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.

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.

On this special season four recap episode, host Christian Terwiesch reflects on his conversations with Lara Liss, Chief Privacy and Data Trust Officer at GE Healthcare; Alfredo Colas, Chief Data and AI Officer at Procter & Gamble; Radha Plumb, Vice President of AI Transformation at IBM; and Dr. Pari Panari, Chair of Radiology at Penn Medicine. Across sectors, their discussions converge on several common themes: integrating AI responsibly, keeping humans in (or on) the loop, and leveraging AI as a collaborator or amplifier rather than a replacement for human capabilities. You’ll also hear Christian’s key takeaways on governance, workflow redesign, and the democratization of creativity, offering practical insights for any business leaders thinking about AI adoption in their own organizations.

Episode Highlights:

1:51 - Lara talks about the importance of ethical AI implementation, and how that requires bringing together diverse perspectives from within your organization.

4:00 - Alfredo explains how AI isn’t simply automating routine work at Procter & Gamble, but actually taking part in creative problem solving.

6:29 - Radha shares her twist on the “human in the loop” trope when it comes to determining which tasks are best delegated to AI and which are best left to people.

9:14 - Pari provides her prognosis about how AI will affect the future of healthcare delivery, and why those entering the field should familiarize themselves with the technology.

Can AI read X-rays better than humans? Will AI make radiologists’ jobs easier or more complicated? And how could a team of AI agents one day work alongside doctors to improve patient care? Those are just a few of the thought-provoking questions at the center of this episode of Where AI Works. 

In this final interview of season four, host Christian Terweisch sits down with Dr. Pari Pandharipande, the Chair of Radiology at Penn Medicine, to explore how artificial intelligence is reshaping the world of medical imaging. Whether we’re talking about X-rays, CT scans, or MRIs, radiology has always relied on expert human interpretation. Now, AI is changing the workflow by boosting efficiency and helping hospitals tackle one of the biggest challenges in healthcare: a growing labor shortage. Dr. Pandharipande also walks us through the day-to-day work of a radiologist, explaining how images are analyzed, reports are generated, and decisions are made. She shares how AI is already shortening MRI exam times, detecting strokes faster, and providing decision-support tools that augment human expertise. 

Episode Highlights:

7:36 - Pari explains how technology, and AI in particular, is being used to speed up and streamline the process of interpreting medical imaging.

16:19 - Pari tackles the tough question of whether or not AI could make work harder for radiologists by taking care of the easy cases and leaving the harder ones for humans.

18:56 - Pari discusses the balancing act that comes with trying to understand and embrace AI while still being somewhat skeptical of its capabilities.

It’s an ambitious objective for any organization: saving $4.5 billion a year — not by cutting staff, but by redesigning the way people and AI work together. It’s an even more noteworthy goal when the organization in question is one of the most storied technology companies in the world.

On this episode of Where AI Works, host Christian Terwiesch speaks with Radha Plumb, the Vice-President of AI-First Transformation at IBM, to explore how the iconic company is driving practical AI transformation on a massive scale. IBM has long been known for innovation, but the conversation has shifted from moonshot experiments to measurable productivity gains thanks to AI-powered workflow redesign. Radha explains why the road to AI advantage starts with strong data foundations, integrated governance, and a clear focus on human-AI collaboration — or as she puts it: “Eliminate. Simplify. Automate.” From HR and procurement to finance and IT, IBM’s internal “Client Zero” strategy reveals where the next wave of automation will hit — and how organizations can scale quickly while maintaining trust and accountability.

Episode Highlights:

7:07 - Radha explains why she prefers the expression “human on the loop” to the more traditional “human in the loop” when discussing how AI can augment workers.

14:33 - Radha discusses IBM’s “Client-Zero” approach, and how the AI initiatives it’s implementing internally serve as a preview of what’s coming for other organizations.

20:57 - Radha shares why it’s important for companies of all sizes to have governance guardrails in place before deploying new AI tools.

It’s one of the world’s most iconic consumer goods companies, founded when America was still in the midst of the Industrial Revolution. Now, more than a century later, it’s on the frontlines of another massive transformation in the way we work thanks to the rise of artificial intelligence.

On this episode of Where AI Works, host Christian Terwiesch is joined by Alfredo Colas, the Chief Data and AI Officer at Procter & Gamble, to explore how the 188 year old company is reinventing itself yet again. With nearly three decades at P&G, Alfredo shares his unique perspective on embedding AI into innovation, from product ideation to smarter supply chains, while keeping humans firmly in the loop. You’ll hear how the company leverages AI to supercharge creativity — turning individual ideas into high-performing concepts — and how AI helps democratize knowledge, making decades of consumer insights instantly accessible to employees across the company. Their conversation also highlights the importance of human judgment in final decision-making, the evolving nature of work, and how AI can eliminate routine tasks to let employees focus on higher-value, creative problem solving.

Episode Highlights:

6:13 - Alfredo shares how AI is being used to enhance rather than replace P&G’s “secret formula” for gaining consumer insights about its products.

10:20 - Alfredo explains how P&G is leveraging AI to boost personal employee productivity, improve quality, and democratize knowledge.

18:23 - Alfredo discusses which aspects of work he foresees changing the most as a result of AI implementation. 

It’s an industry facing a wide variety of challenges; soaring costs, timely care, and employee burnout. But there’s growing evidence that AI can help make the healthcare sector safer, faster, and more human, all at once.

On this premiere episode of season four of Where AI Works, host Christian Terwiesch sits down with Lara Liss, the Chief Privacy and Data Trust Officer at GE HealthCare, to explore how AI is transforming healthcare delivery from the inside out. From smarter imaging and diagnostics to predictive tools that help entire hospital systems run more efficiently, AI’s potential to relieve pressure on the industry is enormous. But as Lara explains, with that power also comes responsibility to embed ethical AI principles at every stage of product development — ensuring transparency, safety, and clinical oversight. She also discusses what it takes to build trust in AI and why it’s critical to keep human practitioners in the loop to ensure patient care remains grounded in expertise and not just algorithms.

Episode Highlights:

6:06 - Lara lays out how AI has the potential to address many of the challenges currently facing the healthcare sector.

8:04 - Lara shares the first step all companies should take if they’re just getting started with AI implementation.

14:03 - Lara explains how GE Healthcare is using AI to augment the abilities of medical professionals rather than replace them.