Start with the decision
A useful AI initiative begins with a banking decision or workflow: who owns it, what outcome should improve, and what evidence will show that it works. A convincing demonstration can still leave data permissions, customer treatment, human review, monitoring and support unresolved.
For your next pilot, ask the sponsor to write one sentence naming the decision, intended outcome, affected population and accountable owner. Then ask operations and control teams to explain how an exception reaches the right person and how the service can be paused.
Three questions for your next leadership meeting
- What are we authorizing? Separate recommendations, human decisions and autonomous actions. Define the data and tools each use case may access.
- What will we be able to demonstrate? Trace a sample output to source information, system version, approvals and resulting action.
- Who responds when the operating boundary changes? Assign reassessment and stop authority for material changes in data, vendors, models, prompts, tools or use.
A practical next step
Choose one active use case and complete a governance review with its business, technology, data, risk and compliance owners. Record unresolved conditions with owners and dates.
Resources for the discussion
AI Governance Operating Model for Banking connects roles, lifecycle gates, monitoring and evidence.
AI Governance Operating Model Roadmap provides a phased plan and readiness gates.
SR 26-2 Model Risk Management explains the updated guidance and why applicability matters.
AI Credit Decisioning: A Beginner’s Guide helps teams map the decision, data, model, customer and governance paths.