The Data Chief

• From Building at Pinterest and Airbnb to Revolutionizing AI at Kumo.AI

  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 Sticking with outdated architectures out of fear or inertia risks falling behind during pivotal transitions.Key Quotes:“The key asset is the data that you have… You need to build the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.

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• Why "Garbage In, Disaster Out" is AI's New Reality: Ecolab CDO

  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.

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• Why Leaders Need to Master Responsible AI: Insights from Pioneer Noelle Russell

  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.

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• How Lloyds Banking Uses Data Escape Rooms to Build a Data Culture

  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.

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• How a CDAO goes from baseball to insurance with Don Vu - New York Life

  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.

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