Meet the world’s top data and analytics leaders transforming how we do business. Hear case studies, industry insights, and personal lessons from the executives leading the data revolution.
Join host Cindi Howson, Chief Data Strategy Officer at ThoughtSpot, every other Wednesday to meet the leaders and teams at the cutting edge.
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Canva’s Moe Kiss on Why Creativity Is the Missing Ingredient in Data
Épisode 123
mercredi 22 octobre 2025 • Durée 40:17
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Technical Fluency in the Age of AI (18:16): While some leaders claim programming is obsolete, Moe insists it’s more important than ever.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 Kiss
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.
3 Must-Read Data and AI Books for 2025 with Geoff Woods, Wendy Batchelder, and Malcolm Hawker
Épisode 122
mercredi 8 octobre 2025 • Durée 01:21:27
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 Moments
Geoff Woods: The AI-Driven Leader
From "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 Handbook
Data 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.
Why CDO of WEX Puts People Before Technology in the Age of AI
Épisode 121
mercredi 24 septembre 2025 • Durée 43:21
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
Unlocking the Autonomous Enterprise, with ThoughtSpot CEO
Épisode 120
mercredi 10 septembre 2025 • Durée 45:41
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.
From Building at Pinterest and Airbnb to Revolutionizing AI at Kumo.AI
Épisode 119
mercredi 20 août 2025 • Durée 32:53
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. Vanja
Mentions:
Why "Garbage In, Disaster Out" is AI's New Reality: Ecolab CDO
Épisode 118
mercredi 6 août 2025 • Durée 40:26
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
Why Leaders Need to Master Responsible AI: Insights from Pioneer Noelle Russell
Épisode 117
mercredi 23 juillet 2025 • Durée 57:32
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.
How Lloyds Banking Uses Data Escape Rooms to Build a Data Culture
Épisode 116
mercredi 9 juillet 2025 • Durée 49:38
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.
How a CDAO goes from baseball to insurance with Don Vu - New York Life
Épisode 115
mercredi 25 juin 2025 • Durée 39:40
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.
How the Met Police Uses AI to Prevent Crime and Protect Communities
Épisode 114
mercredi 11 juin 2025 • Durée 45:04
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
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 Playbook
From 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 Hawker
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 Hawker
Malcolm 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
"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 Stroup
Karen joined WEX in 2022 as Chief Digital Officer, a newly created role. She brings more than 15 years of experience leading product management, digital, and innovation organizations focused on software as a service offerings, primarily in financial services.
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.
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.
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.
"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 Iyer
Anand Iyer is the SVP, Chief Data Officer at Ecolab, where he leads the company’s global data and analytics strategy. Based in Mechanicsburg, Pennsylvania, he oversees enterprise data governance, business intelligence, engineering, and advanced analytics to accelerate Ecolab’s digital transformation. Since joining in 2018, Anand has held several senior roles, including VP of Enterprise Architecture and VP of Architecture for Commercial Digital Solutions, helping to scale IoT and data-driven platforms across the organization.
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.
"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 Russell
Noelle Russell is a multi-award-winning speaker, author, and AI Executive who specializes in transforming businesses through strategic AI adoption. She is a revenue growth + cost optimization expert, 4x Microsoft Responsible AI MVP, and named the #1 Agentic AI Leader in 2025. She has led teams at NPR, Microsoft, IBM, AWS and Amazon Alexa, and is a consistent champion for Data and AI literacy and is the founder of the "I ❤️ AI" Community teaching responsible AI for everyone.
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.
"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 Cunningham
Josh Cunningham is the Group Head of Data and AI Culture at Lloyds Banking Group, where he leads the Data Culture Pillar—one of five strategic pillars in the Group’s data strategy. He is focused on embedding data-driven mindsets across the organization and empowering teams to unlock the full value of data.
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.
“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 Vu
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.
"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 Smith
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.
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