Artificial intelligence has the potential to super-charge innovation. But without robust data governance, your AI initiatives risk failure. Poor data quality, IP leaks, privacy violations, regulatory breaches, and embedded bias can derail projects before they begin. To address these threats, data leaders must first modernize foundational governance policies, rules, and standards across their data lifecycle. 

Only then can they extend governance to confront new and evolving AI-specific risks—hallucinations, toxicity, and rogue agent behavior among them. By proactively adapting governance practices, organizations can maintain trust, ensure compliance, and lay the foundation for scalable, responsible innovation. Join Kevin Petrie, VP of Research at BARC, to learn how to bolster your data governance program in support of safe, successful AI innovation. 

What You’ll Learn: 

-The foundational governance updates needed for using agentic AI 

-How to identify and mitigate data risks 

-How to extend governance from data to AI models and agents