A pricing agent goes rogue. Everyone blames the model. Nobody governed the context it was reasoning over. Most AI governance failures aren't exotic model problems. They're old governance failures that AI makes visible. At Gartner D&A Summit this week, I kept hearing the same debate: data governance vs. AI governance. Two tracks. Two teams. IMO, it's the wrong frame. Gartner's agenda said as much: a unified "Data and AI Governance" track. Not two separate sessions. One. 42% of enterprises already have AI agents in production. The governance frameworks haven't caught up. The disciplines aren't new. Data quality, lineage, access control, lifecycle management. What changed is the surface area. Those practices now need to cover models, prompts, retrieval pipelines, and autonomous agents. One thing. Not three. Charlotte Ledoux and Vivek Dubey make the case for what that actually looks like. Worth the read: https://metadataweekly.substack.com/p/data-governance-vs-ai-governance