enterprise can take advantage of that agnosticism too, Prosser adds. “We’ve got connectors to the Microsoft tools,” she says. “We’re not saying that you have to rip and replace something that’s already in place. We’re giving you something to wrap around it and get even more value out of it.”

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Building the channel

As impressive as everything we’ve discussed to this point is, though, all it does is get Google into the agentic AI ball game. To win that game, the company needs partners too. And it knows it.

“Customers are embarking on their agentic transformation,” Larson (pictured) says. “We need to build an ecosystem of partners to go help them.” The all-new partner program Google began rolling out earlier this year is purpose built for that mission, he adds.

But perhaps not sufficient to get the job done entirely on its own, which brings us back around to 750 million. That’s the number of dollars Google says it’s put into a new fund designed to accelerate agentic AI channel development, an amount so big it dwarfs the mere $100 million Anthropic set aside for partners just last month and left Borcherding a little giddy.

“I was doing cartwheels in the hallway,” he says. “That helps us make the investments that we need to continue to grow and expand and take advantage of the momentum that’s happening right now in the market, so I was thrilled with it.”

According to Larson, some of the new money will go into training and enablement resources. Some will cover the cost of implanting forward deployed engineers of the kind OpenAI has assigned to Shield Technology Partners with global system integrators like Accenture, Cognizant, and Deloitte. And several hundred million of it will serve as “deal acceleration funds” to help partners of all kinds and sizes conduct co-sell activities like workshops, assessments, and pilots.

Prosser hopes the sheer scale of that commitment, if nothing else, inspires partners who haven’t thought seriously about working with Google in a while, including the giant mass of SMB partners long aligned with Microsoft, to give the company a second look. “I think they’d be pleasantly surprised,” she says.

Borcherding, who’s been a member of Google’s partner advisory board since last fall, certainly has been. “They’re leaning heavily in with partners,” he says. “It wasn’t always like that at Google.”

That said, Borcherding continues, the company still has some work to do, like ensuring that its field sales reps both appreciate the importance of partners and know which one to bring in on which opportunity. Google aspires to attach a partner to 100% of deals, according to Prosser, in no small part because deals involving partners are 5% larger than direct ones on average and close at a 1.5x rate. By her own admission, though, it has yet to turn that aspiration into reality. “We’re close” is about as specific as she’ll get for now.

It’s one of many things partners serious about AI and open-minded enough to consider forging new vendor relationships will be watching closely.

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Over on the Business of Tech

Host Dave Sobel is pondering the AI governance gap:

Here’s the mechanism: once GenAI touches real workflows, two properties dominate. It’s metered—cost scales with usage. And it’s probabilistic—outputs vary, and can be wrong. Put those inside a business process and you don’t have a software rollout problem. You have an operations problem.

Lots more thoughts on the topic available here.

A few more bits and pieces

1. Google feels the need for speed too. Remember this passage from last week’s post about how desperate partners are to capitalize on AI ASAP?

“I cannot tell you how often I’ve heard that,” says Pax8 chief strategy officer Ryan Walsh. “I want to go faster. If I have an insight, I want to go faster. If I have a good offering, I’ve got to go faster.”

Well, Larson is hearing it too, and factoring it into the ongoing launch process for the new partner program he leads.

“I’m used to having to take a measured approach towards rolling out partner programs because the ecosystem takes time to consume it,” he says. “Here, the partner’s message to me is very different. It’s go faster. There’s an inflection point here. We realize that this is the world’s greatest opportunity that we might see in our lifetimes, but also a threat if we don’t seize that opportunity and stay out in front of it.”

2. Google has no fear of agentic disintermediation. You may also remember my writing last week about N-able’s new MCP server and the decision it reveals inside the company to embrace an inevitable future in which agents bypass its interfaces to work directly with underlying data. Google has a similar attitude.

“There’s a strong recognition that the genie’s out of the bottle and it’s not going back,” Larson says.

Ingram Micro holds the same conviction. Its Xvantage platform has a new MCP server that some partners are testing right now.

“What we have to work out is the security components of MCP, where they’re working with us agent to agent,” Sahoo (pictured) says. Once that’s done though, he continues, MCP will play perfectly into Ingram’s long-term strategy for continuing to attract and retain partners despite competition from hyperscaler marketplaces.

“They’re not partnering with a distributor anymore. They’re partnering with a platform,” Sahoo says. “More and more, we are moving away from selling products to selling outcomes with intelligence. That’s what MCP will do for us.”

3. Google sees resellable agents as a partner opportunity. Regular readers have spent much of the last year following an active debate between companies like Pax8 heavily invested in the idea that selling ready-made agents is a partner opportunity and others like Ingram Micro that question whether ready-made agents are even a thing. Count Google as a member of Team It’s a Thing.

“There’s going to be agents of all kinds,” Larson predicts. “There’s going to be some agents that partners decide to use just internally. There’s going to be some agents that they feel like they can monetize with their customers.” Google will be more than happy to help sell those agents through its Agent Gallery, he continues, noting that there are roughly 2,000 agents in there now, and many more coming.

4. Data alone does not a moat make. Ingram CEO Paul Bay recently called the company’s 40 years of customer and partner data its competitive moat in the age of AI. Sahoo has a slightly more nuanced view of the matter.

Yes, he says, Ingram’s mass of data, which he spent much of his first year on the job with the company consolidating, is an incredible resource. But a data lake isn’t much use without a surrounding AI infrastructure.

“If you do not have your architecture abstraction right, it’s not going to work the same,” Sahoo says. “Our architecture is our secret sauce.”

But still not enough to sustain a moat on its own. People matter too.

“We’ve brought in a lot of engineering talent,” Sahoo says.

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The security downside of agentic AI

Agentic AI is a source of immense promise for partners—and equally immense risk. Agentic security exec Avihay Nathan of Palo Alto Networks explains the risk part as only someone with his insider’s knowledge of the topic can on the newest episode of MSP Chat, the podcast I co-host. More episodes here.

Also worth noting

• You’ve still got some time to influence where GTIA donates the $2 million it’s set aside to support non-profit technology workforce and community initiatives.

• Just in time for Next: CrowdStrike has extended its real-time cloud detection and response capabilities to Google Cloud environments.

• Acronis has launched GenAI Protection to help MSPs secure and govern the use of AI tools.

• Todyl has introduced an assurance marketplace full of solutions enabling security proof, compliance, and insurability.

• Zapier’s new AI governance features are designed to cover AI agents, MCP-connected AI assistants, no-code workflows, and every other surface where AI runs.

• Who wants to bet AI’s any better: 34% of security pros say they have significant cloud security skills, 53% say they have some, and 13% say they have none, according to ISC2.

• And not a moment too soon! Cisco has introduced a universal quantum networking switch to advance development of scalable quantum networks.

• And not a moment too soon! Juniper Research says 27% of businesses globally are deploying post-quantum cryptography solutions.

• And not a moment too soon! Portal26 has added AI agentic cost control capabilities designed to manage and optimize spending on AI-driven services.

• Speaking of quantum, Cowbell has launched a new U.S. cyberinsurance policy offering coverage of emerging AI and quantum-related risks.

• Zero Networks has launched AI segmentation technology designed to control AI agents, improve visibility, and prevent AI-driven lateral movement in enterprise environments.

• Kamiwaza has expanded public-sector access to its ARIA 508 accessibility AI agent in alliance with TD SYNNEX and Hewlett Packard Enterprise.

• Yikes: 53% of businesses are operating agents autonomously, according to research from the Cloud Security Alliance and Token. 59% say their monitoring of those agents is “largely periodic.”

• Want more anxiety fuel? ShareGate says 93% of organizations say they’re confident their Microsoft 365 governance framework can support AI responsibly. Yet 29% also say AI tools have already surfaced sensitive data they shouldn’t have accessed.

• Cato Networks says the new universal zero-trust network access addition to its enterprise browser eliminates the need for multiple browser-related tools.

• Ivanti has added new autonomous AI-driven capabilities for IT and security operations to its Neurons platform.

• Mega Mega-er: New Charter Technologies has acquired Florida-based MSP ICG.

Perhaps it’s time to rethink resilience.

OpenAI certainly thinks so. There are nine references to “resilience” and “resilient” in the company’s recently published thought piece on AI’s social, economic, and political implications, only one of which is (glancingly) about the kind of resilience we in IT know best, which is cyber resilience.

N-able thinks so too. Protecting systems and data is critical stuff, the company believes, but bring it up with a CEO and they’ll pass you along to their CIO, or whoever else they pay to worry about systems and data.

Business resilience, by contrast, goes straight to every CEO’s innermost anxiety: business continuity. As in, will I continue to have a business if it gets hit with something dangerous and unexpected. Same underlying technologies. Different, more compelling conversation, which is why encouraging partners to discuss business continuity in the existential sense was high on N-able’s agenda during its Empower conference in Fort Lauderdale last week.

“The goal really is to make sure that there’s a resilience layer around businesses so they’re not disrupted,” says John Pagliuca (pictured), the vendor’s president and CEO.

He was talking about the kind of disruption associated with downtime, of course, but I’d argue that in the AI era the kind of disruption associated with Clayton Christensen is at least as relevant to business continuity. SMBs appear to agree too. 62% of them, according to data from Pax8 last month, think AI has become a requirement for continuing to be competitive, and 67% expect to use AI more often in the next year as a result.

The problem, however, is that AI refuses to stand still. With new models, new tools, and new growth strategies, both real and illusory, popping up faster and faster, true business resilience these days is about more than being ready for cyberattacks. It’s about being ready for anything.

“There’s a workforce level of resilience that we need to be thoughtful of. There’s a financial level of resilience that we need to be thoughtful of. There’s a technological level of resilience,” Pagliuca observes.

And, if you’re an IT provider, a level of “unit economic resilience and margin resilience” as well, according to Will Dawson, mideast regional CEO of Lyra Technology Group, the managed services arm of mega mega MSP Evergreen.

“For me, the first step to resilience is owning your P&L and having that P&L discipline so you can react and then reinvest or shift as necessary,” he says. “You can’t be nimble, you can’t react in real time to macroeconomic market changes and market dynamics that are occurring, unless you actually have that very, very dialed in.”

Especially now, when the real time you’re trying to react to keeps accelerating. “The world is speeding up and it’s going to just get faster and faster in this agentic world,” Pagliuca observes.

MSPs are desperate to keep pace. “I cannot tell you how often I’ve heard that,” says Pax8 chief strategy officer Ryan Walsh. “I want to go faster. If I have an insight, I want to go faster. If I have a good offering, I’ve got to go faster.”

Which is why I’m starting to think that the strategic software asset MSPs most need might not be systems of action, per an earlier post, after all. Action is fine when you’re talking generative AI. It’s too slow when you’re talking agentic AI. To win under agentic conditions, you don’t need a system of action. You need a system of speed.

When humans are too slow

It’s a clumsy term that I just made up, so you’ll probably never encounter it again, but the underlying logic is clear enough. A system of action automates work. A system of speed accelerates automation by taking humans as far out of the loop as one dares.

The most obvious use case, per my RSA Conference writeup a few weeks ago, is security. Businesses used to have a good two weeks to detect and remediate a breach before data was exfiltrated, encrypted, or both, says Robert Johnston, the VP and general manager in charge of N-able’s Adlumin MDR/XDR unit.

“Now you might have 10 minutes, 20 minutes,” he notes. “We’re going to be outpaced by attackers if we’re not able to change the way we do defense.”

And overwhelmed, one might add, once frighteningly effective models of the kind Anthropic has teased us all with make finding and exploiting vulnerabilities much, much easier.

“There’s a tidal wave coming,” says Mike Adler (pictured), N-able’s chief technology and product officer.

Adlumin is N-able’s system of speed for coping with that tidal wave. Powered by the same AI that attackers are exploiting, the service handles 90% of incidents that “might have taken you hours, maybe the better part of a day” to tackle, according to Pagliuca, in more like 14-16 minutes instead.

Modern Threat Protection is ConnectWise’s equivalent. Introduced earlier this month, the combo managed EDR, SIEM, and email security solution employs seven role-specific agents to triage and analyze security events and then, if necessary, isolate affected endpoints, open a ticket, and attach a detailed incident report, all at a speed humans can’t match.

“People, especially in tier one, are too slow,” says Russ Humphries, the vendor’s EVP of product management for cybersecurity and data protection.

They also make too many mistakes, Humphries adds. Agents, by contrast, are reliable enough for ConnectWise to offer a 15-minute SLA and money-back guarantee on the managed EDR portion of Modern Threat Protection now, and an additional portion soon.

“All of that agentic goodness, all of that auto-ticket generation, all of that auto-triage, and the SLA promise will be coming to our SIEM offering by the end of this quarter,” Humphries says.

ConnectWise, as we saw earlier this year, is bringing system of speed functionality to ticketing as well. So too now is N-able. Among its several product announcements at Empower was the launch of N-zo, an AI-powered technical expert embedded in N-able’s unified endpoint management solutions.

“It’s really a series of experts,” Adler says. One, for example, specializes in scripting. Others focus on patching, asset management, backup, and the like. Right now, all of them provide real-time advice through a natural language chat window. Later this year, they’ll begin accelerating response times by handling tasks (with human approval) autonomously for users as well. Longer term, according to Pagliuca, forthcoming proactive AI technologies will cut response times to zero by reducing the need for response times in the first place.

“The real goal is not to respond to a ticket fast,” he says. “The real goal is to alleviate the majority of tickets from happening before they even need to happen.”

Partners like Frank DeGeorge, CTO of Lake Forest, Ill.-based Impact Networking, are willing to wait for advances like that, from N-able and others. But not forever. Vendors are making a lot of AI-related profitability promises right now, he notes. Sooner versus later, that ROI needs to start materializing in objectively measurable ways.

“So revenue per employee, profit per employee, number of endpoints per engineer, first call effectiveness,” DeGeorge says. “Those are the things that I’m going to look for in the next 12 months, because all this is BS if it doesn’t move that number. There has to be real operating leverage.”

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N-able and ConnectWise agree: SecOps alone does not a platform make

The need for speed isn’t the only thing N-able and ConnectWise agree on. They’re also big believers in the power of platform. As you’ve read here before, most MSPs these days like the sound of sourcing more products with tighter integration from fewer suppliers.

“MSPs prefer to consume full end-to-end solutions that provide them an outcome, and if they can get that from a single vendor, that’s a win,” Adler says.

The DRaaS solution N-able introduced during Empower illustrates why, he adds. MSPs need BDR solutions and post-disaster recovery environments. Getting both from the same vendor saves time and money.

“I can test a runbook from beginning to end, and I only have one vendor to worry about, and I know that it’s all integrated,” Adler says. “That’s just tremendous value.”

It’s also something most security platform purveyors don’t offer, making it part of a larger edge both N-able and ConnectWise claim over companies like Palo Alto, CrowdStrike, and Trend Micro. Those vendors do security operations, notes N-able CMO Vikram Ramesh. We do security operations, IT operations, and data protection operations in a single, natively-integrated package.

“Our competitors offer one piece of the story, or they may offer the second piece with a partnership, but they don’t have all three,” Ramesh says.

That N-able does saves its partners time during investigations and remediations, Johnston notes, and saves them money on service delivery.

“When you look at our customers, the same people doing IT operations are the same people doing security operations,” he says. Handling both functions in one place boosts technician productivity.

Humphries (pictured) agrees. Security vendors can promise the same result via “perceptual” platform connections with alliance partners, he observes, but can’t deliver the same results without the kind of deep integration made possible by real platforms like ConnectWise’s Asio.

“Perceptual platforms are quite often a set of modules that are glued together with plumbing,” he says. “A real platform has services and a microservice architecture and service buses.” MSPs, Humphries asserts, want the real thing.

From the department of corrections

Mea culpa. Remember when I said that N-able’s now a security vendor last November? I was wrong. Or rather, I was right, but only partially so.

Talking with N-able executives last week about the vendor’s unified SecOps/ITOps/DataOps platform made clear that while N-able is a security vendor, it’s also an endpoint management vendor and data protection vendor. That, in turn, means its competitors include not only Barracuda and Sophos, but ConnectWise, Kaseya, NinjaOne, and Veeam as well. That’s a lot of well-known, well-funded businesses to outflank, Ramesh concedes, but key to the company’s value proposition as well.

“We’re the only vendor focused on the SMB space that has the three pieces of the story,” he says.

Over on the Business of Tech

Host Dave Sobel spent time talking about Treeline, the venture-backed MSP I wrote about recently, with someone who looks a whole lot like me.

Because he was me. Or is me, rather. Listen to the whole conversation here.

Some vendors fear SaaSpocalyptic disintermediation. N-able doesn’t.

At least three companies I’m aware of made MCP-related news last week. One was N-able, which unveiled a new MCP server giving third-party AI solutions direct access to data in the company’s unified endpoint management systems. The other two are Salesforce and GreenCore Solutions Corp.

And who, you ask, is GreenCore Solutions Corp.? Why, none other than the maker of the TreeFree Diaper®, an environmentally responsible alternative to the likes of Pampers and Huggies that’s now also, thanks to GreenCore’s new MCP server, “the first AI-ready diaper SKU in the market.”

Laugh if you like, but I applaud their vision. Parents have done the diaper shopping for about as long as retailers have sold diapers, but in the not-too-distant future their agents will perform that function instead. Rather than fight that development and its troubling implications for brand awareness and customer relationships, GreenCore is embracing the inevitable.

So is N-able. Some CEOs undoubtedly fear becoming an invisible data lake for MSPs who use Claude or ChatGPT as their primary help desk tool. Pagliuca (like the folks at BDR vendor Slide) is entirely chill about it.

“Some folks in MSP-land and enterprise are going to choose to have a different interface experience, and so they might not be spending all of their time in the SaaS tools, which troubles a bunch of SaaS vendors,” he says. “It doesn’t bother me.”

Everyone else should get used to it too, Johnston adds. “The writing on the wall is customers expect to be able to chat and interact with their systems and command them to do things and consume information from them in a natural language format,” he says. “That’s just the bandwagon all the software vendors have to get on, because consumer expectations are going to go that way.”

And by consumer he very much means MSPs, and all of them, within perhaps five to seven years. No matter how intuitive their design, today’s RMM solutions take time to learn. “What MCP kind of allows you to do and AI allows you to do is erase that to zero. You just have to know what you want and somewhat what the system is capable of doing, and then you can just chat it in or voice it in and it’ll figure it out for you,” Johnston says. “You don’t have to learn the UI anymore.”

N-able doesn’t even mind the disintermediating prospect of ending up a contributing data provider to someone else’s newer system of action or more all-encompassing system of record.

“Different folks will bring different AI solutions to the market,” Adler says. “We can provide them pieces. We gain economic value. They gain economic value. It’s a win for both of us.”

And a source of competitive advantage over less forward-thinking peers, he adds. “We’re able to service different kinds of customers from the same avenue.”

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Two pod interviews for the price of one!

And that price is nothing. I spent the first part of last week, before my visit to N-able Empower, at the Channel Partners Conference & Expo, moderating panels, speaking (off the record) with Shield Technology Partners CEO Jim Siders for the first time, and recording two interviews for MSP Chat, the podcast I co-host. One was with Bobby DeMarzo, the impresario in charge of the Channel Partners show. The other was with Peter Kujawa, the EVP in charge of ConnectWise’s IT Nation and Service Leadership groups. Both are included in the latest episode, available here.

Also worth noting

• Speaking, as we have been, of cyber resilience, 87% of U.S. SMBs feel slightly to very confident that their business is cyber resilient, according to research from ESET. I’ll be getting into that with the company on an upcoming episode of MSP Chat.

• According to Kaseya’s 2026 State of the MSP Report, 48% of MSPs rank AI and automation as their top client needs for 2026, but just 13% are generating revenue from them. I’ll be getting into that on another upcoming episode of MSP Chat.

• Veeam’s latest research says that 90% of security leaders believe they can recover quickly but only 28% hit by ransomware could fully restore all affected data. I’ll get into this with the company a little under a month from now at its VeeamON event.

• New Charter Technologies is mega mega-er following its acquisition of GraVoc.

• Microsoft’s Windows 365 Business service will be 20% cheaper starting May 1^st.

• TD SYNNEX has added dedicated NVIDIA HGX B300-based clusters to its Nebius AI Cloud offering.

• TD SYNNEX is also partnering with Orca Security on AI-driven cloud security.

• D&H’s new Success Path to MSP Toolkit is designed to help resellers become MSPs or MSSPs.

• Salesforce has launched a Forward Deployed Engineer Partner Network and AgentExchange, a Pax8-esque marketplace for AI agents and related solutions.

• WatchGuard is integrating its cloud-based management interface with Halo’s rapidly up-and-coming PSA solution.

• Bitdefender has introduced GravityZone Extended Email Security to provide advanced email threat protection.

• Axonius has released AI-powered remediation capabilities across a wide range of asset types and environments.

• And not a moment too soon, either: Sectigo has added private post-quantum cryptography certificates to its Certificate Manager offering.

• KnowBe4’s new Agent Risk Manager aims to secure both human users and AI agents against security threats.

• Aura has launched a BYOD security offering for MSPs designed to protect employee-owned devices in business environments.

• Cork has introduced an automated data mapping feature to address the “dirty data problem” in MSP cybersecurity programs.

• Blancco and Cambrionix have launched an integrated solution for erasing and reimaging Apple devices at scale.

• 86% of businesses expect AI agents to outpace their organization’s security guardrails within the next year, according to Rubrik.

• Keep in mind that Anthropic’s Project Glasswing is scarcely two weeks old and that Synack probably hasn’t seen Mythos Preview yet before deciding whether or not to take Synack’s new Glasswing Readiness Assessment.

• Trustifi has introduced AI-powered security awareness training videos.

• Keeper Security has added new governance and visibility capabilities to its Endpoint Privilege Manager solution.

• According to HP, Poly Edge V Series desk phones all use NoiseBlockAI technology to deliver next-gen call clarity.

• 80% of IT professionals see their role shifting from operator to AI orchestrator, according to new research from SolarWinds.

• SolarWinds has also launched SW1, an agentic AI teammate designed to automate and enhance IT operations.

• Procure IT and NetWolves are partnering to deliver AI-driven intelligence and technology expense management.

• Tracy Thibodeau is the new VP of product, AI, at Monjur.

• AppDirect has acquired PartnerStack to equip its B2B subscription commerce platform with built-in PRM.

• The Alliance of Channel Women has announced winners of its 2025 IMPACT and Sponsor Awards recognizing contributions to the channel community and its 2025 LEAD, INSPIRE, and EMPOWER awards honoring influential women in the channel.

• Cloud Girls Rising’s Women to Watch awards program has recognized six emerging women leaders in technology.

• Tech4Change has announced the winners of its inaugural Heart of the Channel Awards.

At least three companies I’m aware of made MCP-related news last week. One was N-able, which unveiled a new MCP server giving third-party AI solutions direct access to data in the company’s unified endpoint management systems. The other two are Salesforce and GreenCore Solutions Corp.

And who, you ask, is GreenCore Solutions Corp.? Why, none other than the maker of the TreeFree Diaper®, an environmentally responsible alternative to the likes of Pampers and Huggies that’s now also, thanks to GreenCore’s new MCP server, “the first AI-ready diaper SKU in the market.”

Laugh if you like, but I applaud their vision. Parents have done the diaper shopping for about as long as retailers have sold diapers, but in the not-too-distant future their agents will perform that function instead. Rather than fight that development and its troubling implications for brand awareness and customer relationships, GreenCore is embracing the inevitable.

So is N-able. Some CEOs undoubtedly fear becoming an invisible data lake for MSPs who use Claude or ChatGPT as their primary help desk tool. N-able president and CEO John Pagliuca (like the folks at BDR vendor Slide) is entirely chill about it.

“Some folks in MSP-land and enterprise are going to choose to have a different interface experience, and so they might not be spending all of their time in the SaaS tools, which troubles a bunch of SaaS vendors,” he says. “It doesn’t bother me.”

Everyone else should get used to it too, Robert Johnston, the VP and GM in charge of N-able’s Adlumin business, adds. “The writing on the wall is customers expect to be able to chat and interact with their systems and command them to do things and consume information from them in a natural language format,” he says. “That’s just the bandwagon all the software vendors have to get on, because consumer expectations are going to go that way.”

And by consumer he very much means MSPs, and all of them, within perhaps five to seven years. No matter how intuitive their design, today’s RMM solutions take time to learn. “What MCP kind of allows you to do and AI allows you to do is erase that to zero. You just have to know what you want and somewhat what the system is capable of doing, and then you can just chat it in or voice it in and it’ll figure it out for you,” Johnston says. “You don’t have to learn the UI anymore.”

N-able doesn’t even mind the disintermediating prospect of ending up a contributing data provider to someone else’s newer system of action or more all-encompassing system of record.

“Different folks will bring different AI solutions to the market,” N-able chief technology and product officer Mike Adler says. “We can provide them pieces. We gain economic value. They gain economic value. It’s a win for both of us.”

And a source of competitive advantage over less forward-thinking peers, he adds. “We’re able to service different kinds of customers from the same avenue.”

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Two pod interviews for the price of one!

And that price is nothing. I spent the first part of last week, before my visit to N-able Empower, at the Channel Partners Conference & Expo, moderating panels, speaking (off the record) with Shield Technology Partners CEO Jim Siders for the first time, and recording two interviews for MSP Chat, the podcast I co-host. One was with Bobby DeMarzo, the impresario in charge of the Channel Partners show. The other was with Peter Kujawa, the EVP in charge of ConnectWise’s IT Nation and Service Leadership groups. Both are included in the latest episode, available here.

There’s a lot we don’t know about AI.

Like how much time we have before it drowns us with zero days, how much of what it says is correct (and how many of us even care), how much we can trust the results when it aces a safety test, and whether or not it’s making us dumber.

Most of us don’t know what we’re spending on it either.

I mean, we know it’s a lot and growing fast. AI spending of all kinds will climb 44% this year to $2.5 trillion, according to Gartner, while spending specifically on AI models will soar nearly 83% to $26.4 billion. The growth is even sharper for specific AI workloads, furthermore: Average per-organization consumption of tokens for reasoning in particular rose 320x last year at OpenAI, for example.

We also know that totals like that translate to smaller yet substantial equivalents at individual businesses, some 40% of which now spend $10 million or more a year on AI, according to cloud cost management vendor CloudZero. For perspective, that’s similar to the 47% of businesses that spend the same amount on cloud computing, and the gap’s closing fast.

Yet we really don’t know how to forecast AI outlays. AI spend projections were off by 50% or more, in fact, at 20% of the companies surveyed by CloudZero, which encapsulates the reason why nicely in a press release.

“Most companies use some combination of public cloud, private cloud, third-party GPU providers, and hosted LLM APIs. These providers have different billing frameworks, send bills at different intervals, and use different data formats, making it nearly impossible for companies to get a comprehensive overview of what they’re spending—much less what exactly they’re spending it on.”

Even businesses that get all their AI from one source, moreover, often struggle to anticipate future needs. “The volatility of AI workloads—from bursty training cycles to unpredictable inferencing spikes—means that static budgeting and quarterly forecasts can’t keep up,” writes Jevin Jensen, a research vice president for infrastructure and operations at IDC, in an excellent blog post about AI FinOps. “Every new experiment, every dataset added, every prompt creates a ripple in compute, storage, and energy consumption—often in exponential amounts.”

Is it any wonder that spending businesses can’t accurately forecast and struggle merely to track tends to be less than efficient? According to IDC, 41% of organizations are wasting more than 15% of their AI budget currently.

“If you’re talking about projects that are half a million dollars, a million dollars, and if you’re a big company, multimillion dollar projects, 15% is not a small amount of money you’re wasting,” Jensen (pictured) observes.

And that’s before the global population of agents autonomously and often invisibly consuming tokens rises from 28.8 million last year, according to IDC, to a staggering 2.3 billion in 2030.

“You’re talking about having two or three agents per employee,” Jensen says. “All of a sudden you’ve got more agents than you have servers.”

Issues like this are a problem, needless to say, for end users (“I’ve run the numbers, boss, and our projected AI spend for the rest of the year is somewhere between our current run rate and infinity”). They’re even thornier ones for MSPs selling AI solutions and services with unpredictable costs to customers who want entirely predictable rates, not to mention vendors serving MSPs with similar demands.

“A big question becomes - how can you price your product such that you don’t torpedo your business into perpetual negative gross margin,” writes Jamin Ball of Altimeter Capital in a recent blog post.

Or merely declining gross margin. OpenAI itself saw margins drop from 40% to 33% last year, according to The Information, thanks to a 4x increase in inferencing expenses.

Imperfect answers

Jensen has seen this movie before. Cloud costs were devilishly hard to govern even before the Covid pandemic led businesses to put everything on-prem online instead.

“Then they got the bills one month, two months, three months later, and their CFO had a heart attack,” Jensen says.

Cloud FinOps solutions proliferated as a result. IDC, in fact, tracks 135 such systems at present, and while not all of them have AI FinOps features, those that do help businesses set spending guardrails, catch anomalies early, and design systems with cost in mind. Theoretically, they can also spare CFOs at companies with tokenmaxxing developers a fresh round of heart attacks too.

“FinOps tools cannot eliminate variability, but they can make it manageable,” says Rem Baumann (pictured), head of product at AI FinOps vendor Vantage.

Same goes with pricing. “FinOps tools break down cost per API call, per workflow, or per tenant,” Baumann says. “That allows providers to align pricing with actual cost and protect margins as usage scales.”

Unfortunately for managed service providers, Vantage makes one of just a handful of AI FinOps solutions with multi-tenancy. MSPs that don’t want or can’t afford any of them can potentially create something similar on their own, however, using the same AI that created their cost management headaches in the first place, according to Evan Rice, president and COO of managed services software maker Rev.io. Indeed, that’s exactly what he and his team have done.

“Our agents internally, including my own personal one every week, does an ROI dashboard for me that shows, ‘here’s the workflows I did. Here’s the token utilization around those workflows,’” says Rice on the latest episode of the podcast I co-host. Pull in some sales and accounting information too and you’ve got a pretty good sense for whether what you’re spending on AI adds up in light of what you’re making and saving with it.

“That’s how we framed it to our agents. You’re an employee, you’re a valued member of the team. Your salary and compensation are your token consumption. Calculate your costs and justify your continuing to do these things and show the value that you’re delivering,” Rice says. “They’ve done a pretty good job with it so far.”

I’m sure they have. Digital workers may be a lot less predictable than human ones, but they’re every bit as eager to avoid unemployment.

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Speaking of Evan Rice…

You can hear him speak yourself, intelligently and at length, about how MSPs can own the agentic layer at SMBs on the latest episode of MSP Chat. Available right here, right now.

Ready or not (and you’re probably not), quantum computing’s nearing

So, as we’ve just established, there’s a lot we don’t know about AI. Same’s true of quantum computing, where experts like David Mooter, a principal analyst at Forrester, didn’t even know with 100% certainty that it would ever come off the drawing board in a meaningful way as recently as a couple years ago.

“The error rates were just way too high. The qubit counts were just too low,” he says.

And now?

“Now I feel like it will be a reality. I’m very confident in that,” Mooter (pictured) says. “When is definitely more of an up-in-the-air question.”

And also an extremely important one, certainly for venture capital firms, which tripled their investments in quantum startups last year to $5.8 billion, and almost certainly for the rest of us too. Before I discuss why, I should make clear that quantum computers are not supercomputers that can just solve everything, because…well:

“One thing I have seen that drives me nuts is journalists who don’t know what they’re talking about will describe quantum computers as supercomputers that can just solve everything,” Mooter says. “The way I like to describe it is that quantum computers are not supercomputers. They’re different computers. They solve problems in a different way.”

That different way, without getting deep into the (quantum) mechanics of the matter, lends itself especially well to combinatorial challenges like the traveling salesman problem in which there are huge volumes of possible solutions, way more for a human to sort through ever and more than even powerful classical computers can handle quickly. Mooter points to modeling molecular interactions for drug discovery as one example and optimizing investment portfolios as another. Optimizing supply chains, energy grids, and chemical manufacturing processes are among others frequently cited.

Good news for anyone who likes the sound of improving all those areas and more: Your wait continues to get shorter and shorter. In fact, quantum computing made such strides last year as “vendors moved beyond theoretical fault‑tolerant architectures into early engineering reality,” per a recent Forrester report, that practical commercial applications of the technology could begin arriving as soon as 2030, a good five years earlier than the analyst considered likely just 15 months ago.

Developments like that have inspired pretty much all my past writing about quantum. Generative AI was supposed to be years away when it upended our entire industry late in 2022. I’m hoping we can avoid repeating that scenario this time, but also increasingly thinking we’re going to have to move a lot faster to do so.

To take one of a steadily arriving series of examples, research published days ago by Caltech and quantum startup Oratomic outlined a new approach to quantum error reduction that could cut the minimum number of qubits required to make a useful quantum computer from millions to as few as 10,000.

Consider as well the progress being made in hybrid quantum computing, which divides processing chores across classical and quantum machines. P&G used the technique last year in an experiment aimed at optimizing a manufacturing process with 10^{^114} possible arrangements of components and ingredients, more than the number of atoms in the universe.

Acting on its own, a regular computer needed six hours to come up with an answer. SAS’s quantum AI platform needed two minutes, but produced unreliable results. Working together, however, the conventional and quantum computers produced an accurate, actionable result in 12 minutes, or about 96.7% less than what the classical machine needed solo.

Time for partners to start thinking up quantum and hybrid quantum solutions then? Maybe not.

“Don’t view quantum as the next layer that will replace CPUs and GPUs,” said Omdia analyst Jay McBain in a conversation at the Canalys Forum late last year. “It won’t, and it’s going to be interesting for very few partners, maybe in the thousands total.”

But it will be very interesting, or more accurately terrifying, for every partner in the industry with respect to security, and sooner perhaps than any of us would like. Remember that 10,000 qubit breakthrough at Caltech? Well, these guys claim they’ve found a hybrid way to break RSA encryption with just 5,000.

Could be hot air, of course, but gets to the reason we probably need to be thinking harder about quantum computing than most of us are even so. The same Forrester report that said commercial uses of quantum computing could start arriving by the end of the decade said that “Q-Day,” when quantum machines break current public-key cryptography, could arrive then too. Google is getting nervous about timelines on quantum security as well.

And we’re not ready. Governments, financial institutions, utilities, and infrastructure providers are working toward adoption of post-quantum cryptography schemes capable of keeping data safe past Q-Day, says Sandy Carielli, a VP and principal analyst at Forrester. “Firms in other industries are still learning and coming up to speed and are not as far along.”

Meaning they’re late. “I’ve been telling my clients that they have to start now, because full migration will likely take them past that 2030 date,” says Carielli, who also recommends inventorying data and prioritizing it by importance and longevity, along with forming a cross-functional Q-Day team, as good steps toward partial readiness.

And partial readiness is a whole lot better than no readiness. The other similarity between AI and quantum computing, in addition to there being a lot we don’t know about both, is that both are progressing very quickly and appear likely to progress even faster in the near future. At present, only a relative handful of people have access to quantum computers, but that was once true of classical computers as well. Then universities and research institutions started deploying them, sparking a “Cambrian explosion of algorithms,” Mooter notes.

“That took decades,” he continues. “We’ll see the same thing with quantum computers, but it won’t be decades because we’re building on the foundation of classical computer science and we have a lot more funding rolling in than computers did back in the 1950s.”

So years more likely, and I suspect they’ll feel like short ones. Brace yourself now.

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Over on the Business of Tech

Host Dave Sobel discusses Treeline, the a16z-backed, AI-native MSP I wrote about last week, with the author of that piece. As in me. I’ll be appearing on the show live this coming Wednesday here.

OpenText Cybersecurity takes a stab at closing the AI alignment problem

In a recent post, I shared data from GTIA indicating a modest but still worrying erosion of member satisfaction with vendor partner programs, as well as GTIA analyst Carolyn April’s hypothesis that misalignment between what partners want from channel programs in the age of AI and what those programs provide is probably to blame.

Mike DePalma, VP of business development at OpenText Cybersecurity and a member of GTIA’s channel executive council, saw that data too, and wasn’t surprised by it.

“That’s one of the biggest conversations that we’re all as vendors trying to figure out,” he says. “We’re all seeing a drop in satisfaction, and we know that we need to change, and it’s hard.”

Like April, he suspects that meeting partners where they are in relation to vendors versus where they once were has a lot to do with the issue. “The MSPs are different than they were 15 years ago,” DePalma (pictured) says. “Partner programs have stayed the same.”

The alliance agreement OpenText announced with Hatz AI last week is DePalma’s first stab at a remedy. It’s also the first example I can think of since I attended that GTIA conference of a channel chief offering a new benefit to partners specifically in response to changing needs due to AI.

And to be clear, this is all about partner sat. There’s no back end integration happening here. The deal is a referral program pure and simple, and a one-way referral program at that, with leads flowing solely from OpenText to Hatz.

“There’s nothing coming back our way,” DePalma says. “We’re looking at it as what can we add to our partner program that they’re asking for that moves the needle.”

Introductions to Hatz was not a guess. OpenText asked partners what would move the needle in focus groups and got two answers. One was more enablement resources. The other was connections with other vendors. “They’re asking for vendors to work together, to form stronger alliances, whether they’re competitors or not,” DePalma says. The Hatz AI agreement satisfies both asks.

“We want people that are partners to feel that OpenText really cares about us. They don’t just care about what they’re spending with us, they care about helping us grow,” DePalma says.

DePalma and his colleagues at OpenText are exploring lots of ways to send that message at present as they race toward readying an all-new partner program for an official launch on July 1. What they come up with will be of intense interest to OpenText partners. It will also be of some interest to channel watchers like me and channel chiefs at other vendors curious to see what a blank slate partner program for the age of AI looks like.

Also worth noting

• Three things not to miss at next week’s Channel Partners Conference & Expo in Las Vegas: This session I’m moderating, this other session I’m moderating, and the Alliance of Channel Women’s opening day networking event.

• Modern Threat Protection, ConnectWise’s new security platform, combines managed EDR, SIEM services, and email security. More on this coming next week.

• Titan has Silicon Valley AI engineers. Shield has Silicon Valley AI engineers. Treeline has Silicon Valley AI engineers. Looks like Kaseya wants a few too.

• Gradient MSP has released a major upgrade to MSP Studio, its content marketing platform, aimed at solving the industry’s reliance on generic, “canned” content.

• Nerdio and Nutanix have forged an alliance to bring Microsoft-based virtual desktops to hybrid cloud environments.

• The new Acronis MDR by Acronis TRU offers 24/7/365 managed detection and response services tailored for MSPs.

• WatchGuard has unveiled a new endpoint pricing model aimed at giving MSPs a competitive edge through simplified and cost-effective licensing.

• Cynomi has introduced a Go-to-Market Academy designed to help MSPs grow cybersecurity revenue through structured enablement and training.

• Also from Cynomi: new CISO Intelligence AI agents designed to help MSPs scale cybersecurity services and business growth.

• NWN, which discussed AI governance with us recently, has launched a new cybersecurity offering designed to help organizations manage risk and improve security posture.

• Speaking of AI governance, 51% of MSPs say data governance and compliance challenges are the main obstacle to AI adoption, according to AvePoint and Omdia.

• 30.3% of incidents tracked by Blackpoint Cyber in 2025 involved malicious use of legitimate RMM tools, according to a new study by the company.

• Keeper Security has expanded its privileged access management and browser isolation capabilities to support advanced secure browsing workflows.

• Dashlane’s new integration with KnowBe4 aims to convert employee security awareness training into real-time, proactive defense against credential-based threats.

• Norton has added AI agent protection to Norton 360.

• PRM vendor Channelscaler has launched Scailyn, an AI-powered channel agent designed to accelerate partner engagement and innovation.

• Wasabi Technologies says it will acquire Seagate Lyve Cloud to expand its cloud storage business.

• Cisco says it will acquire Galileo to enhance its observability and AI agent monitoring capabilities.

• Channel Leaders, a peer group for channel sales professionals, is now a full-blown community for channel sales professionals called the Channel Sales Association.

• Alex Hesterberg is the new CEO at Devicie, who you read about here earlier.

• Lindsey Westbrook is the new VP of marketing at Coro.

• Alysia Vetter is the new director of PR and communications at GTIA.

• Sharon Florentine is now manager and research analyst at GTIA.