BARC Topical Survey: The State of Data and AI Governance

AI is already in production across almost every organization—but governance has not kept pace.

In this new BARC research study, 234 data, AI, IT, and business leaders share how their organizations are managing the risks and opportunities of AI. The findings show why governance must evolve from a policy exercise into an operational model for trusted, scalable decision-making.

Key findings

• AI is in production at 97% of organizations surveyed.
• 66% experienced an AI-related incident in the past 12 months.
• Governance failures damaged customer trust or brand reputation at 44% of organizations.
• 69% use either centralized governance or a center-of-excellence model.
• Organizations still focus more on data governance than on governing AI models, applications, and agents.
• The leading Responsible AI priorities are data privacy, security, regulatory compliance, transparency, and accuracy.

What the report explores

The study examines how organizations:

• Build effective data and AI governance structures
• Define accountability across executives, business owners, and technical teams
• Manage AI-related incidents and operational risk
• Extend governance beyond data to models, applications, infrastructure, and agents
• Establish human oversight and controls for AI-driven decisions
• Use governance to scale innovation with greater confidence

For Board, the findings underline the importance of connecting trusted data, transparent assumptions, human accountability, and governed AI to better planning and business decisions.

Download the full BARC research study to understand the current state of data and AI governance—and the practical steps organizations can take next.