The OneTrust 2026 AI-Ready Governance Survey Report
AI adoption is creating a governance gap.
Organizations are moving AI into business functions while employees continue to adopt new tools and agents. Governance has advanced alongside that adoption, but not at the same pace or consistency organizations need.
More than half of business leaders say AI governance is integrated into the AI lifecycle, but 47% describe their programs as reactive, fragmented, slow, or manual. Just 17% say governance is embedded by design.
New research highlights where AI governance is advancing and where disconnected execution is creating risk.
AI adoption has moved beyond isolated pilots for most organizations. Nearly three-fourths (74%) report departmental report departmental or scaled AI adoption, and 52% use AI across multiple business functions or have embedded it into business processes and operations.
Governance has also moved forward. But only 5% say coordination and accountability are clear across the AI lifecycle.
Agent Adoption Is Exposing the Next Governance Gap
AI agents provide the survey’s clearest comparison between adoption and governance readiness.
87% of respondents say their organizations encourage agent use, while only 47% say that use is supported by clear governance, oversight, and controls. Another 40% encourage use while governance and controls continue to develop.
Organizations are opening access to agents while they continue to define the rules that surround agent activity.
Agent Encouragement is Outpacing Clear Governance
Shadow AI and Coordination Gaps Are Defining Operating Risks
Shadow AI is a defining visibility challenge for enterprise AI governance. Most organizations can see their approved AI. Far fewer can see everything else.
Nearly half (48%) report clear visibility into sanctioned and unsanctioned AI use. Another 46% have good visibility into approved AI, but limited visibility into employee-led or unsanctioned use.
That gap creates operating risk. One-third experienced employees using unapproved AI tools because approved options or processes were not available quickly enough. Thirty-one percent identified use cases for review after they were already in use.
Organizations are doing the work, but ownership, context, controls, and evidence do not always move consistently from intake through deployment and ongoing use.
Organizations can see their approved AI
Shadow AI creates the operating risk
AI incidents are no longer edge cases. They’ve moved from ‘if’ to ‘when.’
Eighty-six percent of organizations experienced at least one AI-related incident during the past year. Among those respondents, 99% took meaningful action.
Nearly half (45%) implemented formal AI review and approval processes, while 43% expanded monitoring or governance controls.
The response is moving toward stronger governance capacity—not simply slowing down AI.
AI governance is starting to move into operations, but a significant gap remains. Organizations have built governance activities and controls, yet those efforts are not consistently connected across business functions, third parties, and agents as AI scales.
See where AI is being used and how that use changes over time.
Keep reviews moving at the pace of adoption.
Carry governance decisions into active AI workflows.
Give teams clear ownership across the AI lifecycle.
The full 2026 AI-Ready Governance Survey Report provides the detail needed to benchmark your organization and plan the next phase of governance.
Explore the full findings on:
This report is designed for CISOs and other senior leaders responsible for security, risk, privacy, data, AI, and enterprise governance.
OneTrust and Sapio Research surveyed 1,200 senior business decision-makers in June and July 2026 across Australia, Canada, France, Germany, Singapore, Spain, the United Kingdom, and the United States.
The sample included equal representation from CPO, CDO, CISO, and CMO audiences. All respondents worked at organizations with at least $100 million in annual revenue.
Organizations have established many AI governance activities, but those activities are not yet consistently connected across teams, systems, vendors, and lifecycle stages.
Shadow AI refers to AI tools and agents adopted by employees or teams outside formal approval and oversight processes. It is the AI equivalent of shadow IT.
The risk is not the tools themselves. It is the lack of visibility, controls, and accountability around how they are used. When security and risk teams cannot see unapproved AI activity, they cannot assess exposure, enforce policy, or respond to incidents.
AI-ready governance means having the visibility, processes, controls, and accountability structures across the entire business to manage AI at the pace and scale of the business.
It requires continuous monitoring of AI use across functions, vendors, and agents, along with the ability to adapt as adoption changes.
AI agents introduce specific governance challenges because they can act autonomously, initiate processes, and interact with third-party systems in ways that are harder to monitor than traditional AI use.
Governance programs need clear policies for agent use, approval workflows before deployment, and ongoing monitoring after deployment. The gap between agent adoption at 87% and clear governance and controls at 47% reflects how quickly organizations are opening access without first defining the rules that should surround it.
