Technology Usage

MSP tech stacks grew slightly this year, with more providers reporting 16+ apps compared to last year — likely driven by the rise of AI and increasing stack maturity. Having more tools is associated with better performance: top earners are more likely to have 11–20 apps, while average MSPs tend to use fewer than 10.

MSPs with the highest staff utilization (76–99%) tend to use 16-20+ apps, while those with lower utilization rely on fewer solutions, suggesting that more robust, mature tech stacks can boost productivity. However, since higher utilization was linked to higher client churn risk in Chapter 2, MSPs may need to strike a balance between having too many tools for staff to manage vs. investing in ones that drive efficiency and boost staff capacity.

While larger tech stacks may improve performance, they come with challenges: keeping up with new apps, rising solution prices, and changing compliance/security concerns are making managing tech difficult for MSPs — especially as AI tools introduce new learning and training demands (which we’ll explore in this section).

The majority of MSPs now have a documented AI roadmap: 39% are executing their plans, while 36% have yet to do so. However, nearly half feel their adoption of AI has only been “Somewhat effective,” while almost a third feel they are “Very effective.” (Unsurprisingly, those with a documented strategy report more successful adoption).

MSPs who are executing on their AI roadmaps are more likely to report running “Very effective” QBRs and having greater confidence in showing business value to clients. Since reporting is one of the top AI use cases, this may indicate that smart automation makes collecting and sharing key client metrics simpler for MSPs. Other top uses focus on day-to-day MSP operations, especially security and monitoring, operational automation, and internal or client communications.

Today, 62% of MSPs say AI assists with 25% or less of client service delivery, with only a quarter of MSPs delivering 26–50% of services with the help of AI. However, over the next few years, most MSPs expect AI-supported service delivery to move beyond early adoption, with the largest share anticipating usage in the 25–75% range.

Top performers and executives are more likely to predict that 51–75% of services will be AI-assisted in the future, showing AI’s rising influence on operating models and business strategy.

AI service delivery seems to correlate with better overall customer engagement, as MSPs with more AI delivery support now — and higher projected usage in the future — tend to have:

Higher CSAT scores

Highly effective QBRs

High confidence in their ability to deliver value to clients

MSPs with higher staff utilization rates are more likely to report delivering 51–75% of their services with AI assistance.

They also tend to use it more for internal and client communications — suggesting AI may already be helping teams scale and maintain service levels.

A little over half of MSPs expect AI to reshape — rather than eliminate — full-time roles. However, nearly one-fifth say AI has already replaced roles, and a quarter believe it will in the future — showing a clear divide between those who see AI automating work away vs. those who see it augmenting the work staff do.

AI strategy and hiring strategy seem increasingly intertwined. MSPs that report more effective AI adoption are likelier to say AI already has or will replace roles. Those freezing hiring are also more likely to report that AI has or will displace employees. However, MSPs planning to increase hiring in 2026 are also more likely to say AI has already reduced some full-time roles — suggesting that AI may not impact total headcount as much as it shifts the types of roles needed.

The AI divide doesn’t end there. MSPs with the highest utilization rates (76–99%) are more likely to either say that AI replacing employees is unlikely or that it already has — suggesting AI can be used to optimize workloads or reduce certain roles, depending on the MSP’s approach.