Course Description: Innovating with Generative AI for Leaders and Managers

As many of you know, this is my final semester at Princeton. This summer, I’ll be teaching an intensive in person course at Harvard tentatively titled “Innovating with Generative AI for Leaders and Managers.”:

• Schedule: July 14–31, 2025
• Structure: 12 sessions (3 hours each)
• Format: In-person, intensive program
• Enrollment: Limited to 36 students
• Target Audience: Early-career leaders and managers, primarily with private sector focus

Below is my preliminary draft of the course description and learning objectives.

I welcome your feedback and suggestions, please leave comments below.

I am looking forward to this it will be a lot of fun!

Draft Course Description

Generative AI (GAI) is a General Purpose Technology — a versatile innovation with broad economic impact and extensive spillover effects, similar to historical transformations like electricity and computing. The full potential of GAI will only be realized through comprehensive innovation in work processes and management practices.

This course equips current and future leaders with practical knowledge and strategic insights for effectively innovating with Generative AI at three levels: as an individual contributor, as a team manager, and as an organizational leader.

Through interactive discussions, real-world case studies, and hands-on exercises, you’ll explore foundational concepts, examine diverse business applications, and evaluate the strategic, ethical, and operational implications of GAI deployment. A core component involves developing a no-code Generative AI application that addresses a specific business challenge or opportunity, either individually or collaboratively.

Ultimately, this course prepares you to reimagine processes and organizations in the GAI era — enabling you to drive transformation across individual workflows, team dynamics, and enterprise-wide systems.

Learning Goals

By the end of the course, students will be able to:

• Understand GAI fundamentals, capabilities, limitations, and emerging trends including agentic applications.
• Identify strategic opportunities and potential disruptions that GAI creates at individual, team, and organizational levels.
• Analyze how GAI transforms workflows, team coordination, and organizational structures through diverse real-world case studies.
• Build a GAI application using a no-code platform to address a specific problem/challenge.
• Develop governance frameworks and ethical practices for responsible GAI deployment across different organizational contexts.
• Formulate multi-level strategies for innovating with GAI, from personal productivity to enterprise-wide transformation.
• Communicate effectively about GAI implementation to diverse stakeholders, from technical teams to executive leadership.