For all the noise around AI skills shortages and security risks, new data suggests the real blocker to adoption is far less headline-grabbing, and far more operational.
Research from AvePoint and Omdia shows that 51% of managed service providers (MSPs) now see governance and compliance as the biggest barrier to AI adoption, overtaking concerns around security, value realisation and technical expertise.
It’s a finding that cuts through much of the current AI narrative. The tools are here, the investment is happening — but organisations are struggling to deploy AI in a way that is controlled, compliant and scalable.
A Market Moving Faster than its Foundations
The timing matters. Omdia forecasts a $276 billion global partner opportunity tied to AI services by 2030, placing MSPs at the centre of one of the fastest-growing areas in enterprise technology.
Yet the same research highlights a clear execution gap. While 94% of MSPs say they are investing in AI readiness, fewer than half have reached the level of maturity required to deliver AI-ready environments at scale.
In other words, the ambition is there — the operational reality is lagging behind.
“Many of us who work directly with end-customers already have a sense of why AI adoption is stalled in certain regions and sectors,” said Chris Shaw, Director of Channel UK&I at AvePoint. “This data validates what we’re seeing across the UK and Europe: governance and compliance are the real challenges. AI tools are increasingly powerful, but that capability won’t translate into ROI without the right guardrails in place.”
The Hidden Complexity of Scale
What’s becoming clear is that AI adoption is no longer primarily a technology problem — it’s an operational one.
For MSPs, the complexity lies in managing multiple customer environments at once. Each tenant introduces its own configurations, policies and compliance requirements, making standardisation difficult and automation harder to achieve.
Around 40% of providers cite this multi-tenant complexity as the main barrier to scaling automation, effectively slowing down the delivery of AI services even where demand exists.
As one MSP executive put it in the research:
“We could build automations for every client — but we’d have to do it hundreds of times.”
The Push Toward Platform Thinking
This growing complexity is accelerating a shift already underway in the channel: away from fragmented point solutions and towards integrated platforms.
Nearly half of MSPs (49%) now say they want a fully integrated platform, while 91% believe backup and recovery must be unified to support effective governance.
The direction of travel is clear. As AI becomes embedded across workflows, the ability to manage data, enforce policy and maintain visibility across environments is becoming non-negotiable.
“Governance has become the primary barrier preventing customer AI adoption,” said Scott Sacket, SVP, Global Partner Strategy at AvePoint. “MSPs need unified platforms that standardise governance across multi-tenant environments and turn manual processes into repeatable services. Those that get this right will be best placed to capture the opportunity.”
Compliance as a Growth Engine
Despite the challenges, the outlook for MSPs is far from negative. In fact, the research points to governance itself becoming a key revenue driver.
Omdia expects compliance services to grow by 21% in 2026, fuelled by regulatory pressure and increasing demand for continuous compliance.
This reframes the issue. Governance is no longer just a hurdle to overcome — it is becoming a core service layer in the AI economy.
For those looking to explore the findings in more detail, the full report — The Road to AI Readiness: Unlocking the MSP AI Opportunity Through Governance — is available here:
https://www.avepoint.com/
From Capability to Control
The broader message is a shift in how AI readiness is defined.
Success is no longer about access to tools or even technical capability. It is about control — the ability to manage data, enforce policies, and deliver consistent outcomes across increasingly complex environments.
For MSPs, that means building services around:
- Standardised governance frameworks
- Centralised, multi-tenant visibility
- Integrated data protection and compliance
As AI moves beyond experimentation and into core business processes, the organisations that succeed will not be those with the most advanced tools — but those that can deploy them safely, consistently and at scale.
In that sense, governance isn’t slowing AI down. It’s defining who gets to move forward.
