Detailed guide to the AI project lifecycle. It describes five distinct phases: initiation, proof of concept, pilot, full deployment, and ongoing monitoring and optimization. The guide emphasizes the importance of aligning AI projects with business objectives, emphasizing data governance, and establishing a clear roadmap for success. The text also highlights best practices for managing the lifecycle, such as maintaining stakeholder engagement, ensuring clear communication, starting small and scaling, and prioritizing iteration and improvement.