The study, conducted with Osterman Research and based on 750 enterprise leaders, shows that visibility gaps around unsanctioned AI use have nearly tripled, rising from 6.3% in 2025 to 17.6% in 2026. For AI agents, the blind spot is even larger: 21.1% of organisations cannot determine whether employees are using unsanctioned tools to create agents.
At the same time, AI agents have rapidly embedded themselves into daily operations. 46.9% of employees now rely on AI agents weekly or daily, and 88.4% of organisations experienced at least one agent‑related security incident in the past year.
Chris Shaw, Channel Director for UK and Ireland at AvePoint, said the findings highlight a widening gap between customer ambition and operational readiness. “Almost 9 in 10 organisations have experienced an AI‑related breach in the last year… that really shows you the scope of the problem,” he said.
Customers Are Overconfident and Actively Seeking Partner Support
Despite widespread incidents, organisations remain highly confident in their AI security posture. 82.7% say they are “very” or “extremely” confident in preventing unauthorised AI‑related data access, yet up to 72% of those confident organisations still suffered an incident in the past 12 months.
For MSPs, this confidence gap is becoming a clear commercial driver. Customers believe they are ready for AI; the data shows they urgently need help.
The report identifies several areas where partners are already being pulled in:
AI readiness assessments
Data clean‑up and classification
Governance framework design
Agent oversight and policy enforcement
AI FinOps reporting tied to business outcomes
AI Rollouts Delayed – Extending Pre‑Deployment Partner Engagement
Governance gaps are also slowing AI programmes. Nearly 9 in 10 organisations delayed both agentic and generative AI deployments by around six months, citing data security and management concerns.
For MSPs, this is extending pre‑deployment consulting windows and increasing demand for structured data remediation, policy design, and ongoing governance services.
AI‑generated content is adding further pressure: 35.5% of enterprise data is now created by AI assistants, expected to reach 42.1% within a year. With 84.1% of organisations managing at least one petabyte of data, partners are being asked to modernise legacy data, reduce sprawl, and ensure AI systems don’t act on low‑quality inputs.
Governance Tools and Agent Management Platforms Are Becoming New Revenue Streams
The report shows organisations are now prioritising investments in AI training data security and third‑party governance tools — including emerging AI Agent Management Platforms (AMPs) — to regain control.
AvePoint CTO John Peluso said: “Trust in AI requires operational foundations: visibility, enforceable governance, and the ability to audit and correct outcomes when something goes wrong.”
For MSPs, AMPs represent a new category of managed service:
Continuous agent monitoring
Policy‑aligned action validation
Automated remediation
Governance‑as‑a‑service
AI FinOps dashboards for customers
Trust Layer Will Define Partner Success
AvePoint’s research concludes that AI value is no longer constrained by model capability, but by whether organisations – and their partners – have built a trust layer that makes AI outcomes safe, auditable, and scalable.
For MSPs, this trust layer is rapidly becoming a core commercial opportunity. Customers need governance, visibility, and control, and they increasingly expect partners to deliver it.
The full report is available at:https://www.avepoint.com/shifthappens/reports/artificial-intelligence-report-2026
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