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?

On this special season five recap episode, host Matthew Bidwell looks back at his interviews with James Crowley, global products industry practices chair at Accenture, and Eric Bradlow, the vice dean of AI and analytics at Wharton; Donna Morris, the Chief People Officer at Walmart; Paul Stathacopoulos, Vice President of Product for Focus Categories and International Cross Border Trade at eBay; and Ritcha Ranjan, Senior Vice President of Product at Expedia Group. Across these conversations, a clear pattern emerges: AI is moving from isolated pilots into the core of how organizations operate, forcing a shift in how decisions get made, in how work is structured, and in the very skills needed by employees and employers alike.

Episode Highlights:
1:39 - James encourages business leaders to think about the skills they need for their organizations rather than focusing on roles and resumes.

2:40 - Eric explains why he cares less about what employees or students know now, and more about how quickly they can learn new things.

4:38 - Donna discusses the ‘softer skills’ that have historically been overlooked by employers that are now more important thanks to AI.

5:53 - Paul shares his take on the importance of keeping humans in the loop to maintain oversight on the output of AI systems and agents.

9:02 - Ritcha answers the all-important question at the center of this season; which skills are becoming more valuable for employers in the age of AI.

10:03 - Matthew summarizes his key takeaways for business leaders based on everything that was discussed in this season of the pod.

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.

On this episode of Where AI Works, host Matthew Bidwell is joined by Ritcha Ranjan, Senior Vice President of Product at Expedia Group, to explore what happens as AI takes on more and more tasks traditionally handled by humans, forcing employees to decide when it’s actually doing things well. After all, when AI can produce endless ideas and recommendations, the real skill becomes knowing which ones to trust. Ritcha believes skepticism isn’t a bug, it’s a requirement. She explains why building effective AI systems means designing for human judgment: knowing when to keep people in the loop, how to validate outputs, and how to create feedback systems that continuously improve performance. She also shares how her teams at Expedia are experimenting with always-on AI systems, reworking product development, and preparing employees for a world where deep expertise, curiosity, and judgment matter more than ever.

Episode Highlights:
6:25 - Ritcha shares the top three misconceptions some business leaders still have about AI.

9:11 - Ritcha outlines the three-stage evolution most organizations go through when adopting AI — from “help me” to “create for me” to “run this for me.”

12:18 - Ritcha breaks down the risks/rewards of AI implementation, and how the equation changes the further down the road your company gets.

20:06 - Ritcha discusses the skills needed to thrive in an AI-forward environment, and explains how productivity doesn’t come from more output but from better judgment.

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.

Episode Highlights:

4:51 - Paul explains how eBay is harnessing AI to move beyond the traditional product requirements documents to “vibe coding” rapid prototypes in dramatically shorter time-frames.

10:03 - Paul shares how AI agents work alongside humans to ensure compliance, governance, and quality, illustrating that AI isn’t a set-it-and-forget-it solution.

17:51 - Paul discusses how Bay has redesigned the selling workflow from scratch using AI, leading to one of the most impactful test cases in company history.

21:46 - Paul emphasizes the importance of embedding AI into workflows early, rather than as an afterthought, to build skill and muscle memory across teams.

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.

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.

On this season premiere episode of Where AI Works, host Matthew Bidwell is joined by James Crowley, Global Products Industry Practices Chair at Accenture, and Eric Bradlow, Vice Dean of AI and Analytics at Wharton, to unpack the findings of the Wharton Accenture Skills Index. Drawing on analysis of millions of worker profiles and job postings, they explore how AI is accelerating demand for specialized expertise, domain knowledge, and judgment-driven work, while making generalized skills less important on their own. Their conversation also explores what this shift means for business leaders, educators, and employees alike, as AI transforms both how we work and how we learn. It turns out success may depend less on what you know today — and more on how quickly you can build the skills you’ll need tomorrow.

Episode Highlights:

6:22 - James explains how the Wharton Accenture Skills Index was built using an analysis of 150 million worker profiles and 100 million job postings.

13:25 - Eric reflects on why AI should be viewed as a learning accelerator, and why employers should invest in how quickly people can learn rather than in what they already know.

23:25 - James lays out why business leaders need to come up with a “taxonomy” for the skills they need, the skills their employees already have, and the ones they’ll need in the future.