Learn directly from Jean Leah
What you'll learn
Identify the right work for agents
Distinguish work best handled by humans, deterministic automation, AI assistance, or agentic execution.
Apply the Agentic Fit Test
Evaluate a workflow across ambiguity, variability, tool use, iteration, economic value, and consequence of failure.
Make a clear investment decision
Ability to classify an opportunity as Automate, Assist, Agentify, Keep Human, or Kill and explain why.
Why this topic matters
Companies are rushing to deploy AI agents before determining whether the work actually requires one. This results in expensive pilots, unnecessary complexity, weak ROI, and avoidable risk. This lesson gives leaders a practical way to evaluate the work first so they can invest in agents where they create real value and choose simpler approaches.
You'll learn from
Jean Leah
PhD Engineer & AI Executive (Dell, Lowe’s, Texas A&M)
I’m a PhD engineer and AI executive who has spent my career turning complex technology into practical business outcomes. I’ve led enterprise AI and data science work at Dell and Lowe’s and now work across AI, deep-tech commercialization, and technology investment. My teaching focuses on helping leaders make better decisions about where AI belongs, how human and agentic work should be designed, and what it takes to move from experiment to governed execution.