Navigating compliance in generative AI launches
Frameworks and checklists to responsibly introduce generative AI into regulated environments without slowing innovation.
Generative AI unlocks new experiences, but regulated industries need robust guardrails across data, models, and human oversight.
Key takeaways
- Map compliance requirements to every stage of the AI lifecycle
- Embed human review for high-risk decisions
- Document governance policies and incident response plans
Assess risk and readiness
Review data residency, retention, and sensitivity requirements before selecting AI tooling.
Work with legal and compliance teams to define acceptable use cases and failure modes.
Design ethical guardrails
Implement policy-as-code for access controls, logging, and monitoring.
Establish human-in-the-loop processes where model outputs impact customers or finances.
Operationalise governance
Track model performance, drift, and user feedback; review metrics in recurring governance forums.
Update policies and models as regulations evolve, documenting every change for auditors.