Nerdio’s recently released report shows that while MSPs are embracing AI, many are struggling to translate adoption into measurable business results.
The 2026 State of the MSP Business Report is based on a survey of over 150 MSP decision-makers that manage Microsoft 365 (M365) and Azure across their customer bases.
MSP AI adoption outpaces measurable productivity gains
While many MSPs are struggling to find measurable business results, the way providers manage Microsoft environments across customers has become a key differentiator in their ability to scale operations, deliver consistent service, and prepare for an AI-driven future.
The report found that 32% of MSPs have adopted AI tools for their operations, with another 46% piloting or planning to adopt them within the next 12 months. However, just 12% can point to measurable productivity gains.
“AI didn’t create the divide in the MSP industry. It’s making the one that was already there easier to see,” said Will Ominsky, VP & GM, MSP Business at Nerdio. “The difference isn’t whether an MSP has access to AI tools. It’s whether the business has the operational foundation to put them to work consistently for customers across increasingly complex environments.”
“MSPs that build a more consistent, repeatable way to deliver service will be best positioned to turn AI from an experiment into a measurable business advantage,” Ominsky added.
Meanwhile, just 14% of MSPs currently operate a revenue-generating AI service line, and 17% say customers are asking about Microsoft Copilot or other AI tools, but they are not yet ready to respond.
Governance has also been a challenge, with only 14% of providers consistently applying a documented AI governance framework across every customer using Copilot or other AI tools.
Microsoft management complexity creates scaling challenges
The report identifies operating models – how a provider manages M365 and Azure across its customer base – as the clearest predictor of most outcomes in the dataset, ahead of firm size, headcount, and tool count.
The MSPs are sorted into three groups: those relying on native Microsoft tools and manual processes, those using community and open-source tools, and those using commercial multi-tenant management platforms.
Commercial-platform MSPs can onboard a new user while touching three or fewer separate portals, consoles, or tools 52% of the time, compared with 22% of native-tool MSPs.
When an insurer or auditor asks for evidence, 77% of commercial-platform MSPs can produce an audit-ready M365 assessment the same day, compared with 53% of native-tool MSPs.
Further, six in 10 MSPs say Microsoft management complexity is growing faster than their ability to scale, and existing teams are absorbing most of the growth, with 29% of MSPs growing their customer base over the past 12 months without adding proportional engineering headcount, compared with 17% who staffed in step with growth.
Additionally, 29% of MSPs lost technicians to workload-related burnout in the past 12 months, and concern that burnout is a real risk rises from 34% among MSPs running under 200 users per engineer to 54% among those running more than 200.
What MSPs should prioritize to improve AI results
For MSPs, the findings suggest that adopting AI tools alone is unlikely to deliver meaningful productivity improvements without addressing existing operational inefficiencies.
Providers should evaluate whether their current Microsoft 365 and Azure management processes support consistent onboarding, reporting, and governance across customers before expanding AI deployments.
MSPs should also establish measurable productivity benchmarks, including technician time savings and service delivery efficiency, to determine whether AI investments are producing results.
With only 14% of surveyed providers operating revenue-generating AI service lines, those that can demonstrate tangible improvements may be better positioned to translate internal AI adoption into customer-facing services.