Framework
A structured set of policies, processes, and tools guiding the governance, development, deployment, and monitoring of AI systems.
Definition
The organizational backbone for consistent AI practice—defining approval workflows, risk-assessment templates, ethical-check gates, performance metrics, and incident responses. A robust framework scales across business units and adapts to changing regulations. Key activities include periodic framework reviews, training programs, and dashboard-based KPI tracking aligned to strategic objectives.
Real-World Example
A multinational consumer-goods company implements an AI governance framework comprising: (1) project intake forms with risk-scoring; (2) mandatory bias and privacy impact assessments; (3) IT-security integration; (4) quarterly AI-performance and ethics dashboards; and (5) an AI-incident post-mortem process—ensuring every AI project follows a consistent, auditable path.
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