K7 Insights
AI for MSPs: It Speeds Up Whatever You Already Are
Part of Grow Your MSP
Key takeaways
- AI speeds up whatever your MSP already is. Tight process and people who can talk to clients get faster. A people problem gets automated, and now it runs at scale.
- Put AI on the work the client never sees first: triage, documentation, drafting, scripting, summarizing. Keep a human on the touchpoints where a client decides to keep you or fire you.
- Your margin problem is total salary plus tool spend across every seat, and tier 1 is the cheapest seat on the list. Make tier 1 better with work-reducing tools before you count on replacing it.
- The easy button in sales costs trust, and trust is the only thing an MSP sells. Use AI to show up more prepared and more specific, never louder.
AI for MSPs is real, and so is a lot of the hype. Here’s the frame that settles the argument you keep seeing on r/msp: AI speeds up whatever your MSP already is. If your process is tight and your people know how to talk to a client, it makes you faster at that. If your techs can’t hold a conversation and your onboarding is one guy installing agents and leaving, congratulations, you just automated it. The owner’s question was never which tool to buy. It’s where AI goes first, where it must never speak for you, and what it does to your margin and your team. That’s the decision this piece walks through, as one part of growing your MSP.
Is AI for MSPs the real deal or expensive hype?
Both, and which one you get depends on where you point it. On the work your clients never see, AI is the best new hammer the channel has picked up in a decade. At the touchpoints where a client decides whether to keep you, it’s a way to teach them to route around your company.
I’ll show you why with a piece of history. Sanford J. Morganstein was one of the inventors of the phone auto-attendant (his name is on Dytel’s 1990 patent for it), the menu of options you get before you reach a human. What he and his co-inventors really taught every household in America was one process. One button. Press zero. Why? Because people want to work with people, and pressing zero is the fastest way to get to one. Half a century of automation later, that habit is still the first thing anybody does when a recording picks up.
Now watch what MSPs are doing with AI. I hear it all day: “Let’s have AI write the client emails, because our engineers are bad at soft skills.” What you’re actually doing is two things at once. You’re teaching your customers to press zero, and you’re expecting a product to fix a people problem. Every owner I know gets annoyed when a client calls a tech’s cell phone directly. Your shiny tool is going to encourage exactly that, because the client figured out your inbox answers like a robot.
So here’s the decision frame. Before any AI goes into your shop, ask three questions. Does the client ever see this? Does a person on my team learn something by doing it? And if I automate it, what feedback goes quiet? Where the answer to all three is no, no, and nothing, turn the machine on today.
Where should AI go first in an MSP?
Behind the curtain. Ticket triage and routing. Documentation cleanup. Writing the PowerShell script your tier 2 used to spend an hour on. Summarizing a forty-message thread before the QBR. Drafting the internal handoff note. First-pass alert handling in the RMM. None of that work has a relationship attached to it, so speeding it up costs you nothing with the client and buys back real hours.
In most shops that’s the majority of the labor minutes in a week, and it’s the work that burns out good techs. Your best engineer did not get into this business to rewrite the same onboarding runbook for the eleventh time. Give that to the machine and hand the engineer the thing only a human can do, which is sit across from a client who’s scared about a breach and make them feel handled.
Two rules make this stick. First, the output stays internal or gets a human owner before it leaves the building. A script the AI wrote gets reviewed like a script a junior wrote. Second, measure the hours. The same utilization numbers you use for a vCIO will show you where the freed-up time actually went. If it went nowhere you can name, the tool is a hobby.
Where should AI never speak for your MSP?
At the two moments a client remembers: the first impression and the last interaction. Automate those and you’ve abdicated the customer experience at scale, which is a fancy way of saying you’ll find out you were fired after the fact.
Your customer is a goldfish. It doesn’t matter how smart your team is or how much you spent on the stack. When they’re deciding whether to like you, keep you, or fire you, they remember two things. Psychology has names for it: the primacy effect (you remember the start of a list) and the recency effect (you remember the end). The middle, where all your hard work lives, mostly evaporates.
Now think about what you’re gambling on those two moments. Picture the ticket where your tier 3 called the client an idiot in the notes (accidentally?) and the AI rewrite doubled down on the tone. Picture the onboarding where the client started paying you and what they got was an introverted tier 2 who ran around installing endpoints and left. Those are the last interaction and the first impression, and in both, a person wasn’t there.
The speed argument doesn’t save you either. HubSpot Research found in 2018 that 90 percent of customers rate an immediate response as important when a support issue comes up, and almost two-thirds expect that response within ten minutes. That sounds like a case for the bot until you remember what people do with a bot: they press zero. Fast and wrong is still wrong, and the client remembers exactly how it felt.
The skills worth hardening in your shop are the ones that let your people work and relate with other people, more than the ones that turn the wrench faster. That muscle only builds through reps, and the reps are the exact thing you’re about to automate away.
Does AI mean tier 1 is going away?
No, and the whole “tier 1 is going away” schtick is overplayed. It’s the front line that protects your bottom line, and we parade around like it’s the front line causing the heartache.
I get it. Some of the tools and fancy robots are going to make today’s common tier-1 work vanish, and good riddance to it. That doesn’t mean you throw the baby out with the bathwater. My friend Alex Farling says it about the last wave of this: “I was sold an RMM in 2008 to replace my tier 1s, it just required me hiring a tier 3 to operate it.” So run the math. Does the tool plus the senior nerd who runs it replace more than one junior tech? Does the cost generate more bottom line, or more scale? Do you firmly believe your MSP will have zero front-line support, Amazon-style, no human contact with your customers ever?
I don’t think the technology, the channel, or the market is ready for humanless IT, and I don’t think your customers are prepared to never talk to you. Until it all slowly migrates, you’ll need someone standing by for when the automation fails, and it will fail. Someone has to pick up the phone.
And if Service Leadership’s benchmark data is to be trusted, blaming tier 1 for eroding bottom lines misses where the money actually goes: total salary and tool spend, stacked across every seat. Cutting the cheapest seat first is what people do when they haven’t opened the numbers. Your amps only go to ten, so you’re probably best to just make tier 1 better in tandem with a bunch of work-reducing widgets. Fix the layer that answers the phone, give them the tools, then go look at the expensive seats.
If you want a second set of eyes on which seats AI actually changes in your shop, and what that does to the margin, that’s a conversation I have with owners every week on a call. Bring your headcount and your tool spend and we’ll do the math together.
What does the easy button cost you in sales?
Trust, and trust is the only thing an MSP actually sells. AI in sales is where the “speeds up whatever you already are” rule bites hardest, because a lazy motion at scale is a lazy motion your whole market gets to see.
Here’s one I got hit with this spring. An automated dialer play that felt like the spiritual cousin of “your car warranty is expiring.” No attempt to build a relationship. No research into who we are. No attempt to confirm we’re even a fit. Just swipe the card, turn on the machine, expect riches. And the best part? They mis-targeted us as an MSP. So they burned their lead credits, their ops time, and their team’s energy, and ended up with nothing except annoyed people.
Look, I understand the temptation. Getting in front of prospects is tedious and daunting. Hell, at Empath we’ve had to unload the Brinks truck to do it the right way: trade shows, events, a real sales team doing real work. The easy button is always within arm’s reach, and it isn’t easy. It just moves the cost from your calendar to your reputation. Salesforce’s State of the AI Connected Customer report (seventh edition, 2024, over 16,500 respondents) found that only 42 percent of customers trust businesses to use AI ethically, down from 58 percent in 2023. If your first touch reads as robotic and irrelevant, you’re starting the relationship in a hole your reps will spend a year climbing out of.
Use the tools if you want. Use them to show up more prepared and more specific. Never louder. Research the account before the call and summarize the discovery notes after it. The four phases of the MSP sales process don’t change. The prospecting phase gets a better-informed human in it, which is the only version of AI in sales that ever made anyone money.
What is your team no longer learning?
The relationship muscle, and it goes quiet before anything else does. Have you trained the relationship muscle out of your team? That’s my concern with how fast some shops adopted this, and I’ll admit I’m thinking out loud here more than reporting research.
Running a services business is having strong relationships with your customers. You can’t argue with that. But what happens when you’re never actually communicating with your client? Or worse, with your own team? “My technicians use ChatGPT for all client communication” is a sentence I hear with real pride behind it. What’s the tech not learning while the model writes for them? How to deliver bad news. How to notice the client sounded off and say something about it.
This has happened many times over. We used to remember phone numbers. We used to meet friends places without cell phones. Nobody decided to lose those. The tool made them optional, and optional skills go away.
Here’s where the owner pays for it. If you’re not talking to your clients, you’re relying on ticket surveys and an NPS score to tell you they’re happy, and those mechanisms lie by omission. They measure the tickets that got filed, never the frustration that didn’t. Your employees lose something too: the leadership feedback that levels them up only comes from doing the work in front of someone who can coach it.
At the MSP I ran as its operator, taking it from $2M to $20M in under four years, we had a word for the minimum effort that checks the box: paper whipping. I’ve been guilty of it myself, and I owe you a disclosure here. I’m dyslexic. Writing is hard for me, and I use AI as a grammar tool and proofreader every day. That’s a tool doing a tool’s job. Where I draw the line is sending it in to have the conversation for me, because the conversation is the job, and the shop that grew ten times over did it on the strength of people who could have one.
What are the common mistakes MSP owners make with AI?
Almost all of them come from pointing the tool at the wrong side of the curtain:
- Buying the tool before the process. AI speeds up what’s there. If ticket handling has no standard, you now have a fast way to produce inconsistent work.
- Using AI to cover for a soft-skills gap. That’s management avoidance with a subscription fee. Coach the tech or move the tech. The bot is neither.
- Automating onboarding. The first 90 days decide whether the client stays. A person, on site or on camera, in the first week, is the cheapest retention you will ever buy.
- Cutting tier 1 on the strength of a demo. Run the replacement math with the senior salary included. Then decide.
- Believing the survey. When the humans stop talking, the feedback goes quiet, and quiet gets mistaken for happy.
Every one of these is a people decision wearing a technology costume. Make it as a people decision and the technology part is easy.
The one move to make this week
Keep this if you keep nothing else: AI speeds up whatever your MSP already is, so fix the people problem first and then turn the machine on. Take one client-facing workflow your team already automated and have a human make the next touch on it personally. Then take one internal workflow nobody has automated and hand it to the tool. That’s the whole sorting exercise, one row at a time, and it belongs inside the bigger system for growing your MSP.
Take the first whack at it. If the sort turns up a people problem you’d rather not face alone, that’s what the call is for.
- Should an MSP use AI to write client communication?
- For drafting, grammar, and summarizing, yes. For sending, no. The moment the client reads the same tidy paragraph from every tech, they've learned that a robot answers at your company, and the next step they take is to route around it. Let AI clean up a note. Let a person own the message, and make sure your techs still get the reps that come from writing to a client themselves.
- Is AI going to replace tier 1 at MSPs?
- Not in any shop I've seen, and I've been listening for one. The common tickets will go away, and that's good. Someone still has to pick up the phone when the automation fails, and it fails at the worst possible time. The real margin problem is total salary and tool spend, so make tier 1 better with work-reducing tools and measure whether the tool plus the senior person who runs it actually replaces more than one junior tech.
- What should an MSP automate with AI first?
- The work behind the curtain: ticket triage and routing, documentation cleanup, script writing, summarizing long threads, drafting internal notes, first-pass alert handling. That work has no relationship attached to it, so speeding it up costs you nothing with the client. Automate the touchpoints last, if ever.
- How do I know if AI is hurting my client relationships?
- Look at what you no longer hear. If your only feedback is ticket surveys and an annual NPS score, your feedback mechanisms have gone quiet, and quiet reads as fine right up until the cancellation. Count the live conversations your team had with each client last quarter. If that number is near zero, so is your early warning system.
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