https://cohostpodcasting.com <![CDATA[Where AI Works: Conversations at the Intersection of AI and Industry ]]> en 508eff4a-8ec8-41c8-8926-7d0bc20a74d1 Tue, 11 Mar 2025 14:22:55 -0400 Wed, 13 May 2026 18:10:36 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ <![CDATA[Where AI Works: Conversations at the Intersection of AI and Industry ]]> https://files.cohostpodcasting.com/quill-file-prod/e6f8ee87-47be-4a8e-a2cd-6c7f13dff165/shows/508eff4a-8ec8-41c8-8926-7d0bc20a74d1/cover-art/original_f990ef61aa413ffa86f5feec5f03aa59.png https://knowledge.wharton.upenn.edu/where-ai-works-show/ episodic false https://feeds.cohostpodcasting.com/U15PuDPy podcasts@jaraudio.com <![CDATA[Judgment is the New Bottleneck]]> 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. 

]]> Thu, 07 May 2026 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 26:59 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. 

]]> 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. 

]]> false full 4 5 <![CDATA[From PRDs to Prototypes: How AI Is Reinventing Product Development]]> 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.

]]> Thu, 23 Apr 2026 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 29:59 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.

]]> 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.

]]> false full 3 5 <![CDATA[People-Led, Tech-Powered: Walmart’s AI Job Shift]]> 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.

]]> Thu, 09 Apr 2026 05:00:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 26:16 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.

]]> 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.

]]> false full 2 5 <![CDATA[How AI is Reshaping Skills, Hiring, and Education]]> 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.

]]> Thu, 26 Mar 2026 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 33:37 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.

]]> 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.

]]> false full 1 5 <![CDATA[Host's Cut: Reflections on Season Four]]> 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.

]]> Thu, 12 Mar 2026 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 11:00 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.

]]> 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.

]]> false full 5 4 <![CDATA[Where AI Meets Medicine: Rethinking Radiology Workflows]]> 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.

]]> Thu, 26 Feb 2026 04:01:00 -0500 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 22:42 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.

]]> 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.

]]> false full 4 4 <![CDATA[Eliminate, Simplify, Automate: IBM’s Blueprint for AI Transformation]]> 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.

]]> Thu, 12 Feb 2026 04:01:00 -0500 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 26:05 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 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.

]]> false full 3 4 <![CDATA[From Strategy to Shelf: AI in the Consumer Goods Sector]]> 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. 

]]> Thu, 29 Jan 2026 04:01:00 -0500 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 23:26 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 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. 

]]> false full 2 4 <![CDATA[AI in Healthcare: Balancing Innovation and Trust]]> 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.

]]> Thu, 15 Jan 2026 04:01:00 -0500 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 22:29 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.

]]> 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.

]]> false full 1 4 <![CDATA[Beyond the Hype: Peter Cappelli on Where AI Boosts Productivity, and Where It Just Doesn’t]]> This week, we’re doing something different. Instead of our usual episodes, we’re sharing a special conversation featuring “Where AI Works” season 3 host Peter Cappelli on the podcast “Using AI at Work.” It’s a timely, unfiltered look at how companies are actually trying, and often failing, to implement AI.


In this interview, Peter brings his decades of research at Wharton to dismantle the biggest myths leaders believe about AI adoption:

  • Why boards are obsessed with headcount reductions, and why that’s the wrong metric
  • The real reasons only ~5% of companies are meaningfully implementing AI
  • What executives get wrong when they chase “off-the-shelf” AI solutions
  • How job redesign, not job elimination, is where the true productivity gains come from
  • The surprising truth about employee cooperation: guaranteeing jobs may actually speed up AI progress


He also breaks down two real-world case studies, including Ricoh’s attempt to automate insurance paperwork and a manufacturing company’s AI-driven quality control system, revealing what actually works, what doesn’t, and why AI projects fail long before the technology does.


If you’re a leader trying to separate hype from reality, or if you want to understand how AI reshapes work without erasing workers, this conversation is essential listening.

]]> Thu, 20 Nov 2025 04:01:00 -0500 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 1:00:58 This week, we’re doing something different. Instead of our usual episodes, we’re sharing a special conversation featuring “Where AI Works” season 3 host Peter Cappelli on the podcast “Using AI at Work.” It’s a timely, unfiltered look at how companies are actually trying, and often failing, to implement AI.


In this interview, Peter brings his decades of research at Wharton to dismantle the biggest myths leaders believe about AI adoption:

  • Why boards are obsessed with headcount reductions, and why that’s the wrong metric
  • The real reasons only ~5% of companies are meaningfully implementing AI
  • What executives get wrong when they chase “off-the-shelf” AI solutions
  • How job redesign, not job elimination, is where the true productivity gains come from
  • The surprising truth about employee cooperation: guaranteeing jobs may actually speed up AI progress


He also breaks down two real-world case studies, including Ricoh’s attempt to automate insurance paperwork and a manufacturing company’s AI-driven quality control system, revealing what actually works, what doesn’t, and why AI projects fail long before the technology does.


If you’re a leader trying to separate hype from reality, or if you want to understand how AI reshapes work without erasing workers, this conversation is essential listening.

]]> This week, we’re doing something different. Instead of our usual episodes, we’re sharing a special conversation featuring “Where AI Works” season 3 host Peter Cappelli on the podcast “Using AI at Work.” It’s a timely, unfiltered look at how companies are actually trying, and often failing, to implement AI.


In this interview, Peter brings his decades of research at Wharton to dismantle the biggest myths leaders believe about AI adoption:

  • Why boards are obsessed with headcount reductions, and why that’s the wrong metric
  • The real reasons only ~5% of companies are meaningfully implementing AI
  • What executives get wrong when they chase “off-the-shelf” AI solutions
  • How job redesign, not job elimination, is where the true productivity gains come from
  • The surprising truth about employee cooperation: guaranteeing jobs may actually speed up AI progress


He also breaks down two real-world case studies, including Ricoh’s attempt to automate insurance paperwork and a manufacturing company’s AI-driven quality control system, revealing what actually works, what doesn’t, and why AI projects fail long before the technology does.


If you’re a leader trying to separate hype from reality, or if you want to understand how AI reshapes work without erasing workers, this conversation is essential listening.

]]> false bonus 3 <![CDATA[Host's Cut: Reflections on Season Three]]> AI isn’t just a technology story — it’s an organizational one. From talent and transformation to data and decision-making, this season of Where AI Works uncovers how top executives are building the structures and the mindsets that make AI work at scale.


On this special recap and review episode, host Peter Cappelli looks back at the key takeaways from his conversations with Karalee Close, the Global Lead for Talent & Organization at Accenture; Vivian Sun, the Senior Director of Data & AI, Enterprise Architecture and IT Transformation at Jabil Incorporated; Greg Ulrich, the Chief AI & Data Officer at Mastercard; and Sohaib Perwaiz, the Group Business Engagement Lead at RBC Borealis. In each conversation, you’ll hear a first-hand perspective on how they’re guiding their companies through this transformational time, balancing innovation with governance, and experimentation with measurable business value. You’ll also get more of Peter’s expert analysis, including two important observations for any business leaders grappling with AI implementation within their own organizations.

 


Episode Highlights:

2:47 - Karalee explains how implementing AI requires a deep understanding of the roles and tasks within an organization, in order to re-skill employees as needed.


4:39 - Vivian talks about the first AI use-case within her organization, and how it served as a way to gain attention and support from executives.


6:42 - Greg discusses how AI implementation at MasterCard required not just alignment from internal stakeholders, but buy-in from other external partners as well.


8:36 - Sohaib shares RBC’s perspective on the importance of keeping “humans-in-the-loop”, especially as it relates to client relationships.

]]> Thu, 30 Oct 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 10:14 AI isn’t just a technology story — it’s an organizational one. From talent and transformation to data and decision-making, this season of Where AI Works uncovers how top executives are building the structures and the mindsets that make AI work at scale.


On this special recap and review episode, host Peter Cappelli looks back at the key takeaways from his conversations with Karalee Close, the Global Lead for Talent & Organization at Accenture; Vivian Sun, the Senior Director of Data & AI, Enterprise Architecture and IT Transformation at Jabil Incorporated; Greg Ulrich, the Chief AI & Data Officer at Mastercard; and Sohaib Perwaiz, the Group Business Engagement Lead at RBC Borealis. In each conversation, you’ll hear a first-hand perspective on how they’re guiding their companies through this transformational time, balancing innovation with governance, and experimentation with measurable business value. You’ll also get more of Peter’s expert analysis, including two important observations for any business leaders grappling with AI implementation within their own organizations.

 


Episode Highlights:

2:47 - Karalee explains how implementing AI requires a deep understanding of the roles and tasks within an organization, in order to re-skill employees as needed.


4:39 - Vivian talks about the first AI use-case within her organization, and how it served as a way to gain attention and support from executives.


6:42 - Greg discusses how AI implementation at MasterCard required not just alignment from internal stakeholders, but buy-in from other external partners as well.


8:36 - Sohaib shares RBC’s perspective on the importance of keeping “humans-in-the-loop”, especially as it relates to client relationships.

]]> AI isn’t just a technology story — it’s an organizational one. From talent and transformation to data and decision-making, this season of Where AI Works uncovers how top executives are building the structures and the mindsets that make AI work at scale.


On this special recap and review episode, host Peter Cappelli looks back at the key takeaways from his conversations with Karalee Close, the Global Lead for Talent & Organization at Accenture; Vivian Sun, the Senior Director of Data & AI, Enterprise Architecture and IT Transformation at Jabil Incorporated; Greg Ulrich, the Chief AI & Data Officer at Mastercard; and Sohaib Perwaiz, the Group Business Engagement Lead at RBC Borealis. In each conversation, you’ll hear a first-hand perspective on how they’re guiding their companies through this transformational time, balancing innovation with governance, and experimentation with measurable business value. You’ll also get more of Peter’s expert analysis, including two important observations for any business leaders grappling with AI implementation within their own organizations.

 


Episode Highlights:

2:47 - Karalee explains how implementing AI requires a deep understanding of the roles and tasks within an organization, in order to re-skill employees as needed.


4:39 - Vivian talks about the first AI use-case within her organization, and how it served as a way to gain attention and support from executives.


6:42 - Greg discusses how AI implementation at MasterCard required not just alignment from internal stakeholders, but buy-in from other external partners as well.


8:36 - Sohaib shares RBC’s perspective on the importance of keeping “humans-in-the-loop”, especially as it relates to client relationships.

]]> false full 5 3 <![CDATA[From Call Volume to Client Value: AI in the Banking Sector]]> What happens when the volume and complexity of client needs outpace the capacity of even the world’s biggest banks? And how can AI move beyond efficiency tools to actually enrich client conversations, deepen relationships, and reimagine frontline service?


On this episode of Where AI Works, host Peter Cappelli sits down with Sohaib Perwaiz, the Senior Director of Business Advisory at RBC Borealis — the Royal Bank of Canada’s enterprise AI solution development hub and center of excellence. Their conversation explores how AI is being applied across the enterprise, including inside the bank’s advice center, where generative AI is helping thousands of human advisors reduce call times, surface insights from vast pools of transaction data, and transform routine problem-solving into personalized financial guidance. This episode also unpacks the organizational realities of scaling AI in a highly regulated industry: how to design solutions that empower rather than replace employees, how to align technology with real business pain points, and why shifting from “shiny object” experimentation to value-driven implementation is critical for banks and other companies as they navigate the AI era.

 


Episode Highlights:


4:49 - Sohaib describes how generative AI is being applied within RBC’s call center to improve both productivity and the client experience.


11:21 - Sohaib explains why he thinks augmenting human agents with AI adds more value than replacing them with AI-powered chatbots entirely.


17:24 - Sohaib lays out how RBC is using machine learning to drive greater client retention in the mortgage aspect of its business.

]]> Thu, 16 Oct 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 23:35 What happens when the volume and complexity of client needs outpace the capacity of even the world’s biggest banks? And how can AI move beyond efficiency tools to actually enrich client conversations, deepen relationships, and reimagine frontline service?


On this episode of Where AI Works, host Peter Cappelli sits down with Sohaib Perwaiz, the Senior Director of Business Advisory at RBC Borealis — the Royal Bank of Canada’s enterprise AI solution development hub and center of excellence. Their conversation explores how AI is being applied across the enterprise, including inside the bank’s advice center, where generative AI is helping thousands of human advisors reduce call times, surface insights from vast pools of transaction data, and transform routine problem-solving into personalized financial guidance. This episode also unpacks the organizational realities of scaling AI in a highly regulated industry: how to design solutions that empower rather than replace employees, how to align technology with real business pain points, and why shifting from “shiny object” experimentation to value-driven implementation is critical for banks and other companies as they navigate the AI era.

 


Episode Highlights:


4:49 - Sohaib describes how generative AI is being applied within RBC’s call center to improve both productivity and the client experience.


11:21 - Sohaib explains why he thinks augmenting human agents with AI adds more value than replacing them with AI-powered chatbots entirely.


17:24 - Sohaib lays out how RBC is using machine learning to drive greater client retention in the mortgage aspect of its business.

]]> What happens when the volume and complexity of client needs outpace the capacity of even the world’s biggest banks? And how can AI move beyond efficiency tools to actually enrich client conversations, deepen relationships, and reimagine frontline service?


On this episode of Where AI Works, host Peter Cappelli sits down with Sohaib Perwaiz, the Senior Director of Business Advisory at RBC Borealis — the Royal Bank of Canada’s enterprise AI solution development hub and center of excellence. Their conversation explores how AI is being applied across the enterprise, including inside the bank’s advice center, where generative AI is helping thousands of human advisors reduce call times, surface insights from vast pools of transaction data, and transform routine problem-solving into personalized financial guidance. This episode also unpacks the organizational realities of scaling AI in a highly regulated industry: how to design solutions that empower rather than replace employees, how to align technology with real business pain points, and why shifting from “shiny object” experimentation to value-driven implementation is critical for banks and other companies as they navigate the AI era.

 


Episode Highlights:


4:49 - Sohaib describes how generative AI is being applied within RBC’s call center to improve both productivity and the client experience.


11:21 - Sohaib explains why he thinks augmenting human agents with AI adds more value than replacing them with AI-powered chatbots entirely.


17:24 - Sohaib lays out how RBC is using machine learning to drive greater client retention in the mortgage aspect of its business.

]]> false full 4 3 <![CDATA[Trust and Transactions: How Mastercard Is Doing AI Differently]]> What happens when AI isn’t just an add-on or a nice-to-have, but becomes part of the backbone of global commerce? And how can agentic AI be implemented successfully in an ecosystem that’s historically treated bots as malicious or fraudulent actors?


On this episode of Where AI Works, host Peter Cappelli sits down with Greg Ulrich, the Chief AI and Data Officer at Mastercard, to explore how one of the world’s leading payment technology companies is embedding AI across its enterprise. From internal copilots and onboarding tools to its groundbreaking “Agent Pay” initiative, the company’s goal is to both improve productivity and to create secure, trusted systems that allow AI agents to carry out transactions on behalf of consumers and businesses alike. Their conversation also goes beyond the technology to highlight the leadership, cultural, and organizational shifts required to scale AI in such a highly regulated industry, and why cross-enterprise collaboration is as critical as the algorithms themselves. 

 


Episode Highlights:

5:44 - Greg lays out how online shopping and search are being augmented with agentic AI to give customers greater flexibility without compromising security.


11:04 - Greg explains how Mastercard separates legitimate transactions from fraudulent ones, and the increasing role of AI in making that determination.


16:45 - Greg discusses the variety of agentic systems working within Mastercard and how they work together to provide a seamless experience for the end-user.

]]> Thu, 02 Oct 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 21:30 What happens when AI isn’t just an add-on or a nice-to-have, but becomes part of the backbone of global commerce? And how can agentic AI be implemented successfully in an ecosystem that’s historically treated bots as malicious or fraudulent actors?


On this episode of Where AI Works, host Peter Cappelli sits down with Greg Ulrich, the Chief AI and Data Officer at Mastercard, to explore how one of the world’s leading payment technology companies is embedding AI across its enterprise. From internal copilots and onboarding tools to its groundbreaking “Agent Pay” initiative, the company’s goal is to both improve productivity and to create secure, trusted systems that allow AI agents to carry out transactions on behalf of consumers and businesses alike. Their conversation also goes beyond the technology to highlight the leadership, cultural, and organizational shifts required to scale AI in such a highly regulated industry, and why cross-enterprise collaboration is as critical as the algorithms themselves. 

 


Episode Highlights:

5:44 - Greg lays out how online shopping and search are being augmented with agentic AI to give customers greater flexibility without compromising security.


11:04 - Greg explains how Mastercard separates legitimate transactions from fraudulent ones, and the increasing role of AI in making that determination.


16:45 - Greg discusses the variety of agentic systems working within Mastercard and how they work together to provide a seamless experience for the end-user.

]]> What happens when AI isn’t just an add-on or a nice-to-have, but becomes part of the backbone of global commerce? And how can agentic AI be implemented successfully in an ecosystem that’s historically treated bots as malicious or fraudulent actors?


On this episode of Where AI Works, host Peter Cappelli sits down with Greg Ulrich, the Chief AI and Data Officer at Mastercard, to explore how one of the world’s leading payment technology companies is embedding AI across its enterprise. From internal copilots and onboarding tools to its groundbreaking “Agent Pay” initiative, the company’s goal is to both improve productivity and to create secure, trusted systems that allow AI agents to carry out transactions on behalf of consumers and businesses alike. Their conversation also goes beyond the technology to highlight the leadership, cultural, and organizational shifts required to scale AI in such a highly regulated industry, and why cross-enterprise collaboration is as critical as the algorithms themselves. 

 


Episode Highlights:

5:44 - Greg lays out how online shopping and search are being augmented with agentic AI to give customers greater flexibility without compromising security.


11:04 - Greg explains how Mastercard separates legitimate transactions from fraudulent ones, and the increasing role of AI in making that determination.


16:45 - Greg discusses the variety of agentic systems working within Mastercard and how they work together to provide a seamless experience for the end-user.

]]> false full 3 3 <![CDATA[Start Small, Think Big: Making AI Stick]]> AI transformation isn’t about flashy tools — it’s about strategic wins that build momentum and deliver real business value.


On this episode of Where AI Works, host Peter Cappelli is joined by Vivian Sun, the Senior Director of Data & AI, Enterprise Architecture, and IT Transformation at Jabil Incorporated, one of the world’s largest and most quietly influential contract manufacturers. Sun shares how her company scaled AI across its global operations — not by chasing hype, but by starting with tangible use cases that delivered measurable impact. As you’ll hear, Jabil’s journey began with AI-powered computer vision, replacing tedious and error-prone visual inspections. From there, it moved into machine learning for color calibration in manufacturing — transforming decades of tacit worker knowledge into predictive models. They then layered in generative AI to enhance compliance with trade regulations, using AI as both a decision-making assistant and a validation tool. Sun emphasizes that successful AI adoption demands more than tech — it needs executive buy-in, change management, and a relentless focus on business value. Her advice? Start small, but think big, and treat AI not as a tool, but as a company-wide transformation.


Episode Highlights:


6:00 - Vivian discusses how Jabil’s AI journey focused on three core technologies; AI computer vision, machine learning, and generative AI.


11:31 - Vivian explains how early use-cases of AI at Jabil paved the way for further implementation by revealing a direct impact on business, educating employees, and building confidence among executives.


16:58 - Vivian and Peter unpack how generative AI can be used in tandem with machine learning to validate or improve the information gleaned from a company’s data.

]]> Thu, 18 Sep 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 24:22 AI transformation isn’t about flashy tools — it’s about strategic wins that build momentum and deliver real business value.


On this episode of Where AI Works, host Peter Cappelli is joined by Vivian Sun, the Senior Director of Data & AI, Enterprise Architecture, and IT Transformation at Jabil Incorporated, one of the world’s largest and most quietly influential contract manufacturers. Sun shares how her company scaled AI across its global operations — not by chasing hype, but by starting with tangible use cases that delivered measurable impact. As you’ll hear, Jabil’s journey began with AI-powered computer vision, replacing tedious and error-prone visual inspections. From there, it moved into machine learning for color calibration in manufacturing — transforming decades of tacit worker knowledge into predictive models. They then layered in generative AI to enhance compliance with trade regulations, using AI as both a decision-making assistant and a validation tool. Sun emphasizes that successful AI adoption demands more than tech — it needs executive buy-in, change management, and a relentless focus on business value. Her advice? Start small, but think big, and treat AI not as a tool, but as a company-wide transformation.


Episode Highlights:


6:00 - Vivian discusses how Jabil’s AI journey focused on three core technologies; AI computer vision, machine learning, and generative AI.


11:31 - Vivian explains how early use-cases of AI at Jabil paved the way for further implementation by revealing a direct impact on business, educating employees, and building confidence among executives.


16:58 - Vivian and Peter unpack how generative AI can be used in tandem with machine learning to validate or improve the information gleaned from a company’s data.

]]> AI transformation isn’t about flashy tools — it’s about strategic wins that build momentum and deliver real business value.


On this episode of Where AI Works, host Peter Cappelli is joined by Vivian Sun, the Senior Director of Data & AI, Enterprise Architecture, and IT Transformation at Jabil Incorporated, one of the world’s largest and most quietly influential contract manufacturers. Sun shares how her company scaled AI across its global operations — not by chasing hype, but by starting with tangible use cases that delivered measurable impact. As you’ll hear, Jabil’s journey began with AI-powered computer vision, replacing tedious and error-prone visual inspections. From there, it moved into machine learning for color calibration in manufacturing — transforming decades of tacit worker knowledge into predictive models. They then layered in generative AI to enhance compliance with trade regulations, using AI as both a decision-making assistant and a validation tool. Sun emphasizes that successful AI adoption demands more than tech — it needs executive buy-in, change management, and a relentless focus on business value. Her advice? Start small, but think big, and treat AI not as a tool, but as a company-wide transformation.


Episode Highlights:


6:00 - Vivian discusses how Jabil’s AI journey focused on three core technologies; AI computer vision, machine learning, and generative AI.


11:31 - Vivian explains how early use-cases of AI at Jabil paved the way for further implementation by revealing a direct impact on business, educating employees, and building confidence among executives.


16:58 - Vivian and Peter unpack how generative AI can be used in tandem with machine learning to validate or improve the information gleaned from a company’s data.

]]> false full 2 3 <![CDATA[Work, Rewired: Rethinking Talent, Strategy, and AI]]> It’s a daunting task: moving AI from experimentation to transformation across a massive, global organization with more than 800,000 employees. It turns out it isn’t just about optimizing tasks — it’s about rethinking roles entirely, and managing that change effectively.


On this premiere episode of season three of Where AI Works, host Peter Cappelli is joined by Karalee Close, the Global Lead of Talent & Organization at Accenture, to explore what it truly takes to scale AI across a large enterprise — not just in isolated pilots, but as a driver of full organizational reinvention. Karalee shares her firsthand experience leading AI implementation on a global scale, underscoring that the real challenge isn’t technical, but cultural. She also explains how success depends on convincing leadership to embrace new ways of working, and keeping people at the center of every change, rather than treating AI as a tool for incremental improvements in existing workflows. Packed with insights and practical advice about Agentic AI in particular, this episode offers a clear look at what’s required to move beyond experimentation and generate real enterprise value.

 


Episode Highlights:


6:09 - Karalee pushes back against the notion that the relationship between AI and human employees has to be an adversarial one.


11:23 - Karalee explains how defining specific tasks and sequences is no longer necessary thanks to agentic AI — you only have to define the strategic intent.


18:26 - Karalee discusses the resistance Accenture has encountered in implementing AI — both internally and externally — and how to overcome it.

]]> Thu, 04 Sep 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 24:50 It’s a daunting task: moving AI from experimentation to transformation across a massive, global organization with more than 800,000 employees. It turns out it isn’t just about optimizing tasks — it’s about rethinking roles entirely, and managing that change effectively.


On this premiere episode of season three of Where AI Works, host Peter Cappelli is joined by Karalee Close, the Global Lead of Talent & Organization at Accenture, to explore what it truly takes to scale AI across a large enterprise — not just in isolated pilots, but as a driver of full organizational reinvention. Karalee shares her firsthand experience leading AI implementation on a global scale, underscoring that the real challenge isn’t technical, but cultural. She also explains how success depends on convincing leadership to embrace new ways of working, and keeping people at the center of every change, rather than treating AI as a tool for incremental improvements in existing workflows. Packed with insights and practical advice about Agentic AI in particular, this episode offers a clear look at what’s required to move beyond experimentation and generate real enterprise value.

 


Episode Highlights:


6:09 - Karalee pushes back against the notion that the relationship between AI and human employees has to be an adversarial one.


11:23 - Karalee explains how defining specific tasks and sequences is no longer necessary thanks to agentic AI — you only have to define the strategic intent.


18:26 - Karalee discusses the resistance Accenture has encountered in implementing AI — both internally and externally — and how to overcome it.

]]> It’s a daunting task: moving AI from experimentation to transformation across a massive, global organization with more than 800,000 employees. It turns out it isn’t just about optimizing tasks — it’s about rethinking roles entirely, and managing that change effectively.


On this premiere episode of season three of Where AI Works, host Peter Cappelli is joined by Karalee Close, the Global Lead of Talent & Organization at Accenture, to explore what it truly takes to scale AI across a large enterprise — not just in isolated pilots, but as a driver of full organizational reinvention. Karalee shares her firsthand experience leading AI implementation on a global scale, underscoring that the real challenge isn’t technical, but cultural. She also explains how success depends on convincing leadership to embrace new ways of working, and keeping people at the center of every change, rather than treating AI as a tool for incremental improvements in existing workflows. Packed with insights and practical advice about Agentic AI in particular, this episode offers a clear look at what’s required to move beyond experimentation and generate real enterprise value.

 


Episode Highlights:


6:09 - Karalee pushes back against the notion that the relationship between AI and human employees has to be an adversarial one.


11:23 - Karalee explains how defining specific tasks and sequences is no longer necessary thanks to agentic AI — you only have to define the strategic intent.


18:26 - Karalee discusses the resistance Accenture has encountered in implementing AI — both internally and externally — and how to overcome it.

]]> false full 1 3 <![CDATA[Host's Cut: Reflections on Season Two]]> AI is no longer a futuristic promise — it’s become a business imperative. Whether it's edge computing for real-time insights, rethinking patient care ecosystems, or rolling out generative AI to 138,000 employees, this season of Where AI Works highlights how AI is reshaping strategy, service delivery, and decision-making across the enterprise. 


On this recap and review episode, host Serguei Netessine reflects on the key learnings from his conversations with Alan Lee, the CTO of Analog Devices; Elad Walach, the CEO of AIDOC; Tereza Nemenssanyi, Worldwide Director of Private Equity & Venture Capital Partnerships at Microsoft; and Ajay Anand, the Senior Vice President of Global Services, Strategy and Business Services at Johnson & Johnson. Together, they unpack how leading companies are moving beyond hype to maximize ROI across industries — from semiconductors and healthcare to global enterprises. Our guests discuss how AI is enhancing product development, reducing diagnostic errors, transforming shared services, and driving operational efficiency. It turns out technology alone isn’t enough: organizations must align AI adoption with measurable outcomes, foster a culture of experimentation, and build bridges between data scientists, business leaders, and end users to unlock true value.

 


Episode Highlights:

1:43 - Alan shares the “8th grade Earth science model” he uses to explain the relationship between LLMs, industrial AI, and edge-type devices.


4:25 - Elad explains why the true value of AI lies in adopting an enterprise-wide or systems-based approach, rather than a task-by-task approach.


6:05 - Tereza discusses why implementing AI should be an ecosystem play, where different startups and large companies work together to make it more useful. 


7:39 - Ajay lays out the “EEE” framework (experience, effectiveness and efficiency) that Johnson & Johnson uses to track the KPIs of its AI-related efforts.

]]> Thu, 21 Aug 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 9:36 AI is no longer a futuristic promise — it’s become a business imperative. Whether it's edge computing for real-time insights, rethinking patient care ecosystems, or rolling out generative AI to 138,000 employees, this season of Where AI Works highlights how AI is reshaping strategy, service delivery, and decision-making across the enterprise. 


On this recap and review episode, host Serguei Netessine reflects on the key learnings from his conversations with Alan Lee, the CTO of Analog Devices; Elad Walach, the CEO of AIDOC; Tereza Nemenssanyi, Worldwide Director of Private Equity & Venture Capital Partnerships at Microsoft; and Ajay Anand, the Senior Vice President of Global Services, Strategy and Business Services at Johnson & Johnson. Together, they unpack how leading companies are moving beyond hype to maximize ROI across industries — from semiconductors and healthcare to global enterprises. Our guests discuss how AI is enhancing product development, reducing diagnostic errors, transforming shared services, and driving operational efficiency. It turns out technology alone isn’t enough: organizations must align AI adoption with measurable outcomes, foster a culture of experimentation, and build bridges between data scientists, business leaders, and end users to unlock true value.

 


Episode Highlights:

1:43 - Alan shares the “8th grade Earth science model” he uses to explain the relationship between LLMs, industrial AI, and edge-type devices.


4:25 - Elad explains why the true value of AI lies in adopting an enterprise-wide or systems-based approach, rather than a task-by-task approach.


6:05 - Tereza discusses why implementing AI should be an ecosystem play, where different startups and large companies work together to make it more useful. 


7:39 - Ajay lays out the “EEE” framework (experience, effectiveness and efficiency) that Johnson & Johnson uses to track the KPIs of its AI-related efforts.

]]> AI is no longer a futuristic promise — it’s become a business imperative. Whether it's edge computing for real-time insights, rethinking patient care ecosystems, or rolling out generative AI to 138,000 employees, this season of Where AI Works highlights how AI is reshaping strategy, service delivery, and decision-making across the enterprise. 


On this recap and review episode, host Serguei Netessine reflects on the key learnings from his conversations with Alan Lee, the CTO of Analog Devices; Elad Walach, the CEO of AIDOC; Tereza Nemenssanyi, Worldwide Director of Private Equity & Venture Capital Partnerships at Microsoft; and Ajay Anand, the Senior Vice President of Global Services, Strategy and Business Services at Johnson & Johnson. Together, they unpack how leading companies are moving beyond hype to maximize ROI across industries — from semiconductors and healthcare to global enterprises. Our guests discuss how AI is enhancing product development, reducing diagnostic errors, transforming shared services, and driving operational efficiency. It turns out technology alone isn’t enough: organizations must align AI adoption with measurable outcomes, foster a culture of experimentation, and build bridges between data scientists, business leaders, and end users to unlock true value.

 


Episode Highlights:

1:43 - Alan shares the “8th grade Earth science model” he uses to explain the relationship between LLMs, industrial AI, and edge-type devices.


4:25 - Elad explains why the true value of AI lies in adopting an enterprise-wide or systems-based approach, rather than a task-by-task approach.


6:05 - Tereza discusses why implementing AI should be an ecosystem play, where different startups and large companies work together to make it more useful. 


7:39 - Ajay lays out the “EEE” framework (experience, effectiveness and efficiency) that Johnson & Johnson uses to track the KPIs of its AI-related efforts.

]]> false full 5 2 <![CDATA[Experience, Effectiveness, Efficiency: Johnson & Johnson’s AI Journey]]> What does it take to scale AI across a global enterprise without breaking what already works? And how do you unlock value at scale — without losing sight of people, processes, and trust?


On this season finale episode of Where AI Works, host Serguei Netessine speaks with

Ajay Anand, the Senior Vice President of Global Services, Strategy and Business Services at Johnson & Johnson, about how AI is transforming operations behind the scenes at the iconic global healthcare and medtech company. Together, they explore how shared services — spanning HR, finance, procurement, and more — are being reimagined through an AI-first lens, unlocking new value while improving speed, decision quality, and employee experience. They also discuss how GenAI tools like JAIDA are helping 138,000 employees navigate complex internal systems and policies, reducing friction and freeing up time for higher-value work. For business leaders navigating their own AI journeys, this episode offers a clear-eyed look at where to start, how to scale, and what it takes to turn AI from a technical experiment into a strategic operating capability.

 


Episode Highlights:


5:12 - Ajay explains how AI is being integrated into J&J’s processes and services, with a focus on improving complex interactions for the company’s 138,000 employees.


8:18 - Ajay discusses the KPIs — the “Three E framework” — that J&J uses to assess the effectiveness of its AI implementation efforts.


17:06 - Ajay lays out his four-point strategy for other business leaders who are looking to engage with traditional, generative, or agentic AI.

]]> Thu, 07 Aug 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 23:13 What does it take to scale AI across a global enterprise without breaking what already works? And how do you unlock value at scale — without losing sight of people, processes, and trust?


On this season finale episode of Where AI Works, host Serguei Netessine speaks with

Ajay Anand, the Senior Vice President of Global Services, Strategy and Business Services at Johnson & Johnson, about how AI is transforming operations behind the scenes at the iconic global healthcare and medtech company. Together, they explore how shared services — spanning HR, finance, procurement, and more — are being reimagined through an AI-first lens, unlocking new value while improving speed, decision quality, and employee experience. They also discuss how GenAI tools like JAIDA are helping 138,000 employees navigate complex internal systems and policies, reducing friction and freeing up time for higher-value work. For business leaders navigating their own AI journeys, this episode offers a clear-eyed look at where to start, how to scale, and what it takes to turn AI from a technical experiment into a strategic operating capability.

 


Episode Highlights:


5:12 - Ajay explains how AI is being integrated into J&J’s processes and services, with a focus on improving complex interactions for the company’s 138,000 employees.


8:18 - Ajay discusses the KPIs — the “Three E framework” — that J&J uses to assess the effectiveness of its AI implementation efforts.


17:06 - Ajay lays out his four-point strategy for other business leaders who are looking to engage with traditional, generative, or agentic AI.

]]> What does it take to scale AI across a global enterprise without breaking what already works? And how do you unlock value at scale — without losing sight of people, processes, and trust?


On this season finale episode of Where AI Works, host Serguei Netessine speaks with

Ajay Anand, the Senior Vice President of Global Services, Strategy and Business Services at Johnson & Johnson, about how AI is transforming operations behind the scenes at the iconic global healthcare and medtech company. Together, they explore how shared services — spanning HR, finance, procurement, and more — are being reimagined through an AI-first lens, unlocking new value while improving speed, decision quality, and employee experience. They also discuss how GenAI tools like JAIDA are helping 138,000 employees navigate complex internal systems and policies, reducing friction and freeing up time for higher-value work. For business leaders navigating their own AI journeys, this episode offers a clear-eyed look at where to start, how to scale, and what it takes to turn AI from a technical experiment into a strategic operating capability.

 


Episode Highlights:


5:12 - Ajay explains how AI is being integrated into J&J’s processes and services, with a focus on improving complex interactions for the company’s 138,000 employees.


8:18 - Ajay discusses the KPIs — the “Three E framework” — that J&J uses to assess the effectiveness of its AI implementation efforts.


17:06 - Ajay lays out his four-point strategy for other business leaders who are looking to engage with traditional, generative, or agentic AI.

]]> false full 4 2 <![CDATA[From Pain Points to Productivity: Finding AI’s Real Value]]> What if the real value of AI isn’t in the technology itself, but in the pain points and problems it solves for business? That’s the question at the heart of this episode of Where AI Works, which features an iconic company that’s been at the forefront of digital transformation for decades.


Host Serguei Netessine is joined by Tereza Nemessanyi, Worldwide Director of Private Equity & Venture Capital Partnerships at Microsoft, to explore the varied, experimental approaches many of her clients are taking in an effort to monetize their AI offerings. As Tereza points out, AI deployment is still in its early stages, and success in this space requires a culture that supports rapid iteration, short sprints, and a willingness to explore both vertical and horizontal applications to see what sticks. She believes the biggest opportunities lie in high “cost-to-serve” areas — pain points where AI can dramatically reduce effort or complexity. In other words, AI isn’t a destination — it’s a journey, and the smartest companies are already well down the road.


Talking Points:


  • AI Is Being Embedded Into Everyday Tools: 
  • Generative AI is showing up in the software people already use—like Microsoft Word, Excel, and Outlook—making it frictionless for users to adopt.

  • Horizontal Applications Are Leading AI Adoption: 
  • The biggest wins are coming from general-use AI tools that cut across industries, rather than highly specialized vertical applications.

  • GitHub Copilot Is Transforming Developer Productivity: 
  • As a standout example, Copilot is helping developers code faster and smarter, showcasing how AI can be a true productivity partner.



Episode Highlights:


5:21 - Tereza lays out the three main ways in which AI is changing the value proposition for Microsoft investors, clients, and collaborators.


10:30 - Tereza shares examples of horizontal and vertical AI integration efforts, and how they can both connect to a potential ROI. 


19:05 - Tereza discusses the types of blockers she's seen her clients encounter while trying to monetize AT effectively.

]]> Thu, 24 Jul 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 24:35 What if the real value of AI isn’t in the technology itself, but in the pain points and problems it solves for business? That’s the question at the heart of this episode of Where AI Works, which features an iconic company that’s been at the forefront of digital transformation for decades.


Host Serguei Netessine is joined by Tereza Nemessanyi, Worldwide Director of Private Equity & Venture Capital Partnerships at Microsoft, to explore the varied, experimental approaches many of her clients are taking in an effort to monetize their AI offerings. As Tereza points out, AI deployment is still in its early stages, and success in this space requires a culture that supports rapid iteration, short sprints, and a willingness to explore both vertical and horizontal applications to see what sticks. She believes the biggest opportunities lie in high “cost-to-serve” areas — pain points where AI can dramatically reduce effort or complexity. In other words, AI isn’t a destination — it’s a journey, and the smartest companies are already well down the road.


Talking Points:


  • AI Is Being Embedded Into Everyday Tools: 
  • Generative AI is showing up in the software people already use—like Microsoft Word, Excel, and Outlook—making it frictionless for users to adopt.

  • Horizontal Applications Are Leading AI Adoption: 
  • The biggest wins are coming from general-use AI tools that cut across industries, rather than highly specialized vertical applications.

  • GitHub Copilot Is Transforming Developer Productivity: 
  • As a standout example, Copilot is helping developers code faster and smarter, showcasing how AI can be a true productivity partner.



Episode Highlights:


5:21 - Tereza lays out the three main ways in which AI is changing the value proposition for Microsoft investors, clients, and collaborators.


10:30 - Tereza shares examples of horizontal and vertical AI integration efforts, and how they can both connect to a potential ROI. 


19:05 - Tereza discusses the types of blockers she's seen her clients encounter while trying to monetize AT effectively.

]]> What if the real value of AI isn’t in the technology itself, but in the pain points and problems it solves for business? That’s the question at the heart of this episode of Where AI Works, which features an iconic company that’s been at the forefront of digital transformation for decades.


Host Serguei Netessine is joined by Tereza Nemessanyi, Worldwide Director of Private Equity & Venture Capital Partnerships at Microsoft, to explore the varied, experimental approaches many of her clients are taking in an effort to monetize their AI offerings. As Tereza points out, AI deployment is still in its early stages, and success in this space requires a culture that supports rapid iteration, short sprints, and a willingness to explore both vertical and horizontal applications to see what sticks. She believes the biggest opportunities lie in high “cost-to-serve” areas — pain points where AI can dramatically reduce effort or complexity. In other words, AI isn’t a destination — it’s a journey, and the smartest companies are already well down the road.


Talking Points:


  • AI Is Being Embedded Into Everyday Tools: 
  • Generative AI is showing up in the software people already use—like Microsoft Word, Excel, and Outlook—making it frictionless for users to adopt.

  • Horizontal Applications Are Leading AI Adoption: 
  • The biggest wins are coming from general-use AI tools that cut across industries, rather than highly specialized vertical applications.

  • GitHub Copilot Is Transforming Developer Productivity: 
  • As a standout example, Copilot is helping developers code faster and smarter, showcasing how AI can be a true productivity partner.



Episode Highlights:


5:21 - Tereza lays out the three main ways in which AI is changing the value proposition for Microsoft investors, clients, and collaborators.


10:30 - Tereza shares examples of horizontal and vertical AI integration efforts, and how they can both connect to a potential ROI. 


19:05 - Tereza discusses the types of blockers she's seen her clients encounter while trying to monetize AT effectively.

]]> false full 3 2 <![CDATA[AI: The Operating System for Modern Healthcare]]> It's a staggering statistic: every year in the United States, diagnostic errors in the healthcare system lead to 370,000 preventable deaths and 400,000 permanent disabilities. But what if hospitals and practitioners could leverage the power of artificial intelligence to cut those numbers in half?


On this episode of Where AI Works, host Serguei Netessine sits down with Elad Walach, the CEO and founder of AIDOC, which aims to set a new standard for AI-powered healthcare solutions by combining clinical logic, operational intelligence, and system-wide accountability to create an entirely new ecosystem. Their conversation offers crucial insights for other enterprise leaders who are navigating AI adoption and implementation in complex, slow-moving, or low-margin industries. It also highlights the importance of aligning AI innovation with measurable financial and clinical outcomes, rather than assuming the benefits will materialize automatically. As Elad puts it, the old saying “If you build it, they will come” is simply not true in the context of modern healthcare — you also have to prove the value of your technology and be able to extract it.

 

Episode Highlights:

8:23 - Elad discusses the challenge of convincing healthcare providers of the potential of AI when the user or practitioner isn’t the main beneficiary.


15:50 - Elad explains why trying to monetize AI on a per-patient basis was a “disaster” for AIDOC because there was no clear understanding of the value proposition.


19:37 - Elad looks forward to the future of AI-powered healthcare, where applications will not be disease-specific, but comprehensive and generic.

]]> Thu, 10 Jul 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 23:57 It's a staggering statistic: every year in the United States, diagnostic errors in the healthcare system lead to 370,000 preventable deaths and 400,000 permanent disabilities. But what if hospitals and practitioners could leverage the power of artificial intelligence to cut those numbers in half?


On this episode of Where AI Works, host Serguei Netessine sits down with Elad Walach, the CEO and founder of AIDOC, which aims to set a new standard for AI-powered healthcare solutions by combining clinical logic, operational intelligence, and system-wide accountability to create an entirely new ecosystem. Their conversation offers crucial insights for other enterprise leaders who are navigating AI adoption and implementation in complex, slow-moving, or low-margin industries. It also highlights the importance of aligning AI innovation with measurable financial and clinical outcomes, rather than assuming the benefits will materialize automatically. As Elad puts it, the old saying “If you build it, they will come” is simply not true in the context of modern healthcare — you also have to prove the value of your technology and be able to extract it.

 

Episode Highlights:

8:23 - Elad discusses the challenge of convincing healthcare providers of the potential of AI when the user or practitioner isn’t the main beneficiary.


15:50 - Elad explains why trying to monetize AI on a per-patient basis was a “disaster” for AIDOC because there was no clear understanding of the value proposition.


19:37 - Elad looks forward to the future of AI-powered healthcare, where applications will not be disease-specific, but comprehensive and generic.

]]> It's a staggering statistic: every year in the United States, diagnostic errors in the healthcare system lead to 370,000 preventable deaths and 400,000 permanent disabilities. But what if hospitals and practitioners could leverage the power of artificial intelligence to cut those numbers in half?


On this episode of Where AI Works, host Serguei Netessine sits down with Elad Walach, the CEO and founder of AIDOC, which aims to set a new standard for AI-powered healthcare solutions by combining clinical logic, operational intelligence, and system-wide accountability to create an entirely new ecosystem. Their conversation offers crucial insights for other enterprise leaders who are navigating AI adoption and implementation in complex, slow-moving, or low-margin industries. It also highlights the importance of aligning AI innovation with measurable financial and clinical outcomes, rather than assuming the benefits will materialize automatically. As Elad puts it, the old saying “If you build it, they will come” is simply not true in the context of modern healthcare — you also have to prove the value of your technology and be able to extract it.

 

Episode Highlights:

8:23 - Elad discusses the challenge of convincing healthcare providers of the potential of AI when the user or practitioner isn’t the main beneficiary.


15:50 - Elad explains why trying to monetize AI on a per-patient basis was a “disaster” for AIDOC because there was no clear understanding of the value proposition.


19:37 - Elad looks forward to the future of AI-powered healthcare, where applications will not be disease-specific, but comprehensive and generic.

]]> false full 2 2 <![CDATA[AI, Hardware, and the Future of Intelligent Systems]]> How can artificial intelligence not just transform industries but also create real business value? On this premiere episode of season two of Where AI Works, host Serguei Netessine is joined by Alan Lee, CTO of Analog Devices Incorporated, to discuss strategies for the practical deployment and monetization of AI. They explore how AI can enhance product development and predictive maintenance while addressing challenges like power efficiency and hardware constraints. Alan also shares how AI-powered innovations can open new revenue streams and competitive advantages, turning AI from a simple buzzword into measurable business outcomes. The conversation highlights the critical role of edge computing for real-time data processing as well as the cultural collaboration needed between technologists, data scientists, and even skeptics to unlock AI’s full potential. You’ll also hear Alan’s vision for a future where machine intelligence of some sort will exist everywhere, and his advice to other business leaders about when to proceed cautiously and when to go ‘all in’ when it comes to AI.


Episode Highlights:


10:13 - Alan discusses strategies for managing the cultural conflict that can arise within organizations when new technology is implemented.


14:26 - Alan shares a counterintuitive take on the tension between technologists and what he calls “AI skeptics” across different business units.


17:31 - Alan lays out his vision for the future; a world where machine intelligence of some kind will be ubiquitous and pervasive.


19:21 - Alan talks about the challenge of monetizing AI when it still hasn’t realized its full potential in helping us solve some of the world’s most pressing problems.

]]> Thu, 26 Jun 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 25:20 How can artificial intelligence not just transform industries but also create real business value? On this premiere episode of season two of Where AI Works, host Serguei Netessine is joined by Alan Lee, CTO of Analog Devices Incorporated, to discuss strategies for the practical deployment and monetization of AI. They explore how AI can enhance product development and predictive maintenance while addressing challenges like power efficiency and hardware constraints. Alan also shares how AI-powered innovations can open new revenue streams and competitive advantages, turning AI from a simple buzzword into measurable business outcomes. The conversation highlights the critical role of edge computing for real-time data processing as well as the cultural collaboration needed between technologists, data scientists, and even skeptics to unlock AI’s full potential. You’ll also hear Alan’s vision for a future where machine intelligence of some sort will exist everywhere, and his advice to other business leaders about when to proceed cautiously and when to go ‘all in’ when it comes to AI.


Episode Highlights:


10:13 - Alan discusses strategies for managing the cultural conflict that can arise within organizations when new technology is implemented.


14:26 - Alan shares a counterintuitive take on the tension between technologists and what he calls “AI skeptics” across different business units.


17:31 - Alan lays out his vision for the future; a world where machine intelligence of some kind will be ubiquitous and pervasive.


19:21 - Alan talks about the challenge of monetizing AI when it still hasn’t realized its full potential in helping us solve some of the world’s most pressing problems.

]]> How can artificial intelligence not just transform industries but also create real business value? On this premiere episode of season two of Where AI Works, host Serguei Netessine is joined by Alan Lee, CTO of Analog Devices Incorporated, to discuss strategies for the practical deployment and monetization of AI. They explore how AI can enhance product development and predictive maintenance while addressing challenges like power efficiency and hardware constraints. Alan also shares how AI-powered innovations can open new revenue streams and competitive advantages, turning AI from a simple buzzword into measurable business outcomes. The conversation highlights the critical role of edge computing for real-time data processing as well as the cultural collaboration needed between technologists, data scientists, and even skeptics to unlock AI’s full potential. You’ll also hear Alan’s vision for a future where machine intelligence of some sort will exist everywhere, and his advice to other business leaders about when to proceed cautiously and when to go ‘all in’ when it comes to AI.


Episode Highlights:


10:13 - Alan discusses strategies for managing the cultural conflict that can arise within organizations when new technology is implemented.


14:26 - Alan shares a counterintuitive take on the tension between technologists and what he calls “AI skeptics” across different business units.


17:31 - Alan lays out his vision for the future; a world where machine intelligence of some kind will be ubiquitous and pervasive.


19:21 - Alan talks about the challenge of monetizing AI when it still hasn’t realized its full potential in helping us solve some of the world’s most pressing problems.

]]> false full 1 2 <![CDATA[Host's Cut: Reflections on Season One]]> What happens when AI collides with the world of marketing? A seismic shift — but only for those ready to embrace the upheaval. On this recap episode of Where AI Works, host Kartik Hosanagar reviews the four compelling conversations that made up the show’s inaugural season. Jonathan Halvorson, Global SVP of Consumer Experience at Mondelēz International, kicked things off by emphasizing the impact of AI on content creation and media spend — and the importance of preserving brand distinctiveness in an AI-driven landscape. Accenture CMO Jill Kramer shared her personal journey from AI skeptic to champion, outlining a practical roadmap for reskilling marketing teams at scale. David Droga, founder of Droga5 and CEO of Accenture Song, challenged the creative industry to embrace AI not as a replacement, but as a way to elevate originality and move beyond mediocrity. Finally, Accenture’s Chief AI Officer Lan Guan highlighted the gap between AI investment and scaled execution, and stressed the critical need for trust and governance. Together, these voices deliver a powerful message to business leaders: to harness AI's true potential, you must act boldly, intentionally, and creatively.



Episode Highlights:


2:05 - Jonathan discusses the importance of embedding brand distinctiveness in any AI-generated content your company creates.


4:45 - David explains his provocative stance that not all creativity is worth saving.


6:52 - Lan spells out why trust and explainable AI are more important than ever due to the rise in agentic systems.

2:05 - Jonathan discusses the importance of embedding brand distinctiveness in any AI-generated content your company creates.


4:45 - David explains his provocative stance that not all creativity is worth saving.


6:52 - Lan spells out why trust and explainable AI are more important than ever due to the rise in agentic systems.

]]> Thu, 12 Jun 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 8:46 What happens when AI collides with the world of marketing? A seismic shift — but only for those ready to embrace the upheaval. On this recap episode of Where AI Works, host Kartik Hosanagar reviews the four compelling conversations that made up the show’s inaugural season. Jonathan Halvorson, Global SVP of Consumer Experience at Mondelēz International, kicked things off by emphasizing the impact of AI on content creation and media spend — and the importance of preserving brand distinctiveness in an AI-driven landscape. Accenture CMO Jill Kramer shared her personal journey from AI skeptic to champion, outlining a practical roadmap for reskilling marketing teams at scale. David Droga, founder of Droga5 and CEO of Accenture Song, challenged the creative industry to embrace AI not as a replacement, but as a way to elevate originality and move beyond mediocrity. Finally, Accenture’s Chief AI Officer Lan Guan highlighted the gap between AI investment and scaled execution, and stressed the critical need for trust and governance. Together, these voices deliver a powerful message to business leaders: to harness AI's true potential, you must act boldly, intentionally, and creatively.



Episode Highlights:


2:05 - Jonathan discusses the importance of embedding brand distinctiveness in any AI-generated content your company creates.


4:45 - David explains his provocative stance that not all creativity is worth saving.


6:52 - Lan spells out why trust and explainable AI are more important than ever due to the rise in agentic systems.

2:05 - Jonathan discusses the importance of embedding brand distinctiveness in any AI-generated content your company creates.


4:45 - David explains his provocative stance that not all creativity is worth saving.


6:52 - Lan spells out why trust and explainable AI are more important than ever due to the rise in agentic systems.

]]> What happens when AI collides with the world of marketing? A seismic shift — but only for those ready to embrace the upheaval. On this recap episode of Where AI Works, host Kartik Hosanagar reviews the four compelling conversations that made up the show’s inaugural season. Jonathan Halvorson, Global SVP of Consumer Experience at Mondelēz International, kicked things off by emphasizing the impact of AI on content creation and media spend — and the importance of preserving brand distinctiveness in an AI-driven landscape. Accenture CMO Jill Kramer shared her personal journey from AI skeptic to champion, outlining a practical roadmap for reskilling marketing teams at scale. David Droga, founder of Droga5 and CEO of Accenture Song, challenged the creative industry to embrace AI not as a replacement, but as a way to elevate originality and move beyond mediocrity. Finally, Accenture’s Chief AI Officer Lan Guan highlighted the gap between AI investment and scaled execution, and stressed the critical need for trust and governance. Together, these voices deliver a powerful message to business leaders: to harness AI's true potential, you must act boldly, intentionally, and creatively.



Episode Highlights:


2:05 - Jonathan discusses the importance of embedding brand distinctiveness in any AI-generated content your company creates.


4:45 - David explains his provocative stance that not all creativity is worth saving.


6:52 - Lan spells out why trust and explainable AI are more important than ever due to the rise in agentic systems.

2:05 - Jonathan discusses the importance of embedding brand distinctiveness in any AI-generated content your company creates.


4:45 - David explains his provocative stance that not all creativity is worth saving.


6:52 - Lan spells out why trust and explainable AI are more important than ever due to the rise in agentic systems.

]]> false full 5 1 <![CDATA[AI at Scale: Revolutionizing Enterprise Strategy and Growth]]> Is your organization stuck on table stakes or starting to place more strategic bets when it comes to implementing AI? Are your employees still wrapping their heads around LLMs, or have they started experimenting with agentic AI? And what’s the competitive advantage you want your company to be famous for? 


On this season finale episode of Where AI Works, host Kartik Hosanagar tackles those questions and more with the help of a woman who oversees more than 65,000 data and AI practitioners, and has helped her organization book more than 5.6 billion dollars worth of AI-related business in the past 18 months — Accenture’s Chief AI Officer, Lan Guan. Together, they break down the key trends shaping AI’s impact on enterprises, with Lan sharing insights from Accenture’s groundbreaking AI initiatives. You’ll hear specific examples of how AI-powered solutions are improving efficiency and automating workflows across sectors like financial services, oil and gas, and life sciences. Lan also shares her thoughts on which challenges the AI sector still needs to solve, including education, governance, and interoperability.


Episode Highlights: 


7:10 - Kartik and Lan discuss how companies can cope with the “problem of plenty” in the AI space; the vast array of new software solutions on offer.


12:27 - Lan explains how companies need to ensure talent and data readiness to avoid the old “garbage in, garbage out” pitfall that has plagued AI implementation efforts in the past.


17:31 - Lan shares what she sees as the three roadblocks or challenges the industry faces in deploying large scale agent based systems in organizations.

]]> Thu, 29 May 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 24:17 Is your organization stuck on table stakes or starting to place more strategic bets when it comes to implementing AI? Are your employees still wrapping their heads around LLMs, or have they started experimenting with agentic AI? And what’s the competitive advantage you want your company to be famous for? 


On this season finale episode of Where AI Works, host Kartik Hosanagar tackles those questions and more with the help of a woman who oversees more than 65,000 data and AI practitioners, and has helped her organization book more than 5.6 billion dollars worth of AI-related business in the past 18 months — Accenture’s Chief AI Officer, Lan Guan. Together, they break down the key trends shaping AI’s impact on enterprises, with Lan sharing insights from Accenture’s groundbreaking AI initiatives. You’ll hear specific examples of how AI-powered solutions are improving efficiency and automating workflows across sectors like financial services, oil and gas, and life sciences. Lan also shares her thoughts on which challenges the AI sector still needs to solve, including education, governance, and interoperability.


Episode Highlights: 


7:10 - Kartik and Lan discuss how companies can cope with the “problem of plenty” in the AI space; the vast array of new software solutions on offer.


12:27 - Lan explains how companies need to ensure talent and data readiness to avoid the old “garbage in, garbage out” pitfall that has plagued AI implementation efforts in the past.


17:31 - Lan shares what she sees as the three roadblocks or challenges the industry faces in deploying large scale agent based systems in organizations.

]]> Is your organization stuck on table stakes or starting to place more strategic bets when it comes to implementing AI? Are your employees still wrapping their heads around LLMs, or have they started experimenting with agentic AI? And what’s the competitive advantage you want your company to be famous for? 


On this season finale episode of Where AI Works, host Kartik Hosanagar tackles those questions and more with the help of a woman who oversees more than 65,000 data and AI practitioners, and has helped her organization book more than 5.6 billion dollars worth of AI-related business in the past 18 months — Accenture’s Chief AI Officer, Lan Guan. Together, they break down the key trends shaping AI’s impact on enterprises, with Lan sharing insights from Accenture’s groundbreaking AI initiatives. You’ll hear specific examples of how AI-powered solutions are improving efficiency and automating workflows across sectors like financial services, oil and gas, and life sciences. Lan also shares her thoughts on which challenges the AI sector still needs to solve, including education, governance, and interoperability.


Episode Highlights: 


7:10 - Kartik and Lan discuss how companies can cope with the “problem of plenty” in the AI space; the vast array of new software solutions on offer.


12:27 - Lan explains how companies need to ensure talent and data readiness to avoid the old “garbage in, garbage out” pitfall that has plagued AI implementation efforts in the past.


17:31 - Lan shares what she sees as the three roadblocks or challenges the industry faces in deploying large scale agent based systems in organizations.

]]> false full 4 1 <![CDATA[How AI Changes the Game for Creative Teams]]> It’s a controversial statement, especially coming from the founder of one of the most famous creative agencies in the world: “Not all creativity is worth saving.” But it’s with that bold declaration that this episode of Where AI Works begins.


This time, host Kartik Hosanagar is joined by David Droga, founder of Droga5, and current CEO of Accenture Song, for a thoughtful and insightful discussion about AI’s transformative impact on the creativity industry. Together, they tackle the question of whether AI is becoming a critical creative partner for agencies and their clients, or if it’s potentially a threat in certain sectors. They also explore David’s belief that AI could actually be an accelerator and enabler for creatives by eliminating what he calls the ‘mediocre middle’. Listen to the very end and you’ll hear about David’s uplifting and inspirational vision for the future of creativity, and why he thinks true creatives are more relevant in more places than ever, despite the rapid pace of technological change.


Episode Highlights:


9:20 - David explains why he feels not all creativity is worth saving, and how AI will “industrialize the imagination.”


13:32 - Kartik and David discuss how AI is causing business leaders to rethink roles and responsibilities within their organizations. 


18:24 - David explains why he’s still bullish on creative people, but believes creative agencies need to adapt their business models.

]]> Thu, 15 May 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 25:40 It’s a controversial statement, especially coming from the founder of one of the most famous creative agencies in the world: “Not all creativity is worth saving.” But it’s with that bold declaration that this episode of Where AI Works begins.


This time, host Kartik Hosanagar is joined by David Droga, founder of Droga5, and current CEO of Accenture Song, for a thoughtful and insightful discussion about AI’s transformative impact on the creativity industry. Together, they tackle the question of whether AI is becoming a critical creative partner for agencies and their clients, or if it’s potentially a threat in certain sectors. They also explore David’s belief that AI could actually be an accelerator and enabler for creatives by eliminating what he calls the ‘mediocre middle’. Listen to the very end and you’ll hear about David’s uplifting and inspirational vision for the future of creativity, and why he thinks true creatives are more relevant in more places than ever, despite the rapid pace of technological change.


Episode Highlights:


9:20 - David explains why he feels not all creativity is worth saving, and how AI will “industrialize the imagination.”


13:32 - Kartik and David discuss how AI is causing business leaders to rethink roles and responsibilities within their organizations. 


18:24 - David explains why he’s still bullish on creative people, but believes creative agencies need to adapt their business models.

]]> It’s a controversial statement, especially coming from the founder of one of the most famous creative agencies in the world: “Not all creativity is worth saving.” But it’s with that bold declaration that this episode of Where AI Works begins.


This time, host Kartik Hosanagar is joined by David Droga, founder of Droga5, and current CEO of Accenture Song, for a thoughtful and insightful discussion about AI’s transformative impact on the creativity industry. Together, they tackle the question of whether AI is becoming a critical creative partner for agencies and their clients, or if it’s potentially a threat in certain sectors. They also explore David’s belief that AI could actually be an accelerator and enabler for creatives by eliminating what he calls the ‘mediocre middle’. Listen to the very end and you’ll hear about David’s uplifting and inspirational vision for the future of creativity, and why he thinks true creatives are more relevant in more places than ever, despite the rapid pace of technological change.


Episode Highlights:


9:20 - David explains why he feels not all creativity is worth saving, and how AI will “industrialize the imagination.”


13:32 - Kartik and David discuss how AI is causing business leaders to rethink roles and responsibilities within their organizations. 


18:24 - David explains why he’s still bullish on creative people, but believes creative agencies need to adapt their business models.

]]> false full 3 1 <![CDATA[Balancing the Algorithm: How AI Is Reshaping Marketing]]> Where can AI have the biggest impact on business outcomes? How can you empower and encourage your employees to experiment with different use cases? What’s the potential role of agentic AI within your organization? Those are among the central questions in this episode of Where AI Works.


For this wide-ranging and comprehensive conversation, host Kartik Hosanagar sits down with Accenture’s Chief Marketing and Communications Officer, Jill Kramer, to discuss how AI is transforming marketing and how companies can adapt to these changes. Jill shares her journey from fear to embracing AI, emphasizing that curiosity and creativity are the key drivers of innovation. She also stresses the importance of “cohorts, communication, and use-cases” when upskilling and reskilling large teams, to ensure everyone is supported through the transformation. Listen to the very end and you’ll hear Jill’s most important piece of advice for any business leader who’s wrestling with the role of AI within their own organization.


Episode Highlights:


5:55 - Jill details the groundwork she did to position Accenture to be ready to take advantage of Gen AI.


12:02 - Jill explains how to empower employees to try new tools and embrace AI without leaving anyone behind.


19:14 - Jill shares her “cohorts, communication, use-cases” strategy for reskilling large 

]]> Thu, 01 May 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 25:08 Where can AI have the biggest impact on business outcomes? How can you empower and encourage your employees to experiment with different use cases? What’s the potential role of agentic AI within your organization? Those are among the central questions in this episode of Where AI Works.


For this wide-ranging and comprehensive conversation, host Kartik Hosanagar sits down with Accenture’s Chief Marketing and Communications Officer, Jill Kramer, to discuss how AI is transforming marketing and how companies can adapt to these changes. Jill shares her journey from fear to embracing AI, emphasizing that curiosity and creativity are the key drivers of innovation. She also stresses the importance of “cohorts, communication, and use-cases” when upskilling and reskilling large teams, to ensure everyone is supported through the transformation. Listen to the very end and you’ll hear Jill’s most important piece of advice for any business leader who’s wrestling with the role of AI within their own organization.


Episode Highlights:


5:55 - Jill details the groundwork she did to position Accenture to be ready to take advantage of Gen AI.


12:02 - Jill explains how to empower employees to try new tools and embrace AI without leaving anyone behind.


19:14 - Jill shares her “cohorts, communication, use-cases” strategy for reskilling large 

]]> Where can AI have the biggest impact on business outcomes? How can you empower and encourage your employees to experiment with different use cases? What’s the potential role of agentic AI within your organization? Those are among the central questions in this episode of Where AI Works.


For this wide-ranging and comprehensive conversation, host Kartik Hosanagar sits down with Accenture’s Chief Marketing and Communications Officer, Jill Kramer, to discuss how AI is transforming marketing and how companies can adapt to these changes. Jill shares her journey from fear to embracing AI, emphasizing that curiosity and creativity are the key drivers of innovation. She also stresses the importance of “cohorts, communication, and use-cases” when upskilling and reskilling large teams, to ensure everyone is supported through the transformation. Listen to the very end and you’ll hear Jill’s most important piece of advice for any business leader who’s wrestling with the role of AI within their own organization.


Episode Highlights:


5:55 - Jill details the groundwork she did to position Accenture to be ready to take advantage of Gen AI.


12:02 - Jill explains how to empower employees to try new tools and embrace AI without leaving anyone behind.


19:14 - Jill shares her “cohorts, communication, use-cases” strategy for reskilling large 

]]> false full 2 1 <![CDATA[The Future of Marketing: AI-Driven Content Creation]]> Media, entertainment, and advertising are among the industries expected to be most impacted by the rise of artificial intelligence. So what better way to kick off our series on the intersection of AI and business than by exploring the potential perks and pitfalls of AI in the world of marketing?

In this premiere episode of Where AI Works, host Kartik Hosanagar is joined by Jonathan Halvorson, the Global SVP of Consumer Experience at Mondelēz International, which owns some of the most recognizable brands in snacking, including Oreo, Nabisco, and Cadbury. Together, they discuss how AI is transforming marketing and brand strategy, and explore some of the most pressing issues for business leaders, like the role of humans in the loop, and fears that AI could lead to more generic content. You’ll also hear specific case studies and concrete advice to help your organization steer clear of what Jonathan calls that “sea of sameness.”


Episode Highlights:


7:40 - Kartik explains how AI isn’t just about reducing costs but can actually lead to more compelling ad content and better outcomes.


14:23 - Jonathan stresses the importance of clearly defining a brand’s identity before utilizing AI tools, including the product’s visual elements, purpose, and core messaging.


17:14 - Jonathan shares details on a hugely successful Mondelēz campaign in India in which AI was used to generate personalized birthday songs for consumers.

]]> Thu, 17 Apr 2025 04:01:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 25:00 Media, entertainment, and advertising are among the industries expected to be most impacted by the rise of artificial intelligence. So what better way to kick off our series on the intersection of AI and business than by exploring the potential perks and pitfalls of AI in the world of marketing?

In this premiere episode of Where AI Works, host Kartik Hosanagar is joined by Jonathan Halvorson, the Global SVP of Consumer Experience at Mondelēz International, which owns some of the most recognizable brands in snacking, including Oreo, Nabisco, and Cadbury. Together, they discuss how AI is transforming marketing and brand strategy, and explore some of the most pressing issues for business leaders, like the role of humans in the loop, and fears that AI could lead to more generic content. You’ll also hear specific case studies and concrete advice to help your organization steer clear of what Jonathan calls that “sea of sameness.”


Episode Highlights:


7:40 - Kartik explains how AI isn’t just about reducing costs but can actually lead to more compelling ad content and better outcomes.


14:23 - Jonathan stresses the importance of clearly defining a brand’s identity before utilizing AI tools, including the product’s visual elements, purpose, and core messaging.


17:14 - Jonathan shares details on a hugely successful Mondelēz campaign in India in which AI was used to generate personalized birthday songs for consumers.

]]> Media, entertainment, and advertising are among the industries expected to be most impacted by the rise of artificial intelligence. So what better way to kick off our series on the intersection of AI and business than by exploring the potential perks and pitfalls of AI in the world of marketing?

In this premiere episode of Where AI Works, host Kartik Hosanagar is joined by Jonathan Halvorson, the Global SVP of Consumer Experience at Mondelēz International, which owns some of the most recognizable brands in snacking, including Oreo, Nabisco, and Cadbury. Together, they discuss how AI is transforming marketing and brand strategy, and explore some of the most pressing issues for business leaders, like the role of humans in the loop, and fears that AI could lead to more generic content. You’ll also hear specific case studies and concrete advice to help your organization steer clear of what Jonathan calls that “sea of sameness.”


Episode Highlights:


7:40 - Kartik explains how AI isn’t just about reducing costs but can actually lead to more compelling ad content and better outcomes.


14:23 - Jonathan stresses the importance of clearly defining a brand’s identity before utilizing AI tools, including the product’s visual elements, purpose, and core messaging.


17:14 - Jonathan shares details on a hugely successful Mondelēz campaign in India in which AI was used to generate personalized birthday songs for consumers.

]]> false full 1 1 <![CDATA[Welcome to Where AI Works]]> In a world of rapid change, staying competitive requires thoughtful transformation. Where AI Works tackles the big questions shaping AI’s role in business today, cutting through the hype to deliver actionable insights for leaders. Brought to you by the Wharton School, in collaboration with Accenture, this podcast combines cutting-edge research with real-world case studies to uncover how top companies are using AI to upskill workforces, enhance customer experiences, boost productivity, and streamline operations. By addressing the challenges of technological disruption and innovation head-on, each episode provides both the big-picture context and practical strategies leaders need to drive transformation responsibly and effectively. Episode 1 launches on April 17th. Don't forget to follow on Apple Podcasts, Spotify, or your preferred podcast app to be notified as episodes drop!

]]> Tue, 11 Mar 2025 11:56:00 -0400 https://knowledge.wharton.upenn.edu/where-ai-works-show/ 1:00 In a world of rapid change, staying competitive requires thoughtful transformation. Where AI Works tackles the big questions shaping AI’s role in business today, cutting through the hype to deliver actionable insights for leaders. Brought to you by the Wharton School, in collaboration with Accenture, this podcast combines cutting-edge research with real-world case studies to uncover how top companies are using AI to upskill workforces, enhance customer experiences, boost productivity, and streamline operations. By addressing the challenges of technological disruption and innovation head-on, each episode provides both the big-picture context and practical strategies leaders need to drive transformation responsibly and effectively. Episode 1 launches on April 17th. Don't forget to follow on Apple Podcasts, Spotify, or your preferred podcast app to be notified as episodes drop!

]]> In a world of rapid change, staying competitive requires thoughtful transformation. Where AI Works tackles the big questions shaping AI’s role in business today, cutting through the hype to deliver actionable insights for leaders. Brought to you by the Wharton School, in collaboration with Accenture, this podcast combines cutting-edge research with real-world case studies to uncover how top companies are using AI to upskill workforces, enhance customer experiences, boost productivity, and streamline operations. By addressing the challenges of technological disruption and innovation head-on, each episode provides both the big-picture context and practical strategies leaders need to drive transformation responsibly and effectively. Episode 1 launches on April 17th. Don't forget to follow on Apple Podcasts, Spotify, or your preferred podcast app to be notified as episodes drop!

]]> false trailer 1