Enterprise AI for Tech Leaders: From Strategy to Impact

Participants step into the role of a newly appointed CTO at a tech company struggling to integrate AI into its operations. Drawing on the knowledge, skills, and frameworks they have learned in the course, they design a practical roadmap to guide AI adoption and execution.

Using provided organizational context, including qualitative survey inputs and workflow analyses that highlight operational bottlenecks, they produce a capstone deliverable that includes:

• A categorized workstream analysis identifying high-value opportunity areas

• A focused project brief outlining the initial initiative to pursue and the rationale behind it, including opportunity cost considerations

• A multi-stage plan to improve adoption and traction across teams

• A prioritized backlog of additional AI opportunities beyond the initial initiative

• A draft internal communication, such as a Slack post, announcing and framing the transition

The course concludes with structured presentations demonstrating how AI pilots can be translated into accountable, scalable programs aligned with organizational goals

• Evaluate the strategic and organizational implications of Generative AI for enterprise value creation and competitiveness.

• Assess major Generative AI model types and align them with enterprise use cases across key business functions.

• Identify and address the technical, organizational, and human headwinds that limit AI adoption, including overconfidence and jagged intelligence, non-determinism, vendor lock-in, and employee resistance.

• Analyze workforce and talent implications of AI, including evolving competencies and leadership communication.

• Apply generative and agentic AI to decompose jobs, workflows, and tasks to determine where work can be assisted, augmented, or automated.

• Prioritize AI initiatives and develop a practical enterprise AI roadmap that balances ambition and feasibility.

• Apply course frameworks through a Capstone Project integrating strategy, technology, talent, measurement, and governance.

• Technology executives, including CTOs and CIOs, defining and guiding enterprise AI strategy, investment, and scale 

• Mid- to senior-level technical leaders and enterprise architects, evaluating, designing, and governing AI-enabled systems across the organization 

• IT strategists and digital or AI-transformation leaders, translating AI capabilities into coordinated, enterprise-wide initiatives 

• Technology consultants, advising organizations on enterprise AI strategy, implementation, and readiness