CDO Magazine Podcast Series
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.
Why AI Changes Unstructured Data: Data X-Ray’s Kyle DuPont on Metadata Intelligence
Kyle DuPont, Founder and CEO of Data X-Ray, speaks with Maribeth Achterberg, CDO Magazine Editorial Board Member, about how AI is changing the value of unstructured data. The conversation focuses on metadata, file relevance, and how enterprises can help users and agents find the information needed for specific workflows.
AI Agents Join the Workforce: Muralidhar Vemulapalli on Why They Need Accountability
In the final episode of this three-part series, Muralidhar Vemulapalli, Chief Enterprise Architect and Acting Chief Technology Officer at Arkansas Blue Cross Blue Shield, tells Chris Gengo, Chief Innovation Officer at HiLabs, why AI approving eighty percent of prior authorization requests does not mean reviewers can step back. Vemulapalli lays out the decision-centric architecture, funding discipline, and governance principles health plans need to move AI from pilot to production. The conversation closes with a forecast on which health plans will still be processing claims by the next decade and which will be preventing the risks behind them.
Why Better Data Beats Bigger AI Models: Enterprise AI Executive Rohit Chauhan
Rohit Chauhan, former Executive Vice President of Artificial Intelligence & Fraud Solutions at Mastercard, tells Robert Lutton, Vice President of Sandhill Consultants, why a more powerful AI model will not fix fraud detection on its own. Chauhan argues that trust in AI comes from the data architecture underneath it, not from the model's output, and explains how connected context can flip a flagged transaction into a normal one.
AI Governance Makes Innovation Scalable in Trust: Insights from Muralidhar Vemulapalli
In this CDO Magazine interview, Muralidhar Vemulapalli, Chief Enterprise Architect and Acting Chief Technology Officer at Arkansas Blue Cross Blue Shield, tells Chris Gengo, Chief Innovation Officer at HiLabs, why ungoverned AI cannot be deployed at enterprise scale. Vemulapalli lays out the governance model, from AI inventory to human-in-the-loop review, that turns fast models into trustworthy infrastructure. The conversation also covers why provider data is becoming a competitive differentiator instead of a compliance checkbox.
No Use Case, No Value: Mindfuel CEO Nadiem von Heydebrand on Proving AI ROI
Enterprise leaders frequently fail to justify data investments because they report on technical outputs rather than commercial outcomes. In this video, Mindfuel CEO Nadiem von Heydebrand joins CDO Magazine Editorial Board Member Justin Heller to solve this operating model problem. The discussion provides a clear framework for tracking AI value to prove true return on investment to the board.
Fraud Detection Now Depends on Connected Data Architecture: Former Mastercard AI & Fraud Solutions EVP
Banks continue investing in more sophisticated fraud models, yet many still struggle to keep pace with increasingly connected fraud schemes. In Part 1 of this three-part interview series, Rohit Chauhan, former Executive Vice President of Artificial Intelligence & Fraud Solutions at Mastercard, explains to Robert Lutton, Vice President of Sandhill Consultants, why connected data architecture has become the foundation for trusted Enterprise AI and modern fraud detection.
AI Readiness Starts With Decision Infrastructure: Arkansas Blue Cross Blue Shield's Murali Vemulapalli
Muralidhar Vemulapalli, Chief Enterprise Architect and Acting Chief Technology Officer at Arkansas Blue Cross Blue Shield, tells Chris Gengo, Chief Innovation Officer at HiLabs, why most health plans generate insight but never turn it into an operational decision. Vemulapalli argues that AI governance and a unified data fabric matter less than the decision infrastructure and shared accountability that actually move outcomes. This is part one of a three-part CDO Magazine conversation on enterprise AI strategy in healthcare.
Who Owns AI Context in the Enterprise? Carrier Global's Arun Nandi Weighs In
In the final episode of this three-part series, Carrier Global Chief Data Officer Arun Nandi joins Flexor Co-Founder and CEO Or Zabludowski to explain how centralized AI governance and decentralized context ownership can work together inside a large enterprise. Nandi also unpacks why large language models have commoditized domain knowledge once locked inside departing employees and legacy vendors, and why senior executives are increasingly building their own AI prototypes instead of waiting on IT teams.
AI for AI's Sake: Mindfuel CEO Nadiem von Heydebrand on Filtering Real Use Cases from the Noise
Many AI initiatives deliver outputs, yet struggle to generate sustained business value. In this conversation, Nadiem von Heydebrand explains why organizations must shift from project-based thinking to product-based execution and why identifying the right use cases remains one of the biggest challenges in enterprise AI.
Nadiem von Heydebrand, CEO & Co-Founder of Mindfuel, joins Justin Heller, Editorial Board Member at CDO Magazine, to discuss continuous ROI, demand management, and the operational discipline required to prioritize high-value AI opportunities.
The Cost of Rigid Ecosystems: Carrier Global Arun Nandi on Avoiding Long-Term AI Technical Debt
As enterprises race to deploy AI, many risk creating technical debt that will be difficult to unwind in the future. Arun Nandi, CDO at Carrier Global, explains why open standards, architectural flexibility, and trusted data products are becoming essential for sustainable AI adoption. Nandi joins Or Zabludowski, Co-founder and CEO of Flexor, to discuss governance, enterprise architecture, and emerging talent models shaping the next generation of AI organizations.
From Insights to Action: Ashutosh Katiyar on Scaling Next Best Action in Pharma
Scaling Next Best Action platforms across diverse therapeutic areas requires solving the critical challenge of field-level user adoption.
In this interview, Commercial Strategy, Insights & Analytics Executive Ashutosh Katiyar and Subrata Chatterjee, Global Growth Partner for Life Sciences at Tiger Analytics, reveal how explainable AI drives enterprise trust. Discover how embedding invisible analytics directly into existing commercial workflows eliminates operational friction and accelerates decision-making velocity.
AI Governance as an Innovation Accelerator: Carrier CDO Arun Nandi on Scaling Agentic Execution
As organizations face a massive wave of agentic AI adoption, managing technical debt and platform sprawl has become a critical priority for enterprise tech leaders. In this episode, Carrier Global Chief Data Officer Arun Nandi and Flexor CEO Or Zabludowski explore how to transition from traditional data structures to open, agent-optimized architectures. The discussion outlines how robust AI governance can serve as an operational accelerator rather than a bureaucratic bottleneck.
Output Is Easy, Outcomes Are Hard: Mindfuel CEO Nadiem von Heydebrand on Proving AI Value
Enterprise data teams frequently focus on generating technical output rather than delivering true business outcomes. Mindfuel CEO and Co-Founder Nadiem von Heydebrand shares insights with Justin Heller, a CDO Magazine editorial board member, on how to isolate core operational problems to quantify real business value. This discussion provides a clear framework for executing data strategy based on performance metrics instead of mere capability development.
Building Trusted Self-Serve Analytics for Better Commercial Decisions with Ashutosh Katiyar
In this interview, Subrato Chatterjee, Global Growth Partner for Life Sciences at Tiger Analytics, talks with Commercial Strategy, Insights & Analytics Executive Ashutosh Katiyar, about overcoming user adoption hurdles in decentralized data systems. Katiyar explains how embedding natural language querying into existing workflows eliminates the need for tool retraining while maintaining central data governance. The conversation provides a blueprint for transforming data analysts from information gatekeepers into strategic advisor
Data Governance as an AI Accelerator: Databricks Leader Molly Just-Behr on Public Sector Readiness and Trust
Organizations often focus on AI ambitions before addressing data readiness, governance, and trust. In this conversation, Molly Just-Behr explains why AI success depends on strong data foundations, transparent governance, workforce development, and cross-agency data sharing.
Molly Just-Behr, Global Head of Public Sector at Databricks, joins Dr. Adita Karkera, Chief Data Officer for Government and Public Services at Deloitte, to discuss how public sector organizations can responsibly scale AI while maintaining accountability and mission focus.
Databricks Public Sector Leader on Achieving Mission Success Through Unified Data and AI Platforms
Government organizations are under pressure to deliver greater impact with limited resources. In this conversation, Molly Just-Behr explains why unified data and AI foundations are becoming essential for improving mission outcomes, increasing efficiency, and reducing operational risk.
Dr. Adita Karkera, Chief Data Officer for Government and Public Services at Deloitte, interviews Molly Just-Behr, Global Head of Public Sector at Databricks, about democratizing data access, modernizing legacy environments, and building momentum for AI adoption across government agencies.
Shifting to Proactive Intelligence: Regeneron’s Ashutosh Katiyar on Commercial Analytics
The best analytics teams do more than explain the past. They help shape the future.
What happens when commercial analytics shifts from reporting historical performance to enabling proactive decisions?
In this conversation with Subrato Chatterjee, Global Growth Partner for Life Sciences at Tiger Analytics, Ashutosh Katiyar, Executive Director, Commercial Strategy, Insights & Analytics at Regeneron, shares how organizations can build intelligence capabilities that identify signals early, support scenario planning, and create stronger connections between analytics and patient outcomes.
The AI Trust Playbook: Monte Carlo's Barr Moses on Governing Autonomous Agents and Upskilling the Enterprise
AI can automate workflows. It can also amplify risk if trust and governance fall behind.
In the last episode of the interview series with CDO Magazine Editorial Board Member Justin Heller, Monte Carlo CEO Barr Moses explains why data quality, workforce readiness, and AI governance will determine which enterprises lead the next phase of transformation.
Procter & Gamble VP Jeff Goldman on Driving Algorithmic Superiority and Mitigating Model Risk
How does Procter & Gamble scale AI safely while maintaining a competitive edge? Enterprise AI VP Jeff Goldman shares how the company manages model risk and drives continuous algorithmic innovation.
Enstar Group CDO David Tuppen on Why Data Foundations, Not AI Tools, Determine Success at Scale
AI tools are becoming commoditized. Data foundations are not.
Enstar Group CDO David Tuppen explains why governance, automation, and trusted data matter more than the next AI platform.
PODCAST | P&G’s Jeff Goldman on AI Fluency, Enterprise Adoption, and Measuring AI Impact
In Part 2 of this three-part conversation, Jeff Goldman, VP, Enterprise Data Science at Procter & Gamble, joins Donna Medeiros of Data Society Group to discuss what it really takes to scale AI across a global enterprise.
Goldman explains how P&G built long-term AI fluency programs, launched internal generative AI tools like ChatPG, and trained more than 20,000 employees through its decentralized Formula AI initiative.
The conversation also explores:
Why business sponsorship drives AI prioritizationThe measurement challenge behind scaling AIWhat separates scalable AI initiatives from stalled pilotsHow AI is reshaping teamwork and innovationListen now.<...
PODCAST | Monte Carlo CEO on Why Trusted Data Is Becoming the Foundation of Autonomous AI
As AI agents move deeper into enterprise workflows, organizations are confronting difficult questions around autonomy, oversight, security, and trust.
In Part 2 of this three-part conversation, Monte Carlo CEO Barr Moses joins data leader Justin Heller to examine:
The priorities dominating CDO agendas todayWhy AI-ready data foundations matter more than everHow AI agents are accelerating data operationsWhere human intervention still plays a critical roleWhy security and reliability continue to make or break enterprise AI initiativesA practical discussion on what responsible AI deployment actually looks like at enterprise scale.
PODCAST | Enstar Group CDO on Why AI Adoption Fails Without Business-Owned Data Foundations
In this episode, Enstar Group Chief Data Officer David Tuppen discusses the realities of enterprise modernization inside highly regulated environments and why AI success still depends on trusted data foundations.
Topics include:
Simplifying complex data estatesGovernance and privacy by designWhy AI exposes poor data qualityReducing manual processes and Excel dependencyThe evolving mandate of the CDOWhy business ownership is critical for adoptionIn conversation with Robert Lutton, Vice President at Sandhill Consultants.
PODCAST | Qlik + Deloitte on the Next Five Years of AI: Why Durable Enterprise AI Will Win
Former Qlik CEO Mike Capone joins Deloitte’s Dr. Adita Karkera for the final part of our three-part
series on the future of enterprise AI.
The conversation explores:
• Agentic AI use cases delivering value today
• Board-level AI leadership expectations
• Why trusted partnerships matter more than ever
• How Qlik + Deloitte view the next five years of AI transformation
Listen now.
PODCAST | How P&G Is Scaling Enterprise AI Without Losing Local Business Context
What does it actually take to scale AI inside a global enterprise?
In this episode, Donna Medeiros, Vice President of AI and Data Advisory at Data Society Group, speaks with Jeff Goldman, Vice President, Enterprise Data Science at Procter & Gamble, about how P&G operationalizes AI through a combination of data science, AI engineering, and its AI Factory model.
The conversation covers:
• Enterprise AI operating models
• Scaling AI across global markets
• Embedding AI teams into the business
• Why infrastructure and engineering determine AI success
• How P&G measur...
PODCAST | How Health Plans Can Balance AI Innovation, Governance, and Patient Outcomes
As healthcare organizations race to operationalize AI, leaders must balance innovation with governance, interoperability, and patient outcomes.
In this episode, former L.A. Care Health Plan CIO Tom MacDougall speaks with Robert Lutton of Sandhill Consultants about responsible AI adoption in healthcare, why organizations are still in the early stages of operational AI maturity, and how trusted, standardized data will define the next phase of healthcare transformation.
The discussion also explores:
• AI governance in regulated environments
• Real-world healthcare analytics use cases
• Provider benchmarking and care optimization
• The role of...
PODCAST | Massachusetts CDO Karthik Yajurvedi on Building Cross-Agency Data Trust
In the final part of this three-part CDO Magazine series, Karthik Yajurvedi, Chief Data Officer for the Commonwealth of Massachusetts, joins Deloitte’s Adita Karkera for a conversation on what it really takes to operationalize data sharing across government agencies.
The discussion explores governance without bottlenecks, building trust across silos, context-based data quality in the age of AI, and why modern CDOs must increasingly operate as strategic business leaders rather than purely technical executives.
Listen now.
PODCAST | What Enterprises Get Wrong About Trusted AI: Insights From Qlik and Deloitte
How do enterprises build AI systems that employees actually trust?
In Part 2 of this three-part conversation, former Qlik CEO Mike Capone joins Deloitte’s Dr. Adita Karkera to explore responsible AI deployment, AI literacy, transparency, and the cultural changes required to scale AI successfully.
The discussion covers:
Why trust determines AI adoptionThe evolution from data literacy to AI literacyGovernance beyond policies and councilsTransparency during workforce transformationWhy critical thinking still matters in the AI eraListen now on the CDO Magazine Podcast.
PODCAST | How Enterprises Can Prepare Data for AI Agents: Monte Carlo CEO Barr Moses Explains
What changes when AI agents, not just humans, become consumers of enterprise data?
In this conversation, Monte Carlo CEO Barr Moses joins CDO Magazine Editorial Board Member Justin Heller to break down:
• The shift to agent-first data trust
• Why AI governance is becoming more complex
• The risks of poorly governed AI agents
• Why enterprises cannot delay AI experimentation waiting for “perfect” data
Part 1 of a three-part series exploring the future of enterprise AI, governance, and trusted data.
PODCAST | USAWHC CDO Deepak Shah on Scaling AI Through Governance and Data Discipline
What separates isolated AI success from scalable enterprise capability?
In this episode, Deepak Shah, Chief Data Officer at the U.S. Army Western Hemisphere Command, discusses why operational discipline, governance, and trusted data foundations are becoming essential for enterprise AI scale.
The conversation examines:
• Why frameworks, playbooks, and runbooks matter
• How trust in AI depends on traceability and accountability
• The risks of relying on “heroics” instead of repeatable systems
• What real enterprise AI maturity looks like
An insightful discussion for data and AI leaders focused on long-term...
PODCAST | Insights from L.A. Care Health Plan on Building Trustworthy AI in Healthcare
What does responsible AI actually look like inside a healthcare payer organization?
In this podcast episode, former L.A. Care Health Plan CIO & CTO Tom MacDougall discusses how healthcare organizations are rethinking data strategy as rising costs, regulatory pressure, and real-time care demands reshape the industry.
Key discussion points include:
• Why healthcare payers are moving beyond claims-driven data models
• How interoperability is bringing data closer to the point of care
• Building continuously validated clinical data repositories
• Why human-in-the-loop AI remains essential in healthcare decision-making
• How L.A. Care...
PODCAST | AI Automation Depends on Trusted Data Ecosystems: Insights from Qlik and Deloitte
What actually determines whether enterprise AI succeeds?
According to former Qlik CEO Mike Capone, it’s no longer the models.
It’s the harder work underneath:
🔹Trusted data foundations
🔹Governance and lineage
🔹System alignment
🔹Operational trust
🔹Decision intelligence at scale
In conversation with Dr. Adita Karkera of Deloitte, Capone explains why organizations moving toward automation and agentic AI must rethink how they operationalize trust across enterprise systems.
The discussion also explores:
• Why many AI initiatives fail to produce measurable outcomes
• Why...
PODCAST | How Massachusetts Enables Secure Data Sharing Across Agencies to Deliver Resident Outcomes
In Part 2 of this series, Massachusetts CDO Karthik Yajurvedi breaks down what it actually takes to make data sharing work across government agencies.
From early childhood systems to workforce programs, the conversation explores how secure, trusted data sharing enables real outcomes for citizens.
Key themes include:
🔷 Why fragmented data limits policy decisions
🔷 The role of trust, privacy, and compliance
🔷 How modern platforms and agreements enable collaboration
🔷 What production use cases look like in practice
Listen now.
PODCAST | How Fugro Is Solving the Alignment Problem Holding Back AI
Most organizations are not short on data or technology. They are short on alignment.
In this episode, Vincent Brown, Regional Head of IT for the Americas at Fugro, joins Michael Sutter, CEO of Enlivened Tech, to unpack why transformation efforts fail when foundational steps are skipped.
Brown introduces the “Swiss cheese model” of misalignment and explains how gaps in awareness, ownership, and accountability derail outcomes.
You’ll learn:
🔹Why awareness must come before execution
🔹How to define and operationalize data ownership
🔹Why IT enables data, but doesn’t own it
🔹W...
PODCAST | USAWHC CDO: The Discipline Behind Data Initiatives That Scale
Most data initiatives don’t fail during execution. They fail at the start.
In this episode, Deepak Shah, Chief Data Officer at the U.S. Army Western Hemisphere Command, breaks down what it takes to build enterprise data initiatives that scale and endure.
🔹Why most data initiatives fail before execution and how to fix the starting point
🔹Using vision, mission, and goals as execution discipline
🔹What “solve and scale” actually requires: structured intake, prioritization, and governance
🔹Why trust, not the latest models or tools, determines whether data and AI initiatives scale<...
PODCAST | AI in Oncology Is Fragmenting: City of Hope CAIO on Fixing It with Orchestration
AI in healthcare is scaling fast. Coordination is not.
In this final part of a three-part series, Nasim Eftekhari, Chief AI and Analytics Officer at City of Hope, joins Erik Pupo of Guidehouse to examine what it takes to orchestrate AI at scale in oncology.
Key takeaways:
• Why agent orchestration is the next enterprise AI challenge
• What happens when AI agents don’t communicate
• How multimodal AI expands clinical intelligence
• The data foundation still missing in healthcare
• What defines scalable AI in oncology
In conversat...
PODCAST | Public vs Private Sector Data Leadership With the Massachusetts CDO
In Part 1 of this three-part series, the Chief Data Officer for the Commonwealth of Massachusetts discusses the foundations of public-sector data leadership. The interview explores how the role is structured, the similarities and differences between public and private sector data leadership, and the importance of storytelling in driving alignment and trust.
In conversation with Adita Karkera, Chief Data Officer for Deloitte’s Government and Public Services.
PODCAST | How Henkel Scales Data with Governance and Smarter Build vs Buy
Scaling data and AI is not just a technical challenge. It is a series of decisions that shape how fast you move, how much control you retain, and whether your strategy holds up over time.
In this episode, Katrin Botzen, Corporate Director, Global Data and Analytics at Henkel, breaks down what the company got wrong in its early data and AI journey, and how those lessons now guide its approach.
The conversation with Julian Schirmer of OAO, focuses on practical, enterprise realities, from embedding governance and security into systems from the start, to making smarter...
PODCAST | Why Most AI Efforts Stall at Scale and What Truist Is Doing Differently
Most organizations are still stuck in AI pilots. A few are scaling.
What’s the difference?
In this episode, Truist’s Sanjay Sankolli breaks down the operating model shifts required to move from isolated AI success to enterprise-wide impact.
You’ll hear:
🔷Why governance should act as a guardrail, not a gate
🔷How decision latency quietly slows innovation
🔷What it means to move from AI tools to AI as an operating capability
🔷Why data, trust, and alignment matter more than the number of AI models
This is the f...
PODCAST | How to Scale Oncology AI Safely: AI Governance Lessons from Hope LLM
How to Scale Oncology AI Safely: AI Governance Lessons from Hope LLM
As AI adoption accelerates in healthcare, the real challenge is no longer proving value. It’s scaling responsibly.
In this episode, Nasim Eftekhari, Chief AI and Analytics Officer at City of Hope, joins Erik Pupo of Guidehouse to unpack how Hope LLM is transforming oncology workflows across care, clinical trials, and research.
Key themes:
🔹Turning fragmented oncology data into real-time clinical insight
🔹Reducing clinician burden and reclaiming “pajama time”
🔹Embedding clinical trial matching into care delivery
...