AI Project Implementation and Closure

This capstone unit covers the final phases of AI-driven project management, including deployment, release/transition, closing, and post-deployment monitoring while addressing scalability, accessibility, ethics, privacy, and regulatory considerations. Building on prior units, learners synthesize iterative and predictive approaches, prepare compliance and stakeholder plans, and create operational artifacts to support continuous improvement.

Learning Objectives

• Analyze scalability, accessibility, and privacy risks for an AI-driven project and propose measurable mitigation strategies aligned with applicable regulations.
• Evaluate ethical implications and regulatory requirements for first-time AI implementation and justify a stakeholder communication and compliance plan.
• Apply iterative development (sprint and cycle) and monitoring & controlling techniques to produce a project schedule, quality checkpoints, and a risk response plan for AI deployment.
• Demonstrate deployment, release/transition, and closing processes by creating a release checklist, post-deployment metrics, and a hybrid predictive-continuous improvement plan for ongoing operations.