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AI Adoption Hurdles
I recently came across a research study that I believe perfectly encapsulates the current AI opportunity for MSPs. The survey was conducted by Bredin SMB Pulse, a market research firm that polls SMB participants across a wide range of topics. The goal of this particular survey was to understand the most significant hurdles that these businesses face while attempting to implement AI into their business. Where there is pain, there is opportunity, which is why studies like this grab my attention. Here are the results
What I found most interesting about these results was not just the responses but also how much they differed between different ranges of company size. It has become obvious that not everyone is looking at this opportunity the same way and it may even be possible that SMBs have a varying definition of what “AI adoption” even means based on their level of maturity.
There were three responses that jumped out at me as clear MSP opportunities, and they all happened to be leading responses as it relates to the 20-99 or 100-500 employee range. These are as follows:
- Our IT infrastructure is or was outdated
- Training end-users is difficult and time consuming
- Security and compliance are difficult
To get a second opinion, I reached out to one of the only entrepreneurs I know that is truly operating at the intersection of AI and MSP. That’s Jimmy Hatzell, Founder of Hatz AI. We went on to chat about this very research study, as well the general state of the AI opportunity as it related to MSPs.
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Who is driving AI adoption?
One of the first things I was curious to learn was who is actually driving the bus when it comes to AI adoption among SMBs? Are company CEOs holding corporate pep-rallies to get their teams excited about this new tech, or is the status quo quietly getting disrupted from the ground up? Or are MSPs stepping in and leading from outside of the organization? Hatzell claims, “It’s coming from all three—company leadership, end-users, and MSPs—but if the MSP isn’t participating in that conversation, they’re not going to be involved at all. Every analyst out there, every report, shows that spending is heading toward AI. If MSPs don’t take the lead, someone else will step in”
I think he is spot on in this observation as this could get away from MSPs quite quickly if they let it. He went on to explain, “AI adoption isn’t just top-down like ERP systems or big cloud rollouts. It’s also bottom-up. Employees start using AI tools in unexpected ways, gaining efficiency along the way. Studies have shown early adopters using AI at their discretion see up to 30% efficiency gains, and it’s only increasing as more research comes out. Employees find ways to use AI in ways leadership didn’t anticipate, which creates a disconnect and adds to the hesitation from the top.” This game of tug-of-war between end-users and leadership is precisely why MSPs need to act as a voice of reason and lay the groundwork for a successful adoption.
What roadblocks do SMBs face?
While the research provided a wide range of examples of the roadblocks that SMBs face, I asked Jimmy to share a few of the issues that he’s seen while working with MSPs that are leading this charge. He went on to say “The number one issue is that businesses are scared of what they don’t know. Shadow AI is already a massive problem—employees are signing up for free AI tools, sharing accounts, and sometimes even dumping sensitive data into personal systems. That’s a compliance nightmare waiting to happen, and SMBs are hesitant because they don’t know how to manage those risks.”
There is no disputing this as we’ve all likely dealt with this first hand and possibly even taken a few shortcuts ourselves that may have put personal or company data at risk. The problem here is the reason to avoid AI adoption as an organization is also the same reason to embrace it. “Organizations often say, ‘We’re not ready. We need to get our security better, or our infrastructure better.’ That hesitation leads to employees taking AI adoption into their own hands, creating more risks and making compliance even harder to enforce.” This is like when the “cool parents” in high school let the kids have parties at their house. We only later realized that it wasn’t because they were “cool” at all. It was because they knew we would do it anyway, and they wanted to be able to monitor and control the situation.
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How can MSPs fuel adoption?
Jimmy and I went on to discuss the three major pain points that I highlighted earlier and how they map to opportunities that MSPs can generate right now:
Installing Guardrails
As we got deeper into the weeds of the conversation, I started to realize what Jimmy is already hyper-aware of, which is that there is really no such thing as AI-ready when it comes to SMBs. As he put it, “The reality is, the quickest way you can get to a safe adoption of AI is to provide approved guidance and basic training. You don’t need to spend 6 to 12 months trying to make everything perfect. Give people a safe way to consume it now, or they’ll just keep doing it on their own without any guardrails in place.”
“Especially in industries like healthcare or finance, where compliance is critical, you need to have guarantees. Clients need to check that box on their audits with confidence. MSPs play a key role in providing that assurance across the board.” I think what MSPs must come to realize is that whether they are providing executive-level vCISO services or not, they could get tied up in these compliance issues if it gets messy. These guardrails can be just as much a protection for you than they can be for the end customer.
End-User Training
While guardrails can prevent misuse, they are really a last line of defense. Ideally these employees consciously understand the do’s and don’ts as it relates to AI-use on company devices and they comply accordingly. This all starts with training. “It’s not about restricting employees—it’s about enabling them safely. MSPs should provide users with the right tools and the knowledge to use them effectively. This prevents shadow AI issues, like people dumping sensitive data into unapproved tools, and instead channels their enthusiasm in a compliant and productive way.”
The good thing is that the adoption curve is not very steep when it comes to chat-based generative AI tools. Hatzell claims that, “It takes about 10 hours of interacting with AI tools like ChatGPT or CoPilot for people to grasp the full range of capabilities. Once they hit that point, they start to subconsciously think of use cases and efficiencies. MSPs can accelerate that learning curve with structured training programs.”
Modernizing Infrastructure
Once these guardrails are in place and users are trained up on how to use AI within their corporate boundaries, now MSPs can focus on setting the table for AI adoption at a larger scale. This is what I believe to be the true opportunity here, because it is more aligned with an MSP’s existing skillset. We’re not talking about building and training LLMs. We are talking about deploying modernized infrastructure that puts full adoption within arm’s reach. Hatzell says, “Today, MSPs are managing 25 different software applications for SMBs, but we’re moving toward a future where AI agents might reduce that to six. The challenge for MSPs is to stop chasing every new shiny tool and focus on maturing the infrastructure with scalable, reliable solutions that prepare clients for an AI-driven environment.”
“MSPs have already transitioned into consultative roles—acting as technology advisors offering CIO and security services. The next step is helping clients integrate AI securely into their infrastructure. Whether that means upgrading servers, implementing better compliance controls, or optimizing current tech stacks, MSPs are positioned to lead this shift.” If nothing, think of this as a talking point in your next QBR. The SMBs who choose not (or fail) to embrace this evolution could face an extinction level event as it becomes impossible to compete. In this case, being on the right side of history starts today.
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What type of MSPs are capitalizing?
I went on to ask Jimmy where how much self-awareness exists among MSPs as it relates to the opportunity in front of them. He recalled, “We’ve seen a bias toward forward-thinking MSPs reaching out to learn about AI. These are the people raising their hands and saying, ‘I just want to get started. I want to work on this now.’ They’re not waiting for a perfect time because they know things are evolving so quickly”
“I know every MSP has a million projects—PSA migrations, Intune rollouts, and so on—but kicking the AI can down the road is a big risk. If you’re thinking only about the next two months, you’ll miss where the industry is heading in two or three years. Think about how security matured; AI is moving at 50x that speed. We used to say in the early days of cybersecurity, ‘If you’re not involved with your customer’s security, someone else will be.’ It’s the same with AI. MSPs have a choice: Start working on it now and be part of the conversation, or risk being left behind as others take the lead.”
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