The AI Lifecycle Framework

Artificial intelligence systems pass through multiple stages from initial planning and data collection to deployment, operation, monitoring, and eventual retirement. Each stage introduces unique governance responsibilities, risks, controls, and accountability requirements. In this lesson, learners explore the AI lifecycle framework and examine how governance must be integrated throughout the entire lifecycle rather than applied only during development. The lesson introduces governance checkpoints, accountability structures, lifecycle documentation, and review mechanisms that support regulatory compliance, audit readiness, and trustworthy AI operations. Understanding lifecycle governance provides the foundation for assessing AI systems consistently and effectively across their entire operational journey.