Most MSP Problems Aren’t Technical, and AI is the Least of IT All (In your customer’s mind...)

John Harden • March 18, 2026

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The more conversations I have with MSPs about monetizing AI, the less convinced I am that their biggest problems are technical. 

 

They feel technical. They show up as tool debates, platform decisions, AI comparisons, and architecture questions. What bothers me is everyone treats this AI problem like an engineering problem that just need better tools. 

 

But that’s not actually where things break down. 

 

What I hear most often isn’t “this tool doesn’t work.” 

 It’s “we’re not sure what to use.” 

 Or “we’re still testing a few things.” 

 Or “we don’t really know how to talk about this with customers yet.” 

 

That last part matters more than people want to admit. 

 

A lot of this came up in recent coffee chats. Someone will say they’re looking at Copilot, but also using ChatGPT, and then another AI product their vendor just showed them. They’re trying to decide which one to standardize on, whether they should offer multiple options, or whether they should even be selling AI at all yet. 

 

None of that is a technical limitation. It’s a clarity problem. 

MSPs don’t lack tools. They lack conviction. 

 

Every option sounds plausible, and in a lot of cases they ARE plausible. Every vendor has a story. Every demo works in isolation. And because everything might be important, nothing gets fully committed to. 

 

So teams keep evaluating. They keep experimenting. They keep waiting for the moment when it all becomes obvious. And in the meantime, selling AI feels hard. 

 

But that is absolutely not because customers don’t want it. But because MSPs don’t know how to explain it without talking tools. That’s the part I think a lot of people miss. Selling AI isn’t hard because the technology is complex... iIt’s hard because the narrative is unsettled. 

 

If you’re not clear on what AI is in your stack, what problem it actually solves, and where its limits are, then every sales conversation turns into a ramble. You hedge. You over‑qualify. You list tools instead of outcomes. 

 

Customers feel that. 

 

And when the story isn’t clear, trust doesn’t form. Deals stall. AI gets positioned as “interesting” instead of “necessary,” or they go on their own way and solve their own problems. AI isn’t a particularly difficult one to self-service, so that’s the path of least resistance. 

 

That’s not a sales failure. That’s a prioritization failure. 

 

Most MSPs don’t need better pitch decks or smarter demos... They need stronger filters. 

They need to decide what they believe. They need a default answer. They need to say no to a lot of things so the yes actually means something. 

 

That’s where ecosystems start to matter. 

 

An ecosystem reduces choice. It forces consistency. It gives your team shared language instead of a dozen different explanations depending on which tool someone last tried. 

 

When the internal story stabilizes, selling gets easier. Not slicker just clearer. Most MSP problems aren’t technical. And most MSP AI sales problems aren’t either. They’re narrative problems. They’re clarity problems. They’re commitment problems. 

 

AI didn’t create that. It just exposed it. And until that’s addressed, no new tool is going to make AI easier to sell. It’ll just add another option to an already crowded list. 

 

This is where my skepticism keeps leading me. 

 

The real question isn’t how do we sell AI? It’s what are we actually willing to stand behind? 

 

Once that’s clear, the rest starts to quiet down. 



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