AI Strategy Implementation and Governance

This unit focuses on operationalizing enterprise AI and data strategies by translating technical design into deployable, governed solutions. Students will learn to assess costs and infrastructure, apply Agile/DevOps and vendor-management practices, manage risks and ethics, and produce stakeholder-ready plans for sustainable deployment and monitoring.

Learning Objectives

• Analyze and prioritize potential AI and generative-AI use cases by evaluating business value, technical feasibility, infrastructure and compute costs, and risk to produce a ranked justification for implementation.
• Design a comprehensive deployment and maintenance plan that applies Agile and DevOps principles, incorporates retrieval-augmented generation where appropriate, defines monitoring and management mechanisms, and specifies vendor-management strategies and contingency plans.
• Evaluate ethical, legal, and societal implications of foundation-model and generative-AI deployments and recommend concrete governance, mitigation, and compliance measures tailored to organizational context.
• Demonstrate the ability to prepare stakeholder-ready deliverables—including a project pitch, hiring and budget recommendations, advanced project-management timeline, and resource/tooling plan—that support executive decision-making and implementation readiness.