For more than two decades at FedEx, Rebecca Yeung helped bring robotics, autonomous vehicles, and physical AI into one of the world’s largest logistics networks. Now an advisor to companies including Dexterity, she explains what it takes to move physical AI from a promising pilot into daily operations. Rebecca argues that executives often overestimate AI’s short-term impact while underestimating its long-term potential. She also explains why buying robotics without rethinking the underlying process can simply make an inefficient operation run faster, and why boards need to ask harder questions about ROI. Drawing on FedEx’s work with Aurora, Nuro, Dexterity, and Berkshire Grey, she discusses the demands of safety, integration, and scaling. She shares her outlook on humanoid robots and closes with the philosophy behind her book, What Rules?

Drew DeLong works at the intersection of corporate strategy and national interest, where the boundaries between public policy and business have blurred. With a background spanning key roles at the State Department, FAA and White House, and now leading Kearney’s work in Corporate Statecraft and Geopolitical Dynamics, he brings deep experience from both sides of this evolving relationship.
In this episode, Drew examines three structural shifts converging on leadership teams: the unwinding of forty years of globalization, supply security across increasingly contested chokepoints, and an AI wave outpacing the organizations trying to absorb it. He makes the case that today’s disruption is systemic, not cyclical – and explores what that means for leaders navigating trade barriers, supply-chain risk and geopolitical uncertainty.
The conversation also examines what changes when companies become partners to nation states, why government affairs is becoming a board-level strategic capability, and how leaders can distinguish a deliberate pause from standing still.

Suman’s work sits at the collision point of AI ambition and enterprise reality. From Aetna and Highmark to Merck and Pfizer, he has repeatedly been asked to build new data science and AI capabilities inside complex healthcare organizations, where fragmented data, regulatory pressure, and internal politics shape what can actually scale. In this conversation, he traces how the field evolved from early machine learning and open-source analytics into today’s generative AI wave, and why the hardest part has remained surprisingly consistent: getting people, incentives, leadership, and adoption aligned. His lessons move beyond the usual AI hype, offering a grounded playbook for building durable teams, earning executive cover, designing products people want to use, and turning AI from a spotlight initiative into real organizational muscle.