Readiness vs Reliability: Most AI Gains in MSPs Absorbed by Existing Workloads

[00:00:01] 96% of mid-market IT leaders say they trust their managed services provider. Two-thirds of them are thinking about replacing that provider inside a year. The same people said both things in the same survey, and neither number is wrong. This is the Business of Tech. I'm Dave Sobel. The research on AI and IT service delivery has stopped disagreeing about whether it works.

[00:00:29] Let's start with SolarWinds, whose 2026 State of ITSM report, and this is a vendor studying a market it sells into, so weigh it accordingly, found that 84% of IT teams say artificial intelligence is meeting or exceeding their return on investment expectations. Not hoping it will, reporting that it already has. The teams in that study report saving about three hours a week on detecting and flagging issues,

[00:00:57] three more on handling end-user requests, and just under three on ticket triage. Take the single largest of those and nothing else. Three hours a week is roughly a day and a half of technician time recovered every month, and the people doing the work say that payback is real. Now hold on to that number because the next one comes from a different direction entirely.

[00:01:19] Corsica Technologies Commission research, fielded by Censuswide, among 600 IT and security leaders at American companies with 200 to 1,000 employees. And Corsica is itself a managed services and security provider selling into that exact market, which is a detail worth saying out loud before quoting anything they found. 95.8% of those leaders say they trust their current provider at least somewhat.

[00:01:49] 96% in the same study, about two-thirds say they are considering switching providers within the next 12 months. Think about those two numbers together because separately they each sound like something else. 96% trust sounds like a healthy market. Two-thirds shopping sounds like a market in trouble. The same people said both. They're not unhappy, and they are leaving anyway. A 96 is not a good grade here.

[00:02:18] It's a broken thermometer. When every reading comes back the same, the instrument has stopped telling you anything about the patient. Then the third number, which tells you what they are shopping for. Among the ones already considering a change, a third name limited support for artificial intelligence or automation as a driver, tied exactly with reactive rather than proactive service, and just ahead of a lack of strategic guidance at 30%. Artificial intelligence is not the whole story.

[00:02:48] It's the newly won of the three. In 99.7%, effectively all of them, call data integration critical to what they need next. Now, one more piece from outside the channel entirely. Pew Research found that more than half of American adults are now more concerned than excited about artificial intelligence, with the sharpest movement among people under 30. That is the independent read, and it matters for a very uncomfortable reason.

[00:03:17] The demand landing on providers is coming from IT leadership, not from an enthusiastic public into a workforce getting warier by the quarter. So the returns are real and reported. Satisfaction is at a ceiling. And two-thirds of satisfied clients are shopping anyway, on a criterion nobody was graded on last year. None of that adds up until you look at where the recovered hours actually went. If you're listening to this and you haven't hit follow yet,

[00:03:47] on Apple Podcasts, search Business of Tech. It takes five seconds, and you'll get the next episode automatically. I track MSP community conversations every week as part of what we do here. And the pattern I keep seeing is MSPs who are sharp enough to know that AI creates new problems as fast as it solves old ones. Clients making bad decisions, new security vectors, more ticket volume. The MSPs who are getting out ahead of this aren't the ones chasing every new tool.

[00:04:17] They're the ones who built on a solid platform and stayed committed. Pax8 is that platform. A curated cloud and agentic marketplace with AI-native tools built for scaling and simplifying provisioning, governance and operations. Education programs that prescribe a learning path. And the largest partner community in the cloud channel. 47,000 MSPs are already there.

[00:04:41] The ones who move with focus now will win opportunities that distracted players miss. Start at Pax8.com That's P-A-X, the number 8, dot com. Those hours went where they went because only one of the two halves of your business can accept them. Think about what reliability work actually looks like inside a shop. It arrives as tickets. It has a queue, an owner and a finish line you can reach before the end of the quarter.

[00:05:11] Patch the thing. Close the alert. When artificial intelligence hands back three hours a week, that work is standing right there with its hands up. It can absorb the capacity immediately and nobody has to hold a meeting about it. And SolarWinds found something that makes this literal. 83% of those teams now spend three or more hours every week just keeping their AI systems running reliably. Look at that against the time saved. The hours going in and the hours coming out are the same size.

[00:05:41] The dividend is not being banked, being consumed on site. Now look at the other half. The readiness the buyer says they are shopping on. CIO Dive, reporting on Deloitte's research, The research found that full-scale adoption of AI agents remains years away from most organizations. And the gaps named are not model quality. They are governance, workforce readiness and process redesign. That's the whole problem in one sense. There's no ticket for process redesign.

[00:06:10] There's no queue for governance. It has no completion date, no owner by default. And it cannot show a result inside the quarter it starts. And Deloitte put a number on how prepared anyone is. 5%. 5% of organizations say their business processes are highly prepared for AI agents. That's not a gap. That's an empty field. And it's worse than slow. It's often blocked before it begins.

[00:06:36] Separate research covered by CIO Dive, a Cloudera survey of 1,500 architects and infrastructure leads at companies of 1,000 employees and up, found that 95% of them delayed or canceled at least one AI initiative in the past year on governance, compliance, or regulatory grounds. Not a handful of laggards. 95%. And more than half killed or postponed more than six. The readiness work runs into the estate underneath it and stops.

[00:07:06] Now word on those studies because this audience is not the enterprise. Those samples skew large. The Cloudera one starts at 1,000 employees and even the Corsica research tops out around there. The absolute numbers do not transfer to a 30-person client in the Midwest. The shape does. And the shape gets worse as you get smaller. Because a small business has less process written down, not more. So the capacity flows downhill.

[00:07:34] Reliability work can take the hours today. Readiness work cannot take them at all. And that's not a decision anyone made badly. It's a decision nobody was asked to make. The dividend gets allocated by default, by whichever work was standing closest when it arrived. Which means the machine is working exactly as designed and pointed at the one thing that's already finished. Which turns into a problem you can act on the moment you ask what the other half would even look like.

[00:08:05] So the practical problem is not that you are behind on readiness. It's that nobody has defined what being ahead on it looks like. Including the person grading you. Inc. ran a piece on why artificial intelligence feels so hard for small businesses. And the answer it lands on is that most of them have no governance, no defined use cases, and no way to measure a business outcome from any of it. Think about what that means from where you are standing.

[00:08:33] The client who told a survey that limited AI support might make them switch cannot themselves define what adequate AI support would be. They know the shape of what they want. They do not have a specification. Which means the criterion is unwritten and the first provider who writes it down in front of them is the one who sets it. That's not a defensive position. That's the most open competitive ground this market has had in years.

[00:09:00] And it stays open for about as long as it takes for someone to plant something in it. Here's how most shops will try and plant it and why it fails. In the last two weeks alone, Kaseya launched an agentic IT management platform. Syncro shipped a server connecting live MSP data to Claw, ChatGPT, and Copilot. And Hexnode launched an AI context layer for providers, among others. Those are vendor announcements, not independent findings, and they are genuinely useful. But run the arithmetic.

[00:09:30] You buy the platform. So does everyone quoting against you. In a year, you are tied again, one layer up, on a scorecard the vendor sold to all of you at once. Purchasing is a reliability move wearing a readiness label. It cannot separate you because separation is not for sale. And you'll find this harder to steer than it should be for a reason worth naming. You cannot easily audit where your own dividend went.

[00:09:59] The hour reinvested into validation left no artifact behind. The incident prevented never happened, so it never counted. Your own recovered capacity is invisible to you, which is why it drifts. So here's your choice. Spend the dividend on the half you're being shopped against. Take the hours the tooling actually gave back and put them into readiness work the buyer is evaluating. Deliberately. That's an allocation you made on purpose.

[00:10:24] Or keep buying reliability you already have on a scorecard where you and everyone quoting against you are tied at 96. And there's a version of that choice that costs you one question. Are you and your clients tired of the time-consuming ticket tennis of coordinating meetings and help desk calls? Wouldn't it be better to automate this process with a tool that connects directly to ConnectWise Manage or Autotask?

[00:10:51] TimeZest offers scheduling automation that gives you complete control of your schedule and eliminates the hassle of calendar ping pong. As the only service designed specifically for MSPs, it integrates into your workflow and makes scheduling appointments easy on you and your clients. Plus, you can try TimeZest for free.

[00:11:12] Visit TimeZest.com slash MSP Radio and use the code MSP Radio to get 10% off your first year of TimeZest. Why do we care? The fair objection is that mentally shopping is not a request for a proposal and most of those clients will still be yours next year. Probably true, and it doesn't help you. Because you cannot tell from your side which ones are in the real third.

[00:11:38] There's exactly one instrument that resolves it, and it's a question at the next review. What would you need to see from us on AI in the next 12 months to not go looking? The ones with a fast, specific answer are already evaluating you against something. The ones who stall are handing you the chance to write the criterion yourself. So what to consider? Ask the question in the accounts you are least worried about.

[00:12:08] The instinct is to run this with a client who has been difficult lately, and that's the wrong sample. You already know where you stand there. The finding in this research is that satisfaction stopped predicting anything, which means your comfortable accounts are exactly the ones where your read is least reliable. Start with three clients you would describe as happy and treat a fast, specific answer from any of them as new information rather than a compliment.

[00:12:36] Write down what a stalled answer costs you before you get one. Most clients will not have a specification for AI readiness, and the temptation is to fill the silence with a demo or a platform name. Have something else ready. A one-page description of what you would do in their environment over the next two quarters, in their terms, tied to their data and their processes. It does not have to be a product.

[00:13:02] It has to be the first written definition of readiness that they've ever been handed, because whoever hands over the first one sets what every provider after them gets measured against. Decide the allocation before the conversation, not after. If a client tells you what they need, and you have no capacity earmarked for it, you have converted a sales opening into a promise you will break.

[00:13:27] Name the share of recovered hours that goes to readiness work, name who owns it, and do it this quarter. And picture the provider who asked. Six months from now, when a client's board starts asking what the AI plan is, that shop is not scrambling, they wrote the answer with the client half a year earlier, in the client's own words, and it has their name on it. They're not defending a renewal. They are being consulted about a budget.

[00:13:54] If this trend continues, within 12 to 18 months, the competitive question in a renewal stops being whether the client is satisfied, because they will be, and so will the provider quitting against you. And becomes whether anybody ever asked them what they were going to be measuring next. This is the business of tech. Tired of being told your business isn't big enough?

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[00:14:47] The Business of Tech is written and produced by me, Dave Sobel, under ethics guidelines posted at businessof.tech. Thanks for listening. I'll see you on the next episode. Proud member of the MSP Radio Network.