AI Project Deployment and Governance

This capstone unit guides students through the full lifecycle activities required to launch, govern, and close AI-driven projects, emphasizing deployment, iterative development, monitoring, and transition. Students will address practical considerations such as scalability, accessibility, ethics, privacy, regulatory compliance, and hybrid/predictive management approaches to prepare AI solutions for operational use.

Learning Objectives

• Analyze project lifecycle phases (initiating, iterative development/sprints, monitoring and controlling, release/transition, deployment, and closing) by mapping tasks, roles, and deliverables for an AI-driven project
• Apply monitoring, controlling, and deployment techniques by producing a project control plan, sprint cycle schedule, and a release/transition checklist for an AI implementation
• Demonstrate responsible AI governance by creating an ethics and privacy impact assessment, an accessibility plan, and a regulatory compliance checklist aligned with applicable standards
• Evaluate trade-offs between predictive, iterative, and hybrid project management approaches and recommend a scalable, maintainable implementation strategy for a first-time AI deployment