AI Governance for Small Finance Teams

A practical approach for finance leaders who want to adopt AI responsibly: what to automate, what stays human, and how to document the choices in one page rather than forty.

Governance has an image problem in small finance teams. It sounds like a committee, a policy binder and a slower quarter. In practice, the governance a twenty-person finance function needs fits on a single page, and writing it is what allows the team to move faster rather than slower, because nobody has to relitigate the same question every time a new tool appears.

Automate the mechanical, keep the judgment

Draw one line and hold it. Work that is repetitive, rules-based and reviewable can be drafted by a machine. Work that involves an estimate, a judgment, a related-party consideration or a decision that a regulator, lender or auditor may later question stays with a named person.

The one-page policy

Approved tools. Data classes. Human-in-the-loop points. Vendor review — where the data goes, whether it trains a model, retention period. Logging — what was generated, by whom, from what inputs, and who approved it.

Why this is becoming commercial, not just prudent

Customers, auditors and insurers now ask. Enterprise procurement questionnaires include AI handling clauses, audit teams ask how machine-generated support was reviewed, and insurers are beginning to price the answer.

What we commit to

A named accountable owner for AI in finance. A one-page policy your team will actually read. An audit trail that survives review. A quarterly review of tools, data and results.