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SMBs are talking about AI. Their vendors are pitching AI. Their competitors are experimenting with AI. But most of them still don’t know how to actually run on AI, and that gap is the biggest opportunity the managed services industry has seen in a decade.
Pax8’s new research report, The Agentic Workforce Economy: How Digital Labor Is Reshaping SMB Growth and Redefining the Role of IT Providers, released at Beyond 2026, puts hard numbers behind what many MSPs are already sensing in the field. The findings aren’t just interesting, they’re a blueprint for where to focus right now.
Let’s start with the growth curve. AI services within managed services are growing at 59% annually, compared to just 13% for traditional managed services. That gap isn’t going to close, it’s going to widen. If your service catalog still looks like it did three years ago, you are slowly ceding ground to competitors who are moving faster.
But the more important numbers are the ones tied to your clients’ outcomes, because that’s what makes the case when you’re sitting across from an SMB owner.
Those are not incremental improvements. They’re the kind of numbers that change how a business operates. And the problem is that most SMBs stall somewhere in the middle, they’ve started, they’ve dabbled, and now they’re stuck. They lack the internal expertise, the governance structure, and the time to push further. That’s where you come in.
One of the most striking findings in the report: 84% of SMBs say they would trust an outside technology advisor to guide their AI implementation. That number deserves to sit with you for a moment. These businesses are not resisting AI. They’re not skeptical of outside help. They are actively looking for someone to trust with this.
Add to that:
This isn’t a hard sell. The demand exists. What’s missing is a clear, structured service offering that meets that demand at the right price and with the right deliverables. MSPs who build that offering now will own these client relationships for years, because once you’re embedded in how a business runs on AI, switching costs become enormous.
The Pax8 report highlights three near-term opportunities. They’re practical, they build on work most MSPs are already doing, and they can be scoped and priced without requiring a complete service redesign.
This is the lowest-friction entry point, and arguably the most urgent one. Nearly half of SMBs have no AI-specific security policies, even though 83% of them acknowledge that AI has increased their security risk. That’s not ignorance; that’s a readiness gap. Your clients are already using AI tools (ChatGPT, Copilot, Gemini, and dozens of others) in ways that may be exposing sensitive data, creating compliance liabilities, or bypassing existing IT policies entirely.
An AI governance audit covers:
This is something you can package, price, and deliver relatively quickly. It creates immediate value, surfaces upsell opportunities, and positions you as the authority on a topic your client is worried about but doesn’t know how to address.
Generic AI tools give generic results. The MSPs who will win in this space are the ones who understand their clients’ industries well enough to build (or configure) AI workflows that actually fit how those businesses operate.
Think about the vertical you serve most: healthcare, legal, professional services, construction, retail. Every one of those industries has repetitive, high-volume back-office processes that are ripe for agent automation:
The key is not deploying a generic AI tool and calling it done. It’s mapping the workflow, identifying the right model and tooling for the task, testing against real scenarios, and maintaining it over time. That’s a managed service, not a one-time deployment, and it should be priced accordingly.
The report specifically calls out back-office automation as a high-impact, near-term deployment zone. This makes sense: back-office processes are typically well-defined, high-volume, and consequential enough to justify investment, but not so client-facing that errors create immediate reputational risk.
Common back-office agent use cases that MSPs can deploy and manage:
Each of these represents a billable, ongoing managed service. Not a project, a retainer.
Here’s something the report doesn’t spell out but is visible in the data: SMBs don’t just lack AI tools. They lack the people to run them. Hiring an in-house AI specialist, data engineer, or even a technically sophisticated operations manager is expensive and competitive. The talent market for AI skills is tight, and SMBs can’t compete with enterprise salaries.
MSPs can. When you bring AI capabilities as a managed service, you’re offering the equivalent of fractional AI expertise — access to skills and systems that the client couldn’t afford to build internally. That’s a compelling value proposition that justifies premium pricing, especially when you’re delivering measurable outcomes tied to the profitability gains the research highlights.
The growth rate of AI in managed services is 59% year-over-year. That math compounds quickly. MSPs who enter this space now are building expertise, client references, and repeatable playbooks. MSPs who wait six or twelve months will be trying to catch up against competitors who have already landed the accounts.
More immediately: your existing clients are not waiting. They’re experimenting with AI right now, often without telling you, often without proper controls, and often in ways that create security and compliance risk you’ll eventually be called to fix. Getting ahead of that isn’t just a growth play; it’s good client stewardship.
The AI governance audit isn’t just a new service. It’s a reason to have a proactive conversation with every client on your roster this quarter.
Translating this opportunity into recurring revenue requires a few things most MSPs don’t yet have formalized:
A clear service taxonomy. Which AI services are you offering? What are the deliverables, timelines, and pricing for each? Clients can’t buy what isn’t clearly defined.
Assessment and discovery tooling. You need a way to quickly understand a client’s current AI footprint, maturity level, and readiness for deeper deployment. This becomes the foundation for a roadmap, and a sales conversation.
Vendor partnerships. The AI tooling landscape changes quickly. Aligning with platform partners who have SMB-appropriate solutions, support, and economics is essential for building a scalable practice.
Internal enablement. Your techs and account managers need to be able to speak to AI services confidently. That doesn’t mean everyone needs to be an AI engineer, but everyone who touches a client needs enough literacy to identify opportunities and flag risks.
Outcome tracking. The profitability uplifts in the Pax8 research are compelling. But you need to be able to demonstrate value in your own clients’ terms: time saved, costs reduced, errors eliminated, revenue supported. Build measurement into every engagement from the start.
The Pax8 research makes a clear case: SMBs need AI help, they’re willing to pay for it, and they’re ready to trust an MSP to deliver it. The 59% growth rate for AI services isn’t a prediction; it’s already happening, in the market, right now.
The question isn’t whether AI managed services will become a standard part of the MSP portfolio. It will. The question is whether you’ll be the provider who leads that transformation for your clients, or the one who gets displaced by someone who did.
Start with a governance audit. Pick one vertical you know well and build an agent workflow for it. Look at the back-office processes inside your existing client base and find the first one you can automate. Build the muscle now, when the margin for experimentation is still healthy.
Your clients are ready. The data is clear. The growth is there.
The only thing left is the move.
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