Operationalizing AI in Organizations

This unit guides learners through the practical steps of turning AI concepts into repeatable, responsible business outcomes by addressing decision design, data infrastructure, governance, project planning, and culture. Students will integrate risk assessment, transparency, experimentation, and change leadership to organize and execute AI initiatives within enterprise contexts.

Learning Objectives

• Analyze organizational decision workflows and disaggregate decisions to identify actionable inputs that improve AI output actionability and alignment with business goals
• Apply governance, data lifecycle, and infrastructure practices—including archiving, deletion policies, and decentralized data management—to design a compliant AI data management plan
• Evaluate alternative development approaches, project planning components, and adoption risks to select and justify an implementation strategy with concrete mitigation measures
• Demonstrate leadership and culture-change methods by producing an AI initiative implementation plan that fosters transparency, experimentation, stakeholder engagement, and an AI-friendly enterprise culture