Start with a risk and value map
We use risk-value-feasibility matrices when evaluating artificial intelligence investments. In this matrix, regulation, data access, and business value appear on the same dashboard.
In discovery workshops with corporate teams, we clarify the scope of the governance framework by creating OKR alignment and data inventory maps.
Document policies and control mechanisms
Role-based access policies, logged event lists and decision logbooks are created for each new module. JWT refresh cycles and audit log formats are linked to ready-made templates for technical teams.
We document runbooks, approval steps, and escalation routes to operationalize responsible AI principles.
Measure and iterate
Serilog-based correlation ID structures and monitoring dashboards help us verify that governance controls are actually working.
In the retrospectives held at the end of each sprint, reporting outputs and risk indicators are reviewed and the checklist is updated.