AI Lifecycle Overview

This lesson introduces the complete AI lifecycle, providing a structured framework for understanding how artificial intelligence systems are designed, developed, deployed, monitored, and maintained. Learners explore the seven major stages of the AI lifecycle, including data collection, model development, validation, deployment, monitoring, retraining, and retirement. The lesson emphasizes that AI is not a one-time project but an ongoing operational process requiring governance, accountability, and continuous improvement. Understanding the AI lifecycle helps learners recognize how organizations build trustworthy, secure, and effective AI systems in real-world environments.