A 2026 survey of 100 middle-market finance leaders found that 66% consider human oversight critical to deployment, and only 14% say they fully trust AI outputs even after review. That's not hesitation, it's discipline. The CFOs asking the hardest questions about their AI outputs are often the ones running the most sophisticated deployments, because they've learned that scaling agentic AI safely means governing it deliberately, not just adopting it fast.

We pulled research from Maximor, Wolters Kluwer, PwC, EY, and IBM to map the four governance architectures leading finance teams are actually using to move AI from pilot to trusted production.

Inside the guide:

• The four governance frameworks enterprise finance teams rely on, and when each one fits
• How to set autonomous-action thresholds that are jurisdiction-aware and reviewed on a real cadence
• What auditors now expect from your AI decision logs and how to get ahead of it