The Data Chief

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. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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 RuanMentionsInside the Invitation-Only Stock Market for the WealthyNasdaq eVestment: The Institutional Intelligence Platform Powering $90T+ in DecisionsGuest 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. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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 GidwaneyMentionsHow to Train Your AI ‘Coworker’What are AI agent types? How to choose one for your dataReconfiguring work: Change management in the age of gen AIGuest 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. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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 InsightsAI-ready data and the rise of the AI manager with Jennifer Belissent, Principal Data Strategist at SnowflakeScaling agents with trust and control with Rory Blundell, CEO of GraviteeConsider 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 MentionsGAI Insights’ Corporate Buyers Guide to Enterprise Intelligence ApplicationsHarvard Business Review: GAI Insights’ WINS FrameworkGravitee’s AI Readiness CurveThoughtSpot’s Top Data & AI Trends of 2026 ebookGuest Bios Paul BaierMr. 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 BelissentAs 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 BlundellRory 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. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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 KarkhanisGuest Bios Anand IyerAnand 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 StroupKaren 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 CunninghamJosh 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 RussellNoelle 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 TwigIlan 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 KarkhanisKetan 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.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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 DaviesThe 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 DaviesMentionsByte By Yum!Yum! Brands to accelerate AI innovation in an industry-first collaboration with NVIDIA2025 AI & Data Leadership Executive Benchmark SurveyGuest 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. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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 KaramaniMentionsDemis Hassabis, CEO of DeepMind TechnologiesGuest 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. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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 TwigMentionsNavan Introduces World’s Smartest T&E Personal AssistantNavan CognitionAI jailbreak method tricks LLMs into poisoning their own contextSurely You're Joking, Mr. Feynman! (Adventures of a Curious Character)  - Richard P. FeynmanGuest 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. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Join us for a masterclass in building data-driven marketing cultures. Moe Kiss, Director of Data Science in Marketing at Canva, shares how she bridges analytics and storytelling to make data approachable across teams. She breaks down the shift from attribution to experimentation, why storytelling is a must-have skill for every data professional, and how to balance intuition with evidence. Discover how Moe’s redefining the balance between technology, trust, and empathy in data leadership.Key Moments:Data as “Part of the Meal” (09:09): Using a cooking analogy, Moe describes how data should be integrated into decision-making, not as a garnish or afterthought, but as part of the meal itself. She highlights Canva’s culture of balancing intuition with data, ensuring both creative instinct and analytics inform every decision.Storytelling as a Data Superpower (10:57): Moe breaks down her “insight headline” method, turning flat dashboards into stories that drive action. She argues that data storytelling isn’t about aesthetics but understanding, and that trust comes from how clearly insights connect to business impact.Technical Fluency in the Age of AI (18:16): While some leaders claim programming is obsolete, Moe insists it’s more important than ever. Understanding what’s under the hood helps data professionals vet AI outputs, maintain data quality, and confidently guide stakeholders through rapid technological change.Buy vs. Build: The Cost–Benefit Equation (20:11): Moe breaks down how Canva evaluates when to build internal tools versus buy off-the-shelf solutions. She stresses that the best answer depends on scalability, cost, and time to market — and that implementation costs are often underestimated.AI’s New Role in Marketing (24:48): Moe shares how AI is reshaping marketing teams and their relationship with data. She highlights how generative AI tools can democratize access to insights, but warns that without trusted, high-quality data foundations, AI can just as easily amplify mistakes.Key Quotes:"Data is about creativity…It’s not about it being pretty, it’s about being understood.” - Moe Kiss“ We are leveraging AI tools more, and so understanding what's under the hood, I would say, is more essential than ever.” - Moe Kiss“[Know] the business appetite. You need to know how to get the answer with the right level of certainty or uncertainty…at pace with the business.” - Moe KissMentionsAnalytics Power Hour PodcastWhy Are Semantic Layers Suddenly Sexy?The Agentic Semantic Layer and OSI: A New Standard for AIThoughtSpot Joins Forces with Snowflake and Industry Leaders to Spearhead Open Semantic Interchange, Ushering in a New Era of Data and AI InteroperabilityGuest Bio Moe is a Director of Data Science in Marketing at Canva. Prior to that, she was in senior product and marketing analytics roles at THE ICONIC and in an attribution agency, Datalicious. Moe is passionate about growing and developing data scientists, driving industry leading measurement techniques and tooling and expanding the business impact of her team.She is a passionate and active member of the analytics community, co-hosting a bi-weekly podcast, the Analytics Power Hour. She served as the president of the Analytics Association of New South Wales for 7 years and is an ongoing committee member where she helps run Data Analytics Wednesday, a monthly meet up, and Sydney MeasureCamp, yearly unconference. She won the Digital Analytics Association USA's top new practitioner award in 2018. In 2024 was nominated in the Women Leading Tech Awards in the Data Science category and was awarded Snowflake's Data Hero of the Year award. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Welcome to a special author's episode of The Data Chief, where we delve into the minds of three influential authors who are shaping the conversation around data and AI. First, Geoff Woods, author of The AI-Driven Leader, shares his philosophy of prioritizing strategy over technology to make faster, smarter decisions. Next, Wendy Batchelder, author of The Data Governance Handbook, discusses how to transform governance from a rigid bureaucracy into a business accelerator by focusing on business outcomes. Finally, Malcolm Hawker, author of The Data Hero Playbook, challenges data leaders to adopt a heroic mindset by becoming customer-driven and aligning their incentives with business success. Join us to learn how to lead effectively in the AI era by building a strategy-driven, governed, and customer-centric data function.The Data Chief Podcast: Author Episode Key MomentsGeoff Woods: The AI-Driven LeaderFrom "IT Problem" to Strategic Partner (06:20): Woods advocates for viewing AI as a "strategic thought partner" rather than an assistant or replacement, and emphasizes that AI strategy must align with business strategy.The CRIT Framework for Smarter Prompts (12:25): He introduces the CRIT framework for prompt engineering: Context, Role, Interview, Task. This method helps leaders get non-obvious, high-impact strategies from AI by having the AI ask the right questions.Beyond the Bottom Line: AI's Human Impact (22:17): Woods discusses the ROI of AI, including a case where AI identified savings equivalent to 2% of a company's revenue. Wendy Batchelder: The Data Governance HandbookData Governance as an Accelerator (32:33): Wendy Batchelder addresses the myth that data governance is a "dirty word" or a code for "no," arguing that its true purpose is to be an accelerator.Speaking the Language of Business (35:17): Batchelder emphasizes that data governance should be embedded from the start of a project, not as an afterthought. She provides an example of "bad" vs. "good" communication, urging data professionals to speak the language of the business.Measuring Value with Business Outcomes (40:00): She outlines how to measure the value of data governance by connecting it to business outcomes like increased revenue or improved customer service. Malcolm Hawker: The Data Hero PlaybookFrom Limiting Mindset to Growth Mindset (56:00): Hawker discusses why he wrote the book, calling the current moment a "do or die" opportunity for CDOs. He challenges the "limiting mindset" that leads to defeatism.Customer-Driven, Not Data-Driven (1:08:00): He urges data leaders to be "customer-driven, not data-driven," emphasizing the need for data teams to become more business literate.The Power of Product Management (1:14:00): Hawker advocates for bringing product management disciplines into data teams. This approach focuses on putting the customer at the center and ensures that data products are economically viable and tied to ROI.Key Quotes:"It is not technology first, strategy second. It is strategy first, technology second.” - Geoff Woods"The companies that are treating data as something that helps drive business outcomes are thinking about data at the beginning and set up at the end." - Wendy Batchelder“If you deliver value to your customers, if you are the lever of change and transformation in your organization, if you show value from data, you will get a seat at the table." - Malcolm HawkerMentionsThe AI-Driven Leader: Harnessing AI to Make Faster, SmarterHow AI is transforming strategy developmentData Governance Handbook: A practical approach to building trust in data5 key reasons why data analytics is important to businessThe Data Hero Playbook: Developing Your Data Leadership SuperpowersCDOs and CDAOs: Rethink your role or fade awayGuest Bios:About Geoff Woods Geoff Woods is the #1 bestselling author of The AI-Driven Leader, host of the AI-Driven Leader podcast, and Founder of AI Leadership and The AI-Driven Leadership Collective™, a highly vetted network of executives collaborating to harness AI to build better businesses and better lives. As the former Chief Growth Officer of Jindal Steel & Power, Geoff's strategic leadership helped the company grow its market cap from $750 million to over $12 billion in just four years. Prior to that, he co-founded the training and consulting company behind The ONE Thing, advising businesses ranging from $10 million to $60 billion in annual revenue.About Wendy Batchelder Wendy Batchelder is a three-time Chief Data Officer across financial services, technology & healthcare industries, with a wide understanding of how to take highly technical aspects of data management and translate them into simple, concise business valued solutions that are practical and simple to understand. Her background has led her to lead global data & analytics organizations at four Fortune 500 companies. She approaches situations with curiosity and humility, which has led to applying innovative data solutions to challenges with increased complexity to deliver value that companies can measure.A lifelong learner, Wendy graduated from Miami University with a B.S. in Accounting and Information Systems, from Drake University with a Masters of Accountancy, from University of Iowa with an Executive MBA, and pursues ongoing education through Harvard Business School. Her work history includes EY, KPMG, Aviva, Wells Fargo, VMware and Salesforce.About Malcolm HawkerMalcolm helps senior business leaders harness the power of data to transform their businesses. As a former Gartner analyst, he has consulted with some of the world's largest and best-known brands on their enterprise information management strategies and digital transformation initiatives.He is a frequent public speaker on data and analytics best practices with a passion for Master Data Management (MDM) and Data Governance. He welcomes the opportunity to share practical and actionable insights on how companies can become truly data-driven by implementing the cultural, technical, and organizational changes needed for success in the digital age. He is also the author of The Data Hero Playbook. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Join us for a compelling conversation on leading through change with Karen Stroup, Chief Digital Officer at WEX. In this episode of The Data Chief, Karen shares her insights on navigating the complexities of AI adoption. She discusses why focusing on the customer problem is more important than simply applying new technology, how to build trust by accounting for the "human side" of data, and why her team uses a "two-way door decision" to combat the rapid pace of tech change. Discover her "hot take" on the future of analytics, where dashboards become a "backdrop" and an interactive, predictive experience takes center stage.Key Moments:Navigating Ambiguity with People (06:02): Karen argues that leaders' primary role is to build confidence and help people navigate ambiguity. She explains that people fear the unknown more than change and suggests involving employees in the journey to help alleviate that fear.Trust and the Human Side of Data (14:30): She highlights that giving a correct answer is not the same as building confidence that it's the right answer. Karen discusses the importance of accounting for the "human side" of how people feel about the information they receive.Prioritizing AI use cases (22:48). Karen describes WEX's approach, which starts with a top-down cultural shift from the CEO, and then uses filters like value, feasibility, and desirability to prioritize projects.The "Two-Way Door Decision" for Technology (28:13): To combat the disconnect between rapid technology evolution and slow cultural change, Karen discusses using a "two-way door decision". This approach involves architecting solutions to be vendor-agnostic, allowing the company to pivot if a technology proves to be unsuccessful."Hot Take" on the Future of Analytics (35:34): Karen's "hot take" is that the user experience will fundamentally change. She predicts that dashboards will become a "backdrop," while an interactive, predictive experience will move to the foreground.Key Quotes:"Very few customers, whether it be a business or a consumer, say, I want an AI solution. What they're really saying is, I want the problem to be simpler." - Karen Stroup"Answering the question correctly is not the same as building confidence that it's the right answer to the question." - Karen Stroup"Being able to understand data, but in a way that resonates with them, is really important. I do think ThoughtSpot does this well in the sense that you may get one answer, and you say, 'Hey, can you explain that for me?' or 'Where does the data come from?' But that ability to 'peel the onion' is really important." - Karen StroupMentions:WEX's Health and Benefits platformAgentic AI in Financial Services: The future of autonomous finance solutionsTrillion Dollar Coach: The Leadership Playbook of Silicon Valley's Bill CampbellHow Much Data Does a Ring Security Camera Use?Guest Bio: 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.As Chief Digital Officer, Karen is responsible for expanding digital commerce opportunities by harnessing best-in-class product development, design, and digital transformation capabilities from across the enterprise. In addition to creating a unified strategic vision, she leads a team that executes against digital strategy initiatives and strives to create exceptional customer experiences by delivering new digital tools, platforms, and technologies.Prior to WEX, Karen served as the Chief Digital Officer at Thomson Reuters. Prior to her role at Thomson Reuters, Karen served as SVP, Product and Innovation at Capital One Financial Services and VP, Product Management at Intuit. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

The next generation of analytics is here. In this episode of The Data Chief, ThoughtSpot CEO Ketan Karkhanis explains why AI is the new BI, and the future of analytics is autonomous. Karkhanis shares his vision for the autonomous enterprise, where AI agents act on insights and automate workflows.  He also explains why a culture of trust and experimentation is crucial for unlocking AI's full potential. Don't miss this discussion on how to fundamentally rethink how organizations interact with data to drive better business outcomes and build an autonomous enterprise.Key Moments:AI is the New BI (08:35): Ketan explains that AI represents a “foundational rewiring” of the entire technology stack, a shift he calls Cloud 2.0. He predicts the BI market is on the verge of an “upgrade super cycle,” leaving legacy players behind.AI Becomes the Only UI (20:45): Ketan shares his vision that in the future, AI will become "the only UI you will need". He explains that ThoughtSpot’s MCP host can bring together structured data, unstructured data, and world knowledge to provide better context for a user's question.Progress over Perfection (25:56): Leaders are reminded not to let “perfection be the enemy of progress.” For Ketan, a culture of trust and openness to experimentation is more important than having perfectly defined KPIs or flawless dashboards.Training Comes First (29:02): One of the biggest lessons learned was the importance of investing in people before chasing the promise of AI outcomes.  After rolling out mandatory generative AI training, new use cases began emerging organically from across the business—proof that education fuels innovation.Outcomes Over Tech (38:47): Despite mountains of legacy technology, many organizations remain starved for actionable insights. Ketan points to EasyJet as an example of getting it right: rather than focusing on systems and infrastructure, they designed their AI initiative around a tangible outcome—avoiding flight cancellations.The Rise of the Autonomous Enterprise (42:56): The next frontier is the autonomous enterprise, where AI agents don’t just surface insights but also act on them. Ketan envisions a future where humans are freed from mundane tasks to focus on higher-value work like relationships and judgment calls.Key Quotes:"AI becomes the only UI you will need." - Ketan Karkhanis"It's not about AI. It's about ROI." - Ketan Karkhanis"This is no longer just about BI. This is about agents that are driving workflows in your organizations." - Ketan KarkhanisMentions:Go Boundaryless Product SpotlightThoughtSpot Agentic MCP Server Lex Fridman PodcastTeam of Rivals: The Political Genius of Abraham LincolnThe Path Between the Seas: The Creation of the Panama CanalGuest Bio: Ketan Karkhanis is the CEO of ThoughtSpot. 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. Before that, Ketan spent nearly a decade at Salesforce, where he led product areas in Sales, Service Cloud, Lightning Platform, and finally Analytics, wherein as the Senior Vice President & GM of Einstein Analytics, he pioneered incredible innovation, customer success, and business acceleration from launch to over $300M and a 30,000 strong user community. Prior to Salesforce, Ketan was at Cisco Systems where he led various technology initiatives and initiatives spanning Customer Advocacy, Cisco Certifications & eLearning. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Hear how data is rewriting the rules—and driving the future of innovation. Dr. Vanja breaks down his approach to enterprise AI, and the key strategies for success. He shares what it means to be a “data-forward organization” and why data must sit at the heart of how a company operates. Discover why integration speed is the new competitive edge Key Moments:Data as a Core Enterprise Asset (6:04): Dr. Vanja defines what it means to be a “data-forward organization,” emphasizing that data shouldn’t be an afterthought—it must sit at the heart of how a company operates, makes decisions, and serves customers.Relational Foundation Models for Predictive AI (16:26): Dr. Vanja explains how Kumo uses transformer architectures on raw relational data to eliminate 95% of traditional ML tasks like feature engineering—bringing pre-trained, multi-purpose prediction models into the structured data world.Integration Speed as a Competitive Edge (27:03): It's no longer just about who builds the fastest—but who integrates the fastest. Dr. Vanja shares how companies that can quickly adopt and scale best-in-class third-party tools will define the next generation of winners.The Case for Rebuilding at 10x Advantage (29:02): Dr. Vanja urges leaders to rethink old systems if a new approach offers a 10x cost or performance improvement. Sticking with outdated architectures out of fear or inertia risks falling behind during pivotal transitions.Key Quotes:“The key asset is the data that you have… You need to build the whole enterprise around this data. It’s not an afterthought — it’s at the center of the organization and how it functions.” - Dr. Vanja“Companies that integrate the fastest — not just build the fastest — will win.” - Dr. Vanja“If you really value your data, you need to stay in the cloud… If the cost is your only driver, then do what you want — but you’ll miss out on the majority of new technologies.” - Dr. VanjaMentions:Build AI Models for Relational DataThe New Cloud Era of Data Platform Hosted AppsKumo unveils world's first Relational Foundation Model (RFM) for instant predictions on enterprise dataGuest Bio: Dr. Vanja Josifovski is the Co-Founder and CEO of Kumo. Prior to Kumo, Vanja was the CTO at Airbnb & Pinterest. Here, Vanja led an organization that included horizontal groups such as Homes Engineering and Homes Data Science, as well as GM groups such as Marketplace, Relevance and Personalization, and Regulatory Frameworks. Before Airbnb, Vanja was the CTO & VP Eng at Pinterest, responsible for the overall technical vision and strategy of the company and communicating that to leadership and the teams; hiring and development of technical talent. As the head of Engineering, he managed some core engineering teams. Vanja has also served as an advisor and investor for multiple startups and was the founder for Kosei, which was acquired by Pinterest. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Join us for expert insights on driving data-led change. Anand Iyer, Senior Vice President and Chief Data Officer at Ecolab, breaks down his approach to AI-powered innovation. He shares how to ensure AI initiatives directly impact the bottom line, why an engineering approach is key for prioritizing AI use cases, and that "garbage in, disaster out" is the new reality for data at AI scale. Discover how self-service analytics with AI is transforming data access and why AI is now a critical "business forcing function" in today's volatile world.Key Moments:The "Value First Mindset" for AI (03:13): Despite the hype around AI, initiatives must directly impact the top or bottom line in a measurable way. Sustained investment requires a clear link between the AI initiative and its financial value, moving beyond "soft benefits."Engineering Mindset for Prioritization (11:27): Anand discusses how an engineering approach is applied to prioritizing AI use cases, which helps teams focus on thoroughly understanding the problem and desired outcome before selecting a solution. "Garbage In, Disaster Out" (14:27): A new take on an old adage is introduced: "in the AI world is garbage in and disaster out". This highlights the magnified risks of bad data when leveraged at AI scale.Advocacy for Self-Service Analytics with AI (24:10): Self-service analytics is championed, describing how the integration of AI and conversational AI allows users to ask questions regarding the data. This removes the need for IT involvement in report generation and simplifies the learning curve for data structures.AI as a Business Forcing Function (33:38): In today's volatile global environment, near real-time data and AI-driven insights are no longer optional but a "business forcing function". Rapid reactions to market disruptions, policy changes, and supply chain issues are critical for a company's survival and success.Key Quotes:"If you want to have a seat at the table, you've got to be able to talk in terms of what the value is in terms of dollars." - Anand Iyer“We've deployed ThoughtSpot technology to be able to provide self-serve analytics to our teams, which allows them to have access to the data. This enables them to have conversational questions.” - Anand Iyer"The role that data, analytics, and AI play is the ability to give business leaders access to impact and what they should do in a very timely manner so that they can minimize any impact to business." - Anand IyerMentions:Before You Ask an AI Chatbot for Depression Advice, Read This'Garbage in, Garbage out': AI Fails to Debunk Disinformation, Study FindsThe Bhagavad Gita - By Bed VyasGuest Bio: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.With over 14 years of experience in data architecture and digital innovation, Anand has a proven track record of aligning technical solutions with business outcomes. Prior to Ecolab, he held leadership roles at GE Healthcare Digital, CSRA Inc., and CSC. He holds an engineering degree from the National Institute of Technology Rourkela and is known for building high-performing teams and cultivating a data-first culture that drives smarter, more sustainable decisions. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Prepare for game-changing AI insights! Join Noelle Russell, CEO of the AI Leadership Institute and author of Scaling Responsible AI: From Enthusiasm to Execution. Noelle, an AI pioneer, shares her journey from the early Alexa team with Jeff Bezos, where her unique perspective shaped successful mindfulness apps. We'll explore her "I Love AI" community, which has taught over 3.4 million people. Unpack responsible, profitable AI, from the "baby tiger" analogy for AI development and organizational execution, to critical discussions around data bias and the cognitive cost of AI over-reliance.Key Moments: Journey into AI: From Jeff Bezos to Alexa (03:13): Noelle describes how she "stumbled into AI" after receiving an email from Jeff Bezos inviting her to join a new team at Amazon, later revealed to be the early Alexa team. She highlights that while she lacked inherent AI skills, her "purpose and passion" fueled her journey."I Love AI" Community & Learning (11:02): After leaving Amazon and experiencing a personal transition, Noelle created the "I Love AI" community. This free, neurodiverse space offers a safe environment for people, especially those laid off or transitioning careers, to learn AI without feeling alone, fundamentally changing their life trajectories.The "Baby Tiger" Analogy (17:21): Noelle introduces her "baby tiger" analogy for early AI model development. She explains that in the "peak of enthusiasm" (baby tiger mode), people get excited about novel AI models, but often fail to ask critical questions about scale, data needs, long-term care, or what happens if the model isn't wanted anymore.Model Selection & Explainability (32:01): Noelle stresses the importance of a clear rubric for model selection and evaluation, especially given rapid changes. She points to Stanford's HELM project (Holistic Evaluation of Language Models) as an open-source leaderboard that evaluates models on "toxicity" beyond just accuracy.Avoiding Data Bias (40:18): Noelle warns against prioritizing model selection before understanding the problem and analyzing the data landscape, as this often leads to biased outcomes and the "hammer-and-nail" problem.Cognitive Cost of AI Over-Reliance (44:43): Referencing recent industry research, Noelle warns about the potential "atrophy" of human creativity due to over-reliance on AI. Key Quotes:"Show don't tell... It's more about understanding what your review board does and how they're thinking and what their backgrounds are... And then being very thoughtful about your approach."  - Noelle Russell"When we use AI as an aid rather than as writing the whole thing or writing the title, when we use it as an aid, like, can you make this title better for me? Then our brain actually is growing. The creative synapses are firing away." Noelle Russell"Most organizations, most leaders... they're picking their model before they've even figured out what the problem will be... it's kind of like, I have a really cool hammer, everything's a nail, right?"  - Noelle RussellMentions:"I Love AI" CommunityScaling Responsible AI: From Enthusiasm to Execution - Noelle Russell"Your Brain on ChatGPT" - MIT Media LabPower to Truth: AI Narratives, Public Trust, and the New Tech Empire - StanfordMeta-learning, Social Cognition and Consciousness in Brains and MachinesHELM - A Reproductive and Transparent Framework for Evaluating Foundation ModelsGuest Bio: 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.She is the founder of the AI Leadership Institute and empowers business owners to grow and scale with AI. In the last year, she has been named an awardee of the AI and Cyber Leadership Award from DCALive,  the #1 Thought Leader in Agentic AI, and a Top 10 Global Thought Leader in Generative AI by Thinkers360. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Tune in for a masterclass in data leadership. Josh Cunningham, Group Head of Data and AI Culture at Lloyds Banking Group, unveils how this distinguished institution is boldly innovating with cutting-edge AI. Josh provides a riveting look into his unique role, which is dedicated to accelerating talent, building capabilities, and articulating data and AI's profound impact across the organization. Learn how Lloyds is rapidly expanding its data and AI graduate scheme and learn more about their ambitious quest to be the "most data literate bank". Hear how their innovative five-persona literacy framework, and engaging initiatives like the "Data and AI Summer School" and a physical "Data Escape Room," are driving their business forward on data and AI.Key Moments: The "People Side" of Data and AI (12:33): Reflecting on his career, Josh highlights his passion for the "people side" of data and AI, focusing on building teams and fostering career development. This addresses a critical industry gap where technology readiness often outpaces human capability.Scaling Data and AI Talent (17:23): Lloyds Banking Group significantly scaled its data and AI graduate scheme from approximately 10 to 100 graduates annually over three years, while demonstrating a proactive approach to balancing between AI training and tool adoption for their increasing talent pool.Data and AI Literacy Framework (22:52): Lloyds developed a data and AI literacy framework with five personas, from "data beginner" to "citizen," representing an evolving maturity lifecycle. This framework helps map and track colleagues' literacy levels over time.The Data and AI Summer School (29:06): Josh highlights this major, two-month, virtual program that offers over 200 live sessions hosted by internal and external experts. It covers diverse data and AI topics for all colleagues, from beginners to practitioners, and has attracted over 42,000 sign-ups in the previous year.The Physical Data Escape Room (32:18): Lloyds innovated with a physical data escape room that tours the UK, designed to engage colleagues (even those disengaged with data). Its puzzles, anchored to the entire data value chain, enable "learning by stealth" with phenomenal feedback. Key Quotes:"It's trying your best to meet people where they are and make it real for them. So... finding a way to anchor the learning to something that's relevant to their their day to day role, is always gonna make it land better." - Josh Cunningham"I think every organization needs to find a really well-structured balance in terms of training versus adoption." - Josh Cunningham"If I was to think about our data and AI literacy framework, we've developed a framework that consists of five personas. We've tried to break it down in terms of where people might be on their data or AI literacy journey. You can go from data beginner through to data enthusiast, through to data and AI explorer, through to storyteller, through to citizen. - Josh CunninghamMentionsLloyds Banking Group - Escape RoomLloyds Banking Group's partnership with Women in Data Lloyds Banking Group's partnership with Code First Girls The AI Daily Brief PodcastGuest Bio: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.Josh spearheads a range of initiatives, including enterprise-wide data literacy programs, innovative talent attraction efforts, and collaboration events that foster a culture of experimentation and learning. With a background in data and a deep commitment to talent development, he is passionate about transforming how large organizations cultivate data careers, scale innovation, and use insights to shape the future of banking. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Step inside the world of data innovation as Don Vu, SVP and Chief Data and Analytics Officer at New York Life, reveals how a 180-year-old institution is embracing cutting-edge AI. Don, shares insights from his unique background, spanning Major League Baseball and retail startups, now applied to transforming the insurance industry. Hear how New York Life leverages AI to make experiences proactive and intelligent, addressing challenges like the "last mile problem" in data operationalization. Key Moments: MLB Data Insights (07:28): The conversation delves into how every baseball stadium is extensively instrumented with high-speed camera and radar technology, meticulously tracking every object on the field. This massive trove of data is then shared across all baseball clubs for in-depth analysis and the optimization of strategies.The Last Mile Problem (09:38): A critical challenge in data and AI is identified as the "last mile problem," emphasizing that the primary hurdles often lie in the operationalization, change management, adoption, and acceptance of solutions, extending far beyond the mere building of models.Data & AI in Business Strategy (13:08): The discussion highlights that data serves as the fundamental underpinning for seamless operations, while AI actively transforms experiences, making them proactive and intelligent. This deep integration of AI and data is central to New York Life's core business strategy.Data Readiness & Quality (20:08): Persistent data readiness issues are addressed, underscoring that data quality, latency, governance, and stewardship—with business owners held accountable—are absolutely crucial for both structured and unstructured data environments.AI Interoperability & Agent-Driven Future (22:43): The episode explores the importance of tracking emerging AI protocols such as MCP (Model Context Protocol) and agent-to-agent protocols. A compelling vision of the future is also shared, where AI agents act on behalf of consumers. Realizing this vision depends on interoperability across AI systems, enabling smooth, intelligent collaboration between diverse platforms.GuideMe Application & AI (32:46): New York Life's innovative "GuideMe" tool, utilized by agents during client meetings, is described as possessing incredible potential for pervasive AI integration. This integration is set to significantly supercharge both the agent and client experience, streamlining financial planning.Key Quotes:“There is this phrase that data practitioners often cite. It's like this notion of garbage in, garbage out. And data quality matters. The latency of your data is significantly important. The notion of data governance and data stewardship, with a business owner being accountable for the quality of data, is really important." - Don Vu“We think human-led protection-first holistic advice and guidance is really the key here, and we have amazing advisors, we have amazing agents throughout the country, and what we're really focused on is really enhancing them and trying to make their lives easier by having AI at their side.” - Don Vu“Data is the underpinning foundation upon which that runs seamlessly and consistently. AI is the way by which it becomes proactive and intelligent across the entire set of experiences.” - Don VuMentionsHow New York Life’s “Guide Me” is Leading the Way in Digital TransformationRockaway Beach: New York’s Best Kept SecretLeading Change: By John P. KotterDiner: South Williamsburg, Brooklyn RestaurantGuest Bio Don Vu is the Senior Vice President and Chief Data and Analytics Officer at New York Life. In this role, Don leads the company's artificial intelligence (AI) and data team, overseeing AI, data, and insights initiatives and ensuring data architecture supports New York Life's business objectives. Prior to joining New York Life, Don served as chief data officer at Northwestern Mutual, where he spearheaded organizational transformation and enterprise data and AI strategy. His impressive career also includes leadership positions at WeWork as vice president of data and analytics and 13 years at Major League Baseball (MLB) as vice president of data and analytics. Don holds a B.S. in Information Systems and Commerce from the University of Virginia and actively contributes to the field as an advisory board member for McIntire's Business Analytics program. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Step into the future of policing where data is a mission-critical asset. Cindi Howson talks with Aimee Smith, Director of Data at the Metropolitan Police, about the Met’s bold data transformation—from digitizing records dating back to 1829 to using AI and cloud tech for smarter, faster decisions. Hear how initiatives like the V100 program and real-time analytics help improve city safety. Key Moments: Genesis of the Met’s Data Strategy (03:35) - The Met's data strategy's origin is traced to former Commissioner Cressida Dick's leadership, who envisioned leveraging data to transform policing, leading to a program building data capabilities and broadening analytics use beyond traditional intelligence and performance applications.  Mission with Data and AI (13:34): The Met's overarching mission to use data and AI for precise decision-making is articulated, acknowledging the complexity of policing's multiple goals: crime prevention, incident response, organized crime intervention, victim service, and custody safety.  Infrastructure Evolution (15:18): The transformation of the Met's data infrastructure over 5 years, from 8 separate operational systems to an integrated one with cloud technology adoption, is described, enhancing analytics and data science capabilities.  V100 Initiative (19:58): The V100 initiative, a data and analytics effort to reduce violence against women and girls by prioritizing individuals with a history of harm, is explained.  Concert Security Powered by Analytics (27:50): The use of ThoughtSpot by frontline officers is illustrated with a sergeant's innovative application for analyzing crime data around events like the Taylor Swift Eras tour to improve policing plans.  AI Agent Development (36:37): An innovative project to build an AI agent that assists frontline officers at crime scenes by providing real-time guidance is outlined, aiming to improve public protection and investigative outcomes.  Key Quotes:“So if an officer wants to start being able to do their own searches, creating their own sort of planners, thinking about doing their own trend analysis essentially, of crime data, which is great, isn't it? I mean, that's just exactly how you want ThoughtSpot to be used. Every officer has access to that.” - Aimee Smith"I like to think of it as a utility belt—you know how cops wear their utility belt? Well, hanging on there is this ThoughtSpot tool. A sergeant invented a way to use it for planning major events, concerts, to make sure our presence is right. And now that's replicable by other people who want to do the same thing." - Aimee Smith"One of the 5 principles of our business strategy for London to keep it safe is to be more precise in the use of data for decision making. So it's a high-level principle of our strategy. That makes data and analytics much harder, because there aren't enough data specialists and too many data parts to point at all those missions in one go.” - Aimee SmithMentionsMet Police’s V100 InitiativeMet Police Develops an Open Data Strategy with the Open Data InstituteMet Police’s Concert Preparation for Taylor Swift’s Eras Tour Cressida Dick Reflects on Public Trust in the Digital Age The Data Protection ActGuest Bio Aimee Smith's distinguished career in the Metropolitan Police Service (MPS) spans almost a quarter-century, truly a testament to her profound dedication to integrating robust data into the very core of police decision-making. She embarked on her journey in 2001 as an Intelligence Analyst, steadily rising through the ranks. By 2014, her leadership capabilities led her to head UK Policing’s largest Confidential Intelligence Unit. A pivotal "light-bulb moment" crystallized for her the critical importance of effective data management in driving operational outcomes, inspiring her to passionately spearhead the comprehensive MPS data transformation program. In a landmark achievement, Aimee was appointed as the first Director of Data for the MPS, where in 2019, she successfully established the inaugural Data Office within law enforcement, fundamentally reshaping how the service leverages its information. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Embark on an insightful exploration of the hospitality sector, powered by data-driven analysis. Cindi Howson and Hyatt's data trailblazer, Ray Boyle (Vice President, Data and Analytics), are charting a course through Hyatt's data innovation. Witness how Hyatt's four-pillar data strategy is revolutionizing everything from employee empowerment to guest personalization and operational efficiency. Discover how Hyatt is democratizing data with self-service tools and pioneering an AI-powered frontier to redefine the very essence of hospitality!Key Moments: Data as an Asset (08:26): Ray emphasizes the importance of shifting the organizational mindset to view data not as a cost center, but as a critical asset. He discusses how data should be cared for, invested in, and stored like any other valuable asset, with the expectation of generating value for the business.  Hyatt's Data Strategy Pillars (13:00): Ray outlines the four key pillars that form the foundation of Hyatt's data strategy. These pillars include cultivating people and building a data-driven culture, personalizing the guest and customer experience in a high-trust environment, operating with excellence by ensuring operational efficiency and information consistency, and growing with intent by integrating new businesses and data flows.  Key Milestones in Hyatt's Data Transformation (16:42): Ray details the significant milestones in Hyatt's data transformation journey. These include clarifying the data strategy, establishing the data and AI operating model, building data governance capabilities, modernizing the data platform and infrastructure, expanding data assets, and releasing new services like personalization and forecasting.  Data Democratization and Data Fluency (23:00): Ray explains Hyatt's strong emphasis on self-service analytics to empower users across the organization. He discusses the importance of data accessibility, trustworthiness, and usability, as well as the potential of generative AI to further democratize data access and insights.  This includes building a data community to facilitate knowledge sharing and learning, as well as providing tooling and guidance to business organizations to effectively roll out analytics within their domains.  AI's Impact and Collaboration (31:35): Ray explores the transformative impact of AI on businesses and its role in fostering tighter collaboration between business and technology teams. He discusses how AI is driving the need for reimagined workflows and how it's changing the way data is used and delivered across the organization.Key Quotes:“ThoughtSpot has been a key partner of ours on that journey. We just roll the data into the cloud, and we're working to publish our assets, sales, finance, loyalty, revenue, search, and marketing into that infrastructure so that there's just a growing base of information that everybody can use in the self-service context.” - Raymond Boyle"Velocity is something you build over time. It's how I think about the operating model around data, ensuring everyone plays their role and develops the necessary skills. To me, velocity increases as you establish the operating model and you have the business, technology, and data organizations, along with governance and security, all participating effectively. - Raymond Boyle"When you think about the business outcomes and how people are beginning to consider AI's potential in that transformation, I believe AI is becoming a more significant factor every quarter." - Raymond BoyleMentionsThe Four V’s of Big Data, Including VelocityDalva, By Jim HarrisonMinnesota Timberwolves’ SuccessGuest Bio Ray Boyle (current Vice President, Data and Analytics at Hyatt) has enjoyed a distinguished career spanning several industries and roles across consulting, software, analytics, and data leadership. His notable roles include leading strategic planning, research, and analytics for Walmart’s Sam’s Club division; serving as Vice President of Walmart Global Customer Insights and Analytics; Vice President of Walmart’s Global Data and Analytics Platform; Vice President leading FICO’s global retail and CPG practice; and Executive Vice President heading IRI’s Global Shopper Analytics and Services team.Since 2019, Ray has served as Vice President, Data and Analytics at Hyatt. Aligned with Hyatt’s purpose — to care for people so they can be their best — his ambition is to elevate and scale that care through data-driven decisions and automation that benefit guests, customers, owners, and colleagues.Guest Bio Ray Boyle (current Vice President, Data and Analytics at Hyatt) has enjoyed a distinguished career spanning several industries and roles across consulting, software, analytics, and data leadership. His notable roles include leading strategic planning, research, and analytics for Walmart’s Sam’s Club division; serving as Vice President of Walmart Global Customer Insights and Analytics; Vice President of Walmart’s Global Data and Analytics Platform; Vice President leading FICO’s global retail and CPG practice; and Executive Vice President heading IRI’s Global Shopper Analytics and Services team.Since 2019, Ray has served as Vice President, Data and Analytics at Hyatt. Aligned with Hyatt’s purpose — to care for people so they can be their best — his ambition is to elevate and scale that care through data-driven decisions and automation that benefit guests, customers, owners, and colleagues. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.