7 week online course — 0.5 credits
This course is an applied, leadership-oriented introduction to modern AI, focused on helping leaders evaluate and deploy a range of AI approaches, from generative AI assistance, such as workflow automation, to structured, goal-directed systems (often referred to as agentic AI). It is designed as the primary AI experience in the Master’s in Technology Leadership program for students headed toward senior leadership roles.
Students shall move from AI and generative AI fundamentals to practical workflow automation using no/low-code tools, learning how to turn ad hoc prompts into repeatable, auditable processes. The middle of the course introduces agentic systems (LLM "brains" + tools + memory + orchestration) alongside a 4-stage adoption ladder—Assist → Augment → Advise → Autonomous—and an AI risk pyramid to decide where different AI approaches are appropriate and where AI should not be deployed.
The primary objective of the course is to equip leaders with a strategic framework for deciding where, when, and to what extent agentic AI supports business goals, rather than assuming its use. We conclude with organizational integration: designing human + AI teams, evolving roles and governance, and applying principles of responsible AI. We assume a near future in which organizations are built from hybrid teams of humans and AI agents, and focus on what it means to lead and design in that context. Throughout, students build and refine an AI Strategy and Deployment Roadmap for their organization, culminating in a group capstone where they present their roadmap and a simple, aligned demo.
Experiential Leadership Labs ("Vibe Coding"): These are guided, no/low-code prototyping sessions included not to train students as engineers, but to provide the "technical intuition" leaders need to assess feasibility, estimate complexity, and effectively manage engineering teams building these systems. The course emphasizes diagnosis and judgment.