AI Margins and MSP Growth: Dr. Gleb Tsipursky on Passing Savings vs. Competing Away Profit

Dave Sobel (0:00)

My guest today is Dr. Gleb Tsipursky. He runs a future of work consultancy called Disaster Avoidance Experts, and he has a new book out from Georgetown University Press, The Psychology of AI Adoption at Work. The argument is that AI projects stall for human reasons rather than technical ones.

I reviewed the whole thing, and notes included, and I want to spend our time on whether it holds the size of company most of my audience usually runs. Gleb, welcome to the show.

Gleb Tsipursky (0:30)

Thank you, Dave. I appreciate you being on the show. I appreciate you inviting me.

Dave Sobel (0:34)

Well, let's dive right in. Your smallest case study is a firm with just 100 staff or so. And to be fair, the words MSP and managed services don't appear anywhere in your book.

So I've got listeners with 11 employees, like no HR, no CIO, no learning and development budget, and a technician shortage. So when you think about it in that perspective, what in your book is focused and helps and survives for that group?

Gleb Tsipursky (1:01)

Yeah, I just did a training for an eight-people company. So very much in the MSP space, and they outsourced their IT. So they have an MSP as one of the ways that they manage things. They don't have enough people for an IT budget.

So the same principles very much apply to folks who are an eight-people company and people who are an 100-people company and people who are an 1,000-people company. When you get beyond 5,000, that's more like enterprise level, and that's kind of when there's more difficulty, and when at least some of the things from my book would need to be tweaked, and I do have case studies of the larger companies. But for everything that I talk about, you can apply to quite small companies that get MSP services.

Dave Sobel (1:52)

Okay. Now, in the book, the company that I thought looked the most like my audience is ImageQuest, right? So there are 50 some people, IT and security.

So in that case, he doesn't get a case study, he gets some quotes, and what the owner there describes is a 45-minute optional monthly lunch, where everyone shows what they're doing. It's not necessarily profiles, there are five stages. Is that enough at a 50-person company? What do you recommend for those smaller sizes?

Gleb Tsipursky (2:21)

Sure, so he described what he was doing afterward, so after the initial adoption. But this for MSP service providers, where there are your 50-people company or a five-people company, what you really need to do is start with a training, a thorough training on AI adoption.

Because, as you and I chatted before the beginning of the episode, MSP service providers are not necessarily expert in AI. And here's the reason.

They are experts in technical tools and the technology. So they're experts in, let's say, Microsoft products. They're experts in those various forms of technical support, technological support. But AI tools are not necessarily the grassroots ground space of IT folks, because they use natural language programming. So natural language programming is very different than the kind of technical work that MSP service providers are used to. So you build tools within AI using natural language programming. And so people need to be trained on that. People who are in MSP need to be trained on how to use natural language programming. The mindset is very different than working with typical technology tools. And that's some of the reasons why AI adoption projects fail. There's 95% of AI pilots fail to scale. They fail to show return on investment according to a recent MIT study. And that's a big concern. And of course, a number of those failures have happened with MSP support as well as with internal IT support.

And the failures happen because of human psychology and because MSPs are not used to providing the kind of support from natural language services that AI tools require and they're not used to the kind of resistance with which AI tools are met.

Dave Sobel (4:21)

Okay, I'm following and tracking. Now, one of the things I really wanted to dive into is I loved your Chapter 13 about measuring and optimizing. That's an area that oftentimes we talk about in MSPs because we're quite good at measuring and look for a lot of metrics. Now, the chapter gave guidance to track cost reductions and correlate to operating costs and margins.

So, I'm following along. But one of the things I was curious about is never once names a cost that the organization pays, things like licenses or per se or token spend or consultant fees, the non-billable training hour. And it doesn't necessarily latch to a formula to put them in. And if I'm thinking about myself as, say, a 20-person MSP doing things like $30 a seat a month plus fees, plus 40 hours of non-billable training, walk me through the arithmetic on both sides that I should be measuring and optimizing.