Where AI Works: Conversations at the Intersection of AI and Industry

• 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.

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• 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.

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• 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.

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• 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.

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• 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.

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