Kevin Petrie
VP of Research at BARC US
Free study
The State of Data and AI Governance
This BARC study, based on 234 global responses, examines how organizations govern production AI, manage emerging risks, and turn policies into enforceable controls across data, models, agents, and workflows.
What this BARC study answers for data & analytics leaders:
- How can organizations turn data and AI governance from a policy exercise into an effective operating model?
- Which AI-related incidents and business consequences are organizations already experiencing?
- Where are the most significant gaps between established data governance and the governance of AI models and agents?
- How can organizations combine human oversight with scalable monitoring, guardrails, auditability, and agent controls?
- Which governance priorities and challenges differ between North America and EMEA?
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Further information
Based on a global survey of 234 data, AI, IT, and business leaders, the report examines governance structures, risks, technologies, and measures for overseeing AI systems and agents. It shows how AI Leaders operationalize governance across the enterprise and addresses the growing need to govern data, models, and AI agents. A regional comparison highlights different challenges in North America and EMEA. Six practical recommendations help organizations scale AI safely and effectively.
As production AI expands faster than many governance programs can mature, this study helps data and analytics leaders identify critical control gaps and establish the operating model, responsibilities, and technical capabilities needed to scale AI safely.
Author(s)
Timm Grosser
Senior Analyst Data & Analytics
Timm Grosser is a Senior Analyst Data & Analytics with a focus on data management.
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Strengthen Your Data and AI Governance!