CDO Magazine
500 episodes listed below
Enterprise AI after the strategy slide.
CDO Magazine Podcast Series follows data and AI leaders through the operating realities behind enterprise transformation. The conversations favor practical detail: governance, adoption, risk, vendor evaluation, data products, and the long path from promising pilot to scaled business value.
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CDO Magazine Podcast Series is a serious enterprise data and AI interview series focused on what happens after the strategy slide. It follows leaders who are trying to move AI, analytics, and data products through large organizations with legacy systems, risk controls, global teams, and real business expectations. The pacing is measured. Guests are allowed to build full explanations rather than reduce transformation to slogans. Recent episodes spend considerable time on financial services, global companies, healthcare, and enterprise examples, with conversations about Truist, Henkel, City of Hope, Schneider Electric, and Daimler. The recurring concern is scale. AI tools arrive quickly, but institutions still have to decide which problems are worth solving, which vendors can be trusted, and which operating models need to change. The series is especially attentive to the gap between pilots and production. It treats that gap as a business, governance, and architecture problem, not just a technical handoff. In the financial services episodes, Sanjay Sankoli frames AI success around augmentation, workflow acceleration, regulatory posture, and the limits of old platform architectures. In the Henkel conversations, Katrin Bootsen describes data products, catalogs, shared definitions, and the challenge of making data reusable across a global business. City of Hope adds a healthcare lens, where Nassim Eftikari emphasizes patient impact and performance before efficiency or return on investment. Schneider Electric’s Philippe Grandard brings the focus back to change management, education, and knowing when a model’s accuracy is good enough for the process at hand. The show can be dense, but that density is part of its value. It gives enterprise practitioners a way to hear how peers talk through ownership, confidence, procurement, domain expertise, and measurable outcomes. It is best suited to listeners who want operating reality rather than AI theater. The conversations are technical, but they keep circling back to adoption, trust, and business value.
Made for: Built for data, analytics, AI, technology, risk, and business leaders working in or around large organizations. It suits listeners who want practical enterprise lessons rather than introductory AI explainers.
What sets it apart: The series stands out by giving practitioners time to explain the organizational mechanics behind data and AI adoption. It repeatedly connects architecture, governance, compliance, culture, and measurable business outcomes instead of treating them as separate conversations.
The CDO Magazine Podcast Series is a one-of-a-kind series of data-world debates conducted by and for CDOs. The podcast series covers a wide range of topics, including machine learning, artificial intelligence, data technology, the Internet of Things, and robotics. Podcasts range from mini episodes covering high-level themes to longer, in-depth interviews with practicing data professionals and leaders. No matter where you are in your data science career, staying up to date on the latest in data and how it is gaining significant attention is always a good idea. To remain up to date, subscribe to the CDO Magazine Podcast Series.
Based on 4 episodes we listened to · September 2026
Senior enterprise leaders explain how data foundations, governance, and operational priorities turn AI plans into systems organizations can use.
CDO Magazine Podcast Series keeps enterprise AI close to the systems and decisions that determine whether it works. Its interviewers ask senior technology and data leaders to connect strategy with implementation, moving from competitive advantage and business priorities to…
This is where enterprise AI meets its less photogenic relatives: data models, controls, and power grids.
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Short reviews from the PlayNext desk, based on the episodes we processed.
Enterprise AI matters here only when it works across scale, regional complexity, and mixed business models.
Henkel's AI story is treated as an operating problem, not a showcase. Katrin Boten walks through a global company with deep history and shows how AI reaches supply chain work, finance, procurement, and customer recommendation tools.
A grounded enterprise case for getting the data foundation in place before chasing the next layer.
This episode stays on the tension between enterprise data and confident action, with Mars as the concrete backdrop. It keeps circling the same point: the foundation has to be in place, the common data model matters, and the back end sometimes has to catch up before the front end…
Enterprise AI is framed through energy efficiency, demand balancing, and customer value.
The episode treats AI at Schneider Electric as a business choice first and a model story second. Philippe Rambach presents the company as large and international, then keeps the focus on what AI can do for the existing strategy: customer value, energy savings, decarbonization,…
Enterprise AI still depends more on the data layer than the model layer.
CDO Magazine treats enterprise AI as a data and control problem first, and Jyoti Chawla keeps that point in view. Her case is plain enough: vendors, models, and frameworks change fast, so the lasting work sits in data quality, semantic understanding, and human oversight rather…
Markets, macro, AI, and crypto in motion.
Daily AI news through the lens of trust, infrastructure, and real-world deployment.
Murali Vimapalli contrasts data infrastructure with decision infrastructure as the difference between insights and outcomes.
Karan Jain, founder and CEO of Naya One, opens a CDO Magazine interview with Sanjay Sankoli, Chief Architect for AI and Data at Trust Bank, on how enterprises evaluate AI tools.
This interview explores how Henkel implements data and AI transformation by aligning ownership, governance, and culture while leveraging cloud infrastructure and analytics.
Sanjay Sankoli, Chief Architect for AI and Data at Truist Bank, describes where enterprise AI is delivering measurable results across front, middle, and back office functions.
Nassim Eftikari, who leads Applied AI and Data Science at City of Hope National Cancer Center, explains how oncology AI is evaluated, prioritized, and measured for real-world impact.
This episode features an interview with Edgar Gallo, Chief Data Officer at Daimler Truck North America, discussing the practical challenges and strategies for implementing AI adoption in large organizations, focusing on change management and building trust.
Katrin Boten, Henkel's head of data and AI, explains to Julian Schirmer why AI matters across a 47,000-plus-employee global company with adhesive technologies and consumer brands.
This episode explores why many AI initiatives fail to progress beyond pilot stages, featuring insights from an AI architect in financial services on practical applications and enterprise-scale transformations.
This interview with Schneider Electric's Chief AI Officer explores the challenges and best practices of AI transformation, emphasizing that 80-90% of it involves change management rather than just technology.
CDO Edgar Galla discusses AI agents and their application in manufacturing, focusing on safety frameworks and a specific aftermarket use case.
A discussion on the gap between data and insights, focusing on adoption challenges in data-driven solutions.
An interview with Edgar Gallo, CDO at Daimler Trucks, discussing data management and AI in the trucking industry.
Apoorva Vadotkar discusses the Data Buffet framework for driving adoption of data products in an organization.
Interview with Schneider Electric's Chief AI Officer about the company's AI transformation journey and how AI drives efficiency.
Ujwal Sehgal and Rachel Bellino from Mars' People Analytics function explain how they close the gap between enterprise data and actionable insight.
This episode features an interview with a Fortune 500 AI governance leader discussing how to define success metrics and set realistic expectations for AI deployment by focusing on customer needs, business goals, and proper guardrails.
This episode discusses AI governance strategies, including the division of responsibilities between central teams and development pods, focusing on security, privacy, architecture, and legal aspects.
An interview with GE Healthcare's Chief AI Officer discussing edge AI concepts and their applications in medical devices.
Julian Schirmer opens the conversation by asking why AI matters for Schneider Electric.
A discussion with Mars leaders on bridging the gap between data and actionable insights in people analytics.
A CDO interview discussing the necessity of data quality, lineage, and governance before leveraging large language models.
Apoorva Vadodkar, Senior Director and Head of Data and AI at TI Automotive, describes the 5E framework she developed for building AI practices from scratch: Educate, Engage, Experiment, Expedite, and Effectuate.
An interview with Patrick McQuillan, a data governance and responsible AI leader, discussing his career journey and expertise.
This episode features an interview with GE Healthcare's Chief AI Officer discussing the current inflection point in healthcare AI, focusing on the shift from experimental models to embedded systems and the rise of agentic AI for coordinating complex tasks.
An interview with Justin Marsico, Assistant Commissioner for Fraud Prevention at the U.S.
Data still does the heavy lifting.
A CDO interview discussing challenges and advice for emerging data leaders on driving transformation despite legacy systems and cultural resistance.
Kevin Barbosa interviews Ajay from Johnson & Johnson about AI and data innovations transforming global services.
This interview discusses the U.S.
An interview with Justin Marsico, Assistant Commissioner for Fraud Prevention at the U.S.
An interview discussing automatic cost optimization in Snowflake and the role of data leaders in managing complexity.
An interview discussing how to build data ecosystems that enable AI to add value, focusing on fostering a data-informed culture and conveying ROI to stakeholders.
A CIO and CDO discuss the role of enterprise browsers in access security and user experience.
A CDO interview discussing data governance, AI ethics, and empowering business leaders in project selection at AstraZeneca.
A CDO interviews Nebraska's State CIO about innovative data talent initiatives, including split intern models and partnerships with education.