Discover how WHOOP is building an AI-powered health data infrastructure that is redefining how we understand human health. Emily Capodilupo, Senior Vice President of Research, Algorithms, and Data at WHOOP, explains how continuous physiological data is uncovering new opportunities in predictive health through AI, from presymptomatic disease detection to biological age scoring. She examines the governance challenges of deploying AI in a regulated environment and what it takes to build the data trust required to make it work at scale.

Key Moments:

• How WHOOP Built Its AI and Data Foundation (00:57): Emily explains how WHOOP's early focus on elite athlete performance shaped the data collection rigor and multidisciplinary science organization that now powers its predictive health capabilities. She outlines the model she built across AI, machine learning, clinical research, and digital signal processing, and why starting with the highest-demand use case created a data foundation built to scale.
• The Power of Continuous Data (06:21): Emily draws on WHOOP's sleep research to show how continuous physiological data reveals patterns that would be invisible without longitudinal tracking. She shares findings linking sleep architecture to metabolic disease, cancer risk, and cognitive decline, illustrating why the depth and continuity of a data set determine what insights are actually possible.
• The Data Governance Challenge of Acting on Sensitive Data (13:17): Emily shares how WHOOP's respiratory rate data could detect COVID infection up to three days before symptom onset in over 80% of cases, but a denied FDA application left the company holding actionable insights it was legally prohibited from sharing. She examines the governance tension that emerges when your data capabilities move faster than the regulatory frameworks designed to govern them.
• Turning Complex Multi-Signal Data Into a Single Actionable Metric (27:32): Emily introduces WHOOP's Healthspan feature, which translates physiological and behavioral data across nine components into a single biological age score tied to all-cause mortality risk. She explains why distilling complex data into one number is more motivating than presenting raw risk statistics, pointing to research that shows how age-based framing drives stronger behavior change.
• Building Data Trust and Privacy Infrastructure at Scale (31:40): As WHOOP moves into FDA-cleared products and more sensitive data collection, Emily outlines the governance principles that underpin member trust. She argues that for any organization building on sensitive personal data, the asymmetry between earning trust and losing it should be a foundational design constraint.

Key Quotes:

• "It takes 13 years to earn the trust and one mistake to lose it. And that kind of asymmetry is constantly top of mind." - Emily Capodilupo
• "We were able to show that we could detect COVID up to three days before symptom onset in over 80% of cases." - Emily Capodilupo
• “ WHOOP has been collecting data [for] over 12 years. We're working on a lot of new types of algorithms that are able to help people understand their bodies in ways that we might not have appreciated…even just a couple years ago.” - Emily Capodilupo
• "One of the ways that AI has advanced the product... is this ability to chat with WHOOP in natural language, the way you might chat to a doctor or a trainer or a coach." - Emily Capodilupo

Mentions

• Harvard Study | Analyzing changes in respiratory rate to predict the risk of COVID-19 infection 
• Cornell Study Uses WHOOP Sleep Data to Monitor Patients at Risk for Alzheimer’s
• Can Data Help Us Sleep Better? | WHOOP
• There's More to Sleep than Sleep Need: The Importance of Sleep Consistency | WHOOP
• Cribsheet & Expecting Better 2 Books Collection Set By Emily Oster 
• The Family Firm: A Data-Driven Guide to Better Decision Making in the Early School Years By Emily Oster 

Guest Bio 

Emily Capodilupo is an award-winning AI and research leader with more than 13 years of experience building and scaling science-driven organizations in fast-paced startup environments. She began her career as an emergency medical technician before studying neurobiology and human sleep at Harvard University and conducting research at Brigham and Women’s Hospital. Emily is driven by a passion for using data to solve hard problems and advance our understanding of human physiology. Along the way, she "accidentally" became a data scientist, recognizing that the biggest breakthroughs in health require not just rigorous science, but big data and bold technology. 

As WHOOP’s first employee, Emily founded and now leads the company’s science organization, pioneering a new model of health that begins long before diagnosable illness and is continuous, personalized, AI-powered, and designed to empower individuals to take the driver’s seat in their own well-being. She has built and scaled multidisciplinary teams across artificial intelligence, machine learning, digital signal processing, clinical research, and engineering to translate real-time physiological data into actionable insights that improve performance, resilience, and long-term health. Emily’s work sits at the intersection of wearable technology, digital biomarkers, and predictive health, helping shift healthcare from reactive treatment to proactive optimization.

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Learn why scaling AI is as much a human challenge as it is a technological one. Stefano Puntoni, Co-Director of Wharton Human-AI Research and Professor at The Wharton School, examines the limits of data-driven decision making in the age of AI and why insights so often fail to translate into action. He breaks down the psychology behind AI resistance and outlines the leadership and change management strategies needed to turn AI potential into real organizational impact.

Key Moments:

• Why More Data Doesn’t Lead to Better Decisions (02:26): Stefano challenges the assumption that smarter algorithms automatically produce smarter decisions. He argues that decision quality depends on rigorous conceptual thinking before turning to data. Without clearly defining objectives, alternatives, and success criteria, analytics efforts rarely translate into meaningful action.
• Conversational AI and the Lowering of the Cost of Action (07:26): Stefano explains how conversational AI brings decision makers closer to data by reducing friction. By lowering the cost of experimentation, AI enables managers to test hypotheses in real time instead of waiting days for analysis. This shift moves organizations from analysis paralysis to faster, more confident action.
• Rethinking Your Role in the Age of AI (17:16): For professionals navigating disruption, Stefano outlines two paths forward. One is becoming a complement to AI by upskilling and using the technology as a productivity multiplier. The other is pivoting toward skills AI is less likely to replace, such as strategy, orchestration, and human judgment.
• The AWARE Framework: Pairing Technical Rollout with Human Rollout (22:41): Stefano introduces the AWARE framework to help leaders anticipate and manage the human reactions to AI transformation. He argues that every technical implementation must be matched with structured communication, identity support, and organizational alignment. Without this dual-track approach, even well-designed AI systems can fail to gain traction.
• Change Management, AI Literacy, and the Gap in Organizational Readiness (31:11): Only a small percentage of organizations have formal AI change management programs. Stefano questions whether companies are truly prepared for large-scale AI transformation. He emphasizes that AI literacy, leadership accountability, and structured change management will determine whether AI investments translate into sustained performance.

Key Quotes:

• “ The leaders need to know why we are doing AI. AI is not a strategy; AI is just a tool. So what is it that we're trying to achieve?” - Stefano Puntoni
• “ I think the problem is that technology is almost like taking all the oxygen from the room. There's so much attention and urgency around the tech itself that we often forget the people around it.” - Stefano Puntoni
• “You don't want to be the substitute to the technology because if that is what you do, then there's no future. But if you're a complement, the technology might be a multiplier of your productivity.” - Stefano Puntoni

Mentions

• Decision-Driven Analytics: Leveraging Human Intelligence to Unlock the Power of Data
• The Wall Street Journal: The Boss Has a Message: Use AI or You’re Fired
• 2025 Report Accountable Acceleration: Gen AI Fast-Tracks Into the Enterprise
• How AI Affects Our Sense of Self
• Why Gen AI Feels So Threatening to Workers
• Conversational AI: The Next Frontier of Digital Platform Monetization

Guest Bio 

Stefano Puntoni is the Sebastian S. Kresge Professor of Marketing at The Wharton School. Prior to joining Penn, Stefano was a professor of marketing and head of department at the Rotterdam School of Management, Erasmus University, in the Netherlands. He holds a PhD in marketing from London Business School and a degree in Statistics and Economics from the University of Padova, in his native Italy.

His research has appeared in several leading journals, including Journal of Consumer Research, Journal of Marketing Research, Journal of Marketing, Nature Human Behavior, and Management Science. He also writes regularly for managerial outlets such as Harvard Business Review and MIT Sloan Management Review. Most of his ongoing research investigates how new technology is changing consumption and society, including how humans are adopting and evolving with AI.

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Discover how enterprise AI and data strategy are operationalized at scale in one of the most highly regulated industries in the world. Louis DiModugno, Global Chief Data Officer at Verisk, shares how he builds AI-ready data foundations across 40+ petabytes of insurance and risk data, and the best practices behind embedding AI into enterprise products. He discusses unstructured data, deepfakes, and the shift from governance to observability, offering practical insights for data leaders scaling AI responsibly.

Key Moments:

• From Military Leadership to Chief Data Officer: Data Integrity as a Competitive Advantage (03:02): Louis shares how his experience as a U.S. Air Force Colonel has shaped his approach to data governance, data quality, and enterprise AI leadership. He explains why integrity, service, and operational excellence are essential foundations for modern CDOs building trusted, decision-ready data environments.
• Building AI-Ready Data Foundations at a 40+ Petabyte Scale (17:13): Managing more than 40 petabytes of insurance and risk data, Louis breaks down how Verisk transforms complex, multi-source data into AI-ready infrastructure. From entity resolution and master data management to benchmarking and predictive analytics, he outlines what it takes to prepare enterprise data for AI and advanced analytics at scale.
• Designing an AI-First Data Strategy for Enterprise Decision Intelligence (20:00): Louis breaks down how Verisk evolved toward an AI-first data strategy across more than 150 insurance and analytics products. Rather than treating AI as an add-on, he explains how embedding AI into core workflows enables smarter underwriting, pricing, regulatory reporting, and risk management. He also discusses the strategic role ThoughtSpot plays in delivering natural language search, embedded analytics, and scalable AI-driven decision making.
• AI Fraud, Deepfakes, and Risk Management in Financial Services (26:11): As AI-generated images and synthetic claims become more sophisticated, Louis discusses how the insurance industry is combating deepfake fraud and AI-driven manipulation. He shares best practices around AI risk management, vendor partnerships, and regulatory collaboration to protect policyholders and maintain trust.
• Unstructured Data and AI: Why Governance Still Matters (29:28): Louis explores how expanding beyond structured data is reshaping enterprise AI. He explains why incorporating unstructured data into vector databases, graph models, and knowledge systems can significantly improve model accuracy and decision confidence. At the same time, he emphasizes that stronger governance (or observability as he reframes it) is essential as organizations scale AI across regulated industries.

Key Quotes:

• “The more data that you bring to the equation, the more elements that you have in the algorithm, the higher level of accuracy you should be able to reach with your outcomes.” - Louis DiModugno
• “I've tried to move away from using the word governance as much as I like to use the word observability, because I really think observability shows more aspects of what it is that we are doing with the data.” - Louis DiModugno
• “The underlying aspect of what ThoughtSpot's delivering to them is our insights that not only give them their answer, but also give them insights that maybe they weren't looking specifically for. One of the big benefits of ThoughtSpot is that it's trying to anticipate what you're asking for.” - Louis DiModugno
• “We've partnered with ThoughtSpot, which brings AI embedded within its product. By having our data available through the data sets that we populate through the ThoughtSpot products, we've got the opportunity to utilize Spotter and the natural language processing capabilities to interact with the data, so that you can ‘talk with your data’.” - Louis DiModugno

Mentions

• From Months to Weeks: How Verisk Scaled Embedded Analytics
• Breaking Down Digital Media Fraud for Claims in the AI Era
• Randy Bean’s 2026 AI & Data Leadership Executive Benchmark Survey

Guest Bio 

Louis DiModugno brings more than 20 years of career experience in data and analytics to his new role. He has held several leadership positions in insurance and (re)insurance at firms including The Hartford and AXA US, where he served as the company’s inaugural Chief Data & Analytics Officer. Most recently, DiModugno pioneered the role of Chief Data and Technology Officer for Hartford Steam Boiler.

Before entering the private sector, DiModugno served with distinction as a Colonel in the U.S. Air Force and Air Force Reserves. He has held teaching positions at Rensselaer Polytechnic Institute, and he currently serves on the Chief Data Officer Advisory Council for the George Mason University School of Business.

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Learn how AI agents are reshaping enterprise decision-making, AI governance, and brand creativity. Daniel Hulme, Chief AI Officer at WPP & CEO of Satalia/Conscium, explains how AI agents, decision intelligence, and his concept of “brand brains” (AI systems designed to create brand-specific, production-grade content) are changing how organizations operate. He shares why companies don’t have data problems but decision-making problems, and how AI can augment human creativity at scale.

Key Moments:

• From Academic AI Research to Enterprise AI Systems (01:50): Daniel traces his 25-year journey in AI, from studying intelligence and consciousness at UCL to building real-world systems inside global enterprises. He explains how curiosity about what it means to be human ultimately shaped his approach to building practical, responsible AI at scale.
• AI Agents and Risk: Why AI Needs Governance (05:50): Daniel introduces a defining metaphor, describing AI agents as intoxicated graduates—confident, fast, and often wrong. He uses this framing to explain why unchecked agent deployment is risky and why governance, testing, and supervision are essential as organizations scale AI.
• What Most Organizations Get Wrong About AI Testing: (14:00): Daniel breaks down the difference between testing for knowledge versus testing for real capability. He argues that most companies stop at surface-level validation, creating a false sense of safety and trust.
• How AI Changes Business Decision-Making (24:45): Daniel challenges the traditional analytics mindset, arguing that dashboards and insights rarely lead to better decisions. He explains why AI should be designed to make decisions directly and why humans are fundamentally bounded when dealing with complex optimization problems.
• Brand Brains and the Future of Creative Differentiation (30:25): Daniel introduces the concept of “brand brains,” explaining why generic generative AI content won’t create competitive advantage. He shows how agentic systems can produce brand-specific, production-grade content that actually differentiates businesses.

Key Quotes:

• “ There are many things that our brains do that are different to large language models that I think will inspire us to create much more energy-efficient machines.” -  Daniel Hulme 
•  “Giving human beings better insights doesn't typically lead to better decisions… So working backwards from the problem to the data historically, for me, has been a success.” - Daniel Hulme 
•  “The reality is that those agents will go wrong… So there's going to be much more emphasis over the next year or so on governance [and] on making sure that they are capable of doing that job.” - Daniel Hulme 

Mentions

• WPP’s AI “brains”
• Will AI ever be better than humans at predicting what humans want? | WPP
• The Hidden Spring: A Journey to the Source of Consciousness by Mark Solms

Guest Bio 

Dr. Daniel Hulme is a globally recognised expert in Artificial Intelligence (AI) and investor in emerging technologies. He's the CEO of Satalia, an award-winning AI company that was acquired by the world's largest marketing company in 2021, WPP, where he is now the Chief AI Officer. Daniel has been recognised as one of the world's leading keynote speakers as well as one of the top ten Chief AI Officers globally. Amongst his many technology investments, Daniel is also Founder and CEO of the World's first commercial research organisation to understand Machine Consciousness, Conscium.

With over 25 years academic experience with AI, Daniel received his Masters and Doctorate in AI at UCL. He was previously Director of UCL’s Applied AI Masters Programme, where he is now UCL’s Computer Science Entrepreneur-in-Residence. Daniel is also an Impact Board Member of St Andrew’s University Computer Science department and the University of Sussex Informatics department, focused on using AI to solve business and social problems.

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Discover how Nasdaq uses data platforms at a massive scale to power markets and prepare for AI. Angie Ruan, Nasdaq’s CTO of Capital Access Platforms, explains how large-scale data systems support market integrity, transparency, and decision-making across public and private markets. She defines what it really means to be AI-ready, how leaders should modernize data platforms, and how market fundamentals help separate real AI value from hype.

Key Moments:

• Why Nasdaq Is More Than a Stock Exchange (06:10): Angie reframes Nasdaq as a global technology company rather than a traditional exchange, explaining how data, platforms, and engineering underpin trust, resilience, and transparency across public and private markets.
• The Scale of Market Data Powering the Global Financial System (11:15): Angie breaks down the massive scale of Nasdaq’s data ecosystem, including hundreds of billions of market messages per day and platforms supporting more than $90 trillion in assets. She explains how data quality and reliability are foundational to market integrity and decision-making.
• Building a Unified Data Intelligence Platform at Nasdaq (16:35): Angie explains how Nasdaq approaches data architecture, governance, and platform design to create a unified data intelligence layer. She shares why access control, operational efficiency, and data trust matter more than raw data volume when enabling analytics and AI at scale.
• The AI-Ready Playbook for Data and AI Leaders (19:20): Drawing on her experience across startups and large enterprises, Angie outlines a practical framework for data and AI transformation. She emphasizes cloud adoption, breaking down silos, listening to business needs, and treating platform modernization as both a technical and organizational challenge.
• Is AI a Bubble? Using Market Data to Separate Hype from Reality (31:00): Angie applies a data-driven lens to the AI bubble debate, examining earnings growth, margins, return on equity, and capital investment. She explains why current financial indicators suggest today’s AI moment differs fundamentally from past technology bubbles.

Key Quotes:

• “ The foundation of any data strategy is actually cloud… If you don't put the data or the actual system in the cloud, it's much harder in terms of services and platform, let alone AI.” - Angie Ruan
• “Data is great, but the more important [thing]... is how we put it all together.” - Angie Ruan
• “ The world is going to change so fast… Being curious [and] continuing to learn, it is so important.” - Angie Ruan

Mentions

• Inside the Invitation-Only Stock Market for the Wealthy
• Nasdaq eVestment: The Institutional Intelligence Platform Powering $90T+ in Decisions

Guest Bio 

Angie Ruan is the Chief Technology Officer, Capital Access Platforms at Nasdaq. An award-winning industry leader, Ms. Ruan holds four technical patents and has been instrumental in driving digital transformation across many industries, including enterprise application, e-commerce, payment, and capital markets. She most recently served as Vice President of Engineering at Chime before returning to Nasdaq where she was the Senior Vice President of Global Technology, responsible for overseeing the development of Key Market Technology Products and Corporate Platforms. Prior to joining Nasdaq, Ms. Ruan served as the Global Group Technology Vice President of consumer experiences and platform for American Express, where she was responsible for the digital transformation of American Express web and mobile technology. Before then, she was the Unit CIO for U.S. Consumer and U.S. Small Business, and was also Head of Engineering for Global PayPal Retail and Merchant product lines. As well, she held various executive engineering leadership roles at eBay including building the eBay messaging system, creating the eBay mobile platform, and transforming the DevOps organization.

Recognized as one of Silicon Valley's Women of Influence, Ms. Ruan holds an M.S. in Computer Science from the University of California, Santa Barbara, and studied undergraduate in Computer Science at Tsinghua University of China.

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Discover why the future of AI at work is more human than you think. Vinay Gidwaney, Chief Product Officer at OneDigital, shares how treating AI agents as talent rather than technology is changing AI adoption at work. He explains people-first change management, managing AI coworkers, building trust in human AI teams, and why real transformation depends on equity, access, and better decision-making.

Key Moments:

• AI as a Coworker (01:45): Vinay introduces “Ben,” an AI benefits consultant at OneDigital, to illustrate a fundamentally different way of thinking about AI at work. Instead of positioning AI as automation or replacement, he explains how AI coworkers are designed to augment human expertise and support better decision-making.
• Hiring, Training, and Managing AI Like Employees (04:20): Vinay walks through OneDigital’s intern-to-apprentice model for AI, including job descriptions, cultural fit, human managers, and ongoing supervision. He shows how applying HR rigor to AI builds trust, accountability, and clarity while helping employees see AI as part of the team, not a threat.
• Why AI Projects Fail: The Misguided Focus on Tools over Talent (10:45): Vinay argues that AI fails when treated like a traditional IT rollout. He emphasizes that AI adoption is fundamentally a people and change-management challenge, calling on HR leaders to lead the shift in how humans and AI work together.
• Recognizing the Limits and Risks of AI Automation (23:10): Vinay explains why fully autonomous AI agents often fall short in knowledge-based organizations. He cautions leaders to be skeptical of automation-first promises and introduces a more realistic model centered on cognition, human oversight, and thoughtful ROI evaluation.
• The Future of Work in an AI World (38:10):  Vinay reflects on his career and argues that software alone is no longer a defensible moat. He emphasizes speed, insight, services, and human judgment as the true sources of lasting value.

Key Quotes:

• “ If you treat AI like any other technology that you've adopted in your company. It's not going to work out as well as you'd like… It's not a technology thing, it's a people thing.” - Vinay Gidwaney
• “ AI is a great way to spread human talent in your organization because they mirror what your humans are doing.” - Vinay Gidwaney
• “AI is talent and you have to treat AI in the same way that you treat the talent within your organization.” - Vinay Gidwaney

Mentions

• How to Train Your AI ‘Coworker’
• What are AI agent types? How to choose one for your data
• Reconfiguring work: Change management in the age of gen AI

Guest Bio 

Vinay Gidwaney is the Chief Product Officer at OneDigital, a national insurance, employee benefits, HR, and financial services company serving 100,000 employers and 10 million families, with over $1B in revenue. He is responsible for defining and executing the technology and AI strategy as the company reinvents the insurance and wealth management industries with innovative products.

Previously, Vinay led the technology strategy for CIC Health during one of the largest COVID-19 public health campaigns in U.S. history. Collaborating with public partners, he helped set up award-winning vaccination efforts at iconic locations such as Gillette Stadium and Fenway Park, and at numerous community sites, administering 1.2 million COVID-19 vaccinations in less than seven months.

A 2002 winner of the prestigious MIT Technology Review Magazine Top 100 Innovators Under 35 award, Vinay is a proud father to Leela, Niam, Kayvion and Samay.

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In this season premiere of The Data Chief podcast, host Cindi Howson sits down with three industry leaders to unpack what’s next for AI, and the concrete moves data and AI leaders need to make in 2026—many of which are detailed in ThoughtSpot’s Top Data & AI Trends of 2026 ebook.

Get ready for a deep dive into:

• Agentic AI goes mainstream with Paul Baier, CEO and Co-Founder of GAI Insights
• AI-ready data and the rise of the AI manager with Jennifer Belissent, Principal Data Strategist at Snowflake
• Scaling agents with trust and control with Rory Blundell, CEO of Gravitee

Consider this your field guide to navigating AI in 2026.

Key Moments:

• Agentic AI Goes Mainstream with Paul Baier, GAI Insights (1:50): Paul Baier, CEO and Co-Founder of GAI Insights, explains why enterprises that already have GenAI in production are pulling decisively ahead, how agentic AI is reshaping enterprise operating models, and why leadership alignment and AI literacy will determine winners in 2026.
• AI-Ready Data and the Rise of the AI Manager, Jennifer Belissent, Snowflake (19:16): Dr. Jennifer Belissent, Principal Data Strategist at Snowflake, breaks down why data quality, transparency, and governance remain the foundation of AI success, and why the next critical enterprise skill is learning how to manage AI agents as part of the workforce.
• Scaling Agents with Trust and Control with Rory Blundell, Gravitee (35:11): Rory Blundell, CEO of Gravitee, shares how the agentic era is redefining API integration, why most enterprises are stuck at early AI maturity stages, and how agent management and security frameworks will unlock real action in 2026.

Key Quotes:

• “Yo u have to treat AI as a capability and not an IT project.” - Paul Baier
• “ Transparency as a requirement is not slowing down adoption. It's actually accelerating it.” - Jennifer Belissent
• “My prediction is that companies that adopt robust security frameworks in 2026 will be the companies that accelerate fastest.” - Rory Blundell 

Mentions

• GAI Insights’ Corporate Buyers Guide to Enterprise Intelligence Applications
• Harvard Business Review: GAI Insights’ WINS Framework
• Gravitee’s AI Readiness Curve
• ThoughtSpot’s Top Data & AI Trends of 2026 ebook

Guest Bios 

Paul Baier

Mr. Baier is the CEO and principal analyst at GAI Insights. Mr Baier co-authored 4 articles about enterprise GenAI that were featured in Harvard Business Review and MIT Sloan Management Review. He was appointed an Executive Fellow at Harvard Business School and is a Forbes contributor. He is a seasoned software entrepreneur with two decades of experience and multiple exits. Related to AI, he was VP of Product at First Fuel Software, an enterprise AI company for 5 years. He holds an MBA from Harvard and a BA from Kenyon College.

Jennifer Belissent

As Principal Data Strategist, Jennifer advises Snowflake customers on data and AI strategy and best practices in building world-class organizations. Previously, she spent over a decade as a Forrester Analyst, and has held management positions in tech sales and marketing, designed urban policy programs, taught secondary school math as a Peace Corps volunteer, and earned a Ph.D. in political science from Stanford University and a B.A. in econometrics from the University of Virginia.

Rory Blundell

Rory Blundell is the CEO of Gravitee. He joined the company in March 2020, first as Chief Revenue Officer, before becoming CEO in September 2020. Prior to Gravitee, Blundell led SnapLogic's EMEA expansion from a technical sales perspective, overseeing significant growth in EMEA revenues over three years. Prior to SnapLogic, he was the CEO and founder of Velinko, a UK software and consultancy company for the legal and accounting sectors.

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In this special episode, host Cindi Howson pulls together the most useful, and hard-won, lessons from a year of conversations with Data Chiefs leading the GenAI charge. With generative and agentic AI no longer a side experiment, this episode spotlights five practices early adopters can rely on to move from pilots to profit. Expect straight talk on what to prioritize, how to bring people with you, and how to scale AI with the trust, literacy, and guardrails that make impact stick.

Key Moments:

• Tying AI to Real Dollars with Anand Iyer, Ecolab (02:10): Anand cuts through the GenAI FOMO and brings everything back to a simple survival test: if you can’t draw a straight line from an AI initiative to top-line growth or bottom-line savings, it won’t last. His lesson is a sharp reminder that “cool” doesn’t scale, value does. 
• Leading Through Ambiguity with Karen Stroup, WEX (06:01): Karen names what everyone’s feeling: ambiguity is paralyzing. She explains how leaders earn trust by shrinking the unknown into learnable, bite-sized experiments and creating the psychological safety people need to engage instead of resist.
• Building Practical AI Literacy at Scale with Josh Cunningham, Lloyds Banking Group (12:42):  Josh shares how Lloyds Banking Group makes literacy impactful by meeting people where they are. Rather than one-size-fits-all training, they pair broad fundamentals with role-specific learning so every business unit can build confidence in ways that match their actual work. 
• Scaling Responsible Agentic AI with Noelle Russell, AI Leadership Institute (25:09): Noelle steps in with a practical framework for building agentic systems that don’t go rogue. She walks through the POET framework and stresses that responsible AI isn’t a final checkpoint. It’s something you embed from the first idea to production, with guardrails that protect people and outcomes.
• Embedding AI Where Work Happens with Ilan Twig, Navan (32:35): Ilan tells a classic early-adopter story: start with a business problem, move fast, and be ruthless about what needs building versus buying. His lesson is that AI wins when it’s inside the workflow, supporting decisions at the point of impact rather than living in a separate tool. 
• Don’t Let Perfection Stall Progress with Ketan Karkhanis, ThoughtSpot (40:59): Ketan shares a culture gut-check: waiting for perfect metrics, perfect KPIs, or perfect clarity is how progress dies. He argues for visible, trust-building iteration, because in AI, speed to learning beats speed to certainty. 

Key Quotes:

• “One thing that people sometimes forget is that at the end of the day, it's all about are we either saving money or making money? And are you able to show that in the bottom line or the top line in a measurable way?” - Anand Iyer
• “I don't think there's any chief anything officer that should not be considering AI today. I think if you're not considering AI, you are at the risk of being disrupted because you're not going to be learning at the pace with the rest of the industry, and there's someone out there looking for a better way.” - Karen Stroup
• “It’s trying your best to meet people where they are… Finding a way to anchor the [AI] learning to something that's relevant to their day-to-day role is always going to make it land better.” - Josh Cunningham
• “ When people lose 70% of their trust in you, they just don't buy from you, they don't work for you, they don't talk about you… and your business starts to die. I think that trust component is a human component… and it is underpinning all the other philosophies that I have.” - Noelle Russell
• “When you asked me about how to educate yourself on AI, I think that companies must make a decision, and quickly, this or that.” - Ilan Twig
• “ Don't let perfection be the enemy of progress.” - Ketan Karkhanis

Guest Bios 

Anand Iyer

Anand Iyer is the SVP, Chief Data Officer at Ecolab, where he leads the company’s global data and analytics strategy. Based in Mechanicsburg, Pennsylvania, he oversees enterprise data governance, business intelligence, engineering, and advanced analytics to accelerate Ecolab’s digital transformation. Since joining in 2018, Anand has held several senior roles, including VP of Enterprise Architecture and VP of Architecture for Commercial Digital Solutions, helping to scale IoT and data-driven platforms across the organization.

Karen Stroup

Karen joined WEX in 2022 as Chief Digital Officer, a newly created role. She brings more than 15 years of experience leading product management, digital, and innovation organizations focused on software as a service offerings, primarily in financial services.

Josh Cunningham

Josh Cunningham is the Group Head of Data and AI Culture at Lloyds Banking Group, where he leads the Data Culture Pillar—one of five strategic pillars in the Group’s data strategy. He is focused on embedding data-driven mindsets across the organization and empowering teams to unlock the full value of data.

Noelle Russell

Noelle Russell is a multi-award-winning speaker, author, and AI Executive who specializes in transforming businesses through strategic AI adoption. She is a revenue growth + cost optimization expert, 4x Microsoft Responsible AI MVP, and named the #1 Agentic AI Leader in 2025. She has led teams at NPR, Microsoft, IBM, AWS and Amazon Alexa, and is a consistent champion for Data and AI literacy and is the founder of the "I ❤️ AI" Community teaching responsible AI for everyone.

Ilan Twig

Ilan Twig is the co-founder and Chief Technology Officer (CTO) of Navan, the leading modern travel and expense management platform, globally. As CTO, Ilan drives Navan’s product development and engineering efforts, leveraging cutting-edge technologies — including AI — to enhance user experience and operational efficiency. 

Ketan Karkhanis

Ketan Karkhanis is the CEO of ThoughtSpot, the Agentic Analytics Platform company. Prior to joining the company in September 2024, Ketan was the Executive Vice President and General Manager of Sales Cloud at Salesforce. He returned to Salesforce in March 2022 after his time as the COO of Turvo, an emerging supply-chain collaboration platform. 

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Learn how one of the world’s biggest restaurant companies is turning data and AI into a recipe for global innovation. Cameron Davies, Chief Data Officer at Yum! Brands, shares how he’s combining strategy, technology, and change management to drive gobal growth. He explains how Yum! is building AI literacy from the top down, reimagining operations with generative AI, and partnering with NVIDIA to scale innovation. Cameron reveals what true data leadership looks like, balancing bold ideas with business impact, and proving transformation starts with people, not technology.

Key Moments:

• Start with the Business Problem, Not the Tech (04:27): Cameron recalls advice from a mentor, “start with the business problem down, not the technology up.” He emphasizes that innovation only matters when it solves real business challenges, reminding data leaders not to get enamored with the “cool” factor of technology at the expense of impact.
• Balancing Global Scale with Local Agility (07:45): Cameron unpacks the challenge of scaling analytics across 160 countries and four major brands, 98% of which are franchise-owned. He explains how Yum! balances centralization and autonomy, ensuring smaller markets have a voice while global teams leverage shared technology and insights.
• Building AI Literacy from the Top Down (13:44): Cameron describes Yum!’s investment in digital upskilling, from Harvard-led training for executives to hands-on AI workshops for employees. He outlines how the company is embedding AI tools, like Microsoft Copilot and ChatGPT, into daily workflows to build confidence and accelerate adoption.
• Digitizing the Restaurant: Byte By Yum! (17:18): Cameron introduces Byte By Yum!, a suite of proprietary software that simplifies restaurant operations. He explains how it unifies e-commerce, point-of-sale, voice AI, and kitchen systems to make running a restaurant easier and more efficient in an increasingly complex digital environment.
• Partnering with NVIDIA to Power the Future (25:12): Cameron shares how Yum!’s strategic partnership with NVIDIA is fueling next-generation restaurant innovation. He reveals how the collaboration gives Yum! early access to cutting-edge AI engineering and product strategy, extending his team’s capabilities with some of the best minds in the field.

Key Quotes:

• “Technology’s actually a whole lot easier than people, and the more successful the people are, the harder it is to get them to change.” - Cameron Davies
• The business problem is the business problem. You never have as much data as you want, as fast as you want, as cleanly as you want. People are always people, but the opportunities are always the opportunities.” - Cameron Davies
• “I think sometimes we get so enamored with the technology… We forget it’s all in the service of a business problem.” - Cameron Davies

Mentions

• Byte By Yum!
• Yum! Brands to accelerate AI innovation in an industry-first collaboration with NVIDIA
• 2025 AI & Data Leadership Executive Benchmark Survey

Guest Bio 

Cameron Davies currently serves as the Chief Data Officer at Yum! Brands since July 2020. Prior to this role, Cameron held the position of Senior Vice President of Corporate Decision Sciences at NBCUniversal, Inc. from September 2013 to July 2020, overseeing the Corporate Management Sciences and NBCU News Group Insights teams, focusing on advanced analytics and data strategies. 

Cameron's career at Walt Disney Co. spanned from October 1996 to September 2013, where responsibilities included leading the Walt Disney World Resort Forecast and Planning teams and managing global Yield Management. Cameron established and led the Corporate Center of Excellence in Management Science and Integration, collaborating with Disney executives on analytics initiatives. Earlier in the career, from May 1989 to June 1996, Cameron served as a Professor of Finance and Accounting at Pensacola Christian College, teaching various business courses. 

Cameron holds a Master of Business Administration (MBA) in Marketing Research and Operations Management from the UWF Lewis Bear Jr. College of Business and a Bachelor of Science in Business/Accounting from Pensacola Christian College.

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Step inside a conversation on the art and architecture of AI transformation. Vedran Karamani, Group Data Analytics & Agentic AI – CDAIO at Alghanim Industries, shares how he’s embedding intelligence across one of the Middle East’s largest conglomerates. He breaks down what it takes to make AI approachable in the boardroom, why data literacy is now a business imperative, and how to balance innovation with operational reality. Discover how Vedran is redefining the role of data, technology, and human insight in shaping the next generation of enterprise transformation.

Key Moments:

• From Deterministic to Probabilistic Thinking (10:19): Vedran explains how today’s AI shifts decision-making from predictable, rules-based systems to adaptive, probabilistic ones. He shares how leaders must learn to balance control with flexibility to build trust in AI’s potential while managing its unpredictability.
• AI Literacy in the Boardroom (12:55): Vedran emphasizes that real transformation begins with leadership understanding. He shares how he uses storytelling and analogies to educate executives on AI fundamentals, turning abstract concepts like “deterministic vs. probabilistic” into relatable, actionable insights.
• The Readiness Factor (17:29): Not every business is equally prepared for AI. Vedran breaks down the difference between change management and change readiness, urging leaders to assess cultural alignment, technical infrastructure, and data maturity before diving into transformation.
• Data as the Differentiator (25:15): Vedran argues that as algorithms become commoditized, competitive advantage will come from the quality and context of a company’s data. He outlines how clean, well-modeled, and contextualized data will form the backbone of any successful AI strategy.
• The Middle East’s AI Momentum (32:05): Vedran highlights how ambition, experimentation, and government investment are fueling rapid AI growth across the Middle East. He contrasts this energy with slower-moving Western markets, suggesting the region’s “learn fast” mindset could shape the future of global innovation.

Key Quotes:

• "Today, no business has an excuse not to be data-driven.” - Vedran Karamani
• “ With today's AI, we are almost unleashing this immense power that's very probabilistic… We need to learn how to coexist with that and how to leverage it for the greatest benefit of our businesses.” - Vedran Karamani
• “ If you want to stand the chance to have AI help you transform your business, you better get your data to a certain standard for that to be even possible.” - Vedran Karamani

Mentions

• Demis Hassabis, CEO of DeepMind Technologies

Guest Bio 

With over two decades at the forefront of Data Analytics and AI leadership, Vedran Karamani charted a path of innovation across global landscapes, from the dynamic markets of the Middle East to the dynamic tech hubs of North America. Guiding multi-million-dollar portfolios, Vedran pioneered disruptive solutions, propelling sectors like Aviation, Retail, Telecom, Defense, Oil & Gas, Digital, Logistics, and Education into the future.

Renowned for his collaborative leadership approach, Vedran empowered diverse teams to navigate challenges with agility, fostering an environment of continuous growth and individual excellence. From concept to execution, he’s led the charge in delivering game-changing strategies, business cases, and prototypes, ensuring organizations stay ahead in today's rapidly evolving landscape.

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• In this episode of The Data Chief, Ilan Twig, co-founder and CTO of Navan, shares why large language models will revolutionize our relationship with technology—just like the mouse did for the keyboard. From pushing AI to its limits to launching Navan Cognition, built for zero critical hallucination, Ilan reveals what it really takes to lead through change and build AI that people can trust. He also dives into a critical question every company must face: Will you build AI from scratch, or build with AI partners?? And if you're curious about the next frontier, Ilan paints a bold vision of agent-to-agent communication—where AI services talk to each other and your admin work disappears into the background.  A must-listen for anyone building the future of AI-powered user experiences.

Key Moments:

• Agent-to-Agent Communication (A2A) (17:00): Ilan envisions a future where dedicated AI services communicate with each other in natural language, without the need for an API. This "mother of all bots" would manage administrative tasks by talking to other bots, simplifying complex tasks for the user.
• AI as a "Human" Experience (27:16): Ilan was surprised by the release of ChatGPT in 2022 because it was the first time a technology felt human. This led him to spend four months building and testing the technology's boundaries, including its ability to lie or be "jailbroken" with creative prompts.
• Identifying the Core Business (31:43): Ilan advises companies to decide if they want to become an "AI company" or simply use AI. He explains that building a core AI platform requires a huge commitment.
• A Case Study in Building (35:32): The conversation furthers, as a light is shed on the building of “Navan Cognition”, because no solution existed at the time to prevent critical hallucinations in AI models. This system includes a supervisor agent that works to catch and correct undesirable responses, creating a "zero critical hallucination" experience for its users.

Key Quotes:

• "LLMs would do to the mouse what the mouse did to the keyboard when it comes to how humans interact with computers."  - Ilan Twig
• “My role is to always apply the best technology in order to drive, to create the best product and best experience. That's my role. And it is not technology for the sake of technology. It is technology for the sake of creating value for the users." - Ilan Twig
• “We ended up using ThoughtSpot. We also applied the generative AI capabilities that you guys have built into your product. That's build versus buy. That's the benefit of buy.”  - Ilan Twig

Mentions

• Navan Introduces World’s Smartest T&E Personal Assistant
• Navan Cognition
• AI jailbreak method tricks LLMs into poisoning their own context
• Surely You're Joking, Mr. Feynman! (Adventures of a Curious Character)  - Richard P. Feynman

Guest Bio 

Ilan Twig is the co-founder and Chief Technology Officer (CTO) of Navan, the leading modern travel and expense management platform, globally. As CTO, Ilan drives Navan’s product development and engineering efforts, leveraging cutting-edge technologies — including AI — to enhance user experience and operational efficiency. This is Ilan’s second successful venture with Navan CEO Ariel Cohen, following their previous company, StreamOnce, a business multimedia integration platform acquired by Jive Software. With nearly two decades of engineering experience, Ilan has a proven track record of leading innovative research and development teams. He previously held key roles at Hewlett-Packard and Rockmelt, where he managed large-scale engineering initiatives. Ilan holds a Bachelor of Science in Computer Science from the Academic College of Tel-Aviv, Yaffo. As a forward-thinking technologist, Ilan is passionate about integrating AI-driven solutions to redefine the future of corporate travel and expense management.

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