Generative AI has compressed the distance between experiment and production. Teams can prototype in days what once took quarters — but without guardrails, the same speed introduces reputational, legal, and operational risk.
Effective AI governance for mid-market organisations is not a heavyweight compliance programme. It is a set of clear accountabilities: who approves use cases, how data is classified, where models may run, and how outputs are reviewed before they reach customers or regulators.
Start with a short list of permitted use cases, require lightweight impact assessments for new ones, and embed review into existing product and security rhythms. Velocity and accountability are not opposites — they are prerequisites for sustainable AI adoption.