People-Led, Tech-Powered: Walmart’s AI Job Shift
Where AI Works: Conversations at the Intersection of AI and IndustryShow Notes
It’s a question that looms large for any business leader these days, but the stakes are even higher for those that manage massive workforces: as AI transforms the workplace, what happens to jobs and the people doing them? On this episode of Where AI Works, host Matthew Bidwell speaks with Donna Morris, the Chief People Officer at Walmart, about what it means to introduce AI across one of the largest workforces on the planet; more than 2.1 million associates around the world. Morris explains the company’s “people-led, tech-powered” approach, where AI is used to augment employees rather than replace them. She also discusses the emergence of new roles like AI agent-builders , and explores the skills that matter most in an AI-driven workplace. While technical expertise is important, Morris argues that adaptability, communication, curiosity, and interpersonal skills will define the most successful employees in the years ahead. For leaders navigating this rapid change, the takeaway is simple: invest in people, build new skills, and be sure to bring your workers along for the ride.
Episode Highlights:
6:03 - Donna outlines how AI will reshape the workforce: some jobs will evolve, some will emerge—like AI “agent builders”—and some will disappear, making reskilling essential.
10:24 - Donna discusses the skills that matter most in an AI-driven workplace, emphasizing communication, adaptability, learning agility, and interpersonal skills.
22:30 - Morris discusses the human side of AI transformation, stressing the importance of transparency and communication as companies navigate uncertainty about how work will change.
More from Where AI Works: Conversations at the Intersection of AI and Industry
What happens when AI stops being a tool and starts reshaping how decisions get made? Who has the judgment and responsibility to double-check the work that AI is doing? And what actually separates companies that are scaling AI from those that are just experimenting?
If AI removes traditional constraints on execution, what becomes the limiting factor? AI can now generate, summarize, and analyze, but it still can’t judge. And as many business leaders are learning, that can cause a new wrinkle in workflows.
How is AI transforming product development inside large-scale organizations? What does it look like when teams move from Product Requirements Documents to rapid prototyping? And how are roles, workflows, and decision-making changing in our increasingly AI-first world? On this episode of Where AI Works, host Matthew Bidwell sits down with Paul Stathacopoulos, Vice President of Product for Focus Categories and International Cross Border Trade at eBay, to find out how AI is reshaping the way products are built and delivered inside one of the world’s largest online marketplaces. Together, they explore how eBay is using AI across three key areas: improving customer-facing experiences, unlocking insights from massive datasets, and fundamentally transforming product development workflows. They also discuss the shift from traditional PRDs to rapid, AI-generated prototypes, and how “vibe coding” is enabling teams to test ideas with customers in a period of days instead of months. Finally, they unpack how AI is blurring roles across product, design, and engineering, and why adopting an AI-first mindset is critical to staying competitive in a rapidly evolving landscape.
The way we think about jobs is changing. As artificial intelligence reshapes how work gets done, traditional roles and titles are giving way to something more fluid: a skills-based economy. But while organizations are moving quickly to redefine what they need, workers and educators are still catching up, creating a growing gap between the skills people claim to have and the capabilities employers truly value.
AI isn’t here to replace us, it’s here to challenge the way we think, work, and decide. But the true test isn’t in implementing the technology itself — it lies in how humans choose to integrate AI into their work, take responsibility for its outputs, and reimagine systems to deliver meaningful, measurable results.