It seems like only yesterday that I attended my first MIT Chief Data Officer and Information Quality (CDOIQ) Symposium back in 2008. The event had already been operating for a few years at that time. Participants gathered in a conference space and discussed why data would become a critical asset to organizations if only they paid attention to their information quality.  

How times have changed, and how in some respects, the challenges remain the same. Data is now uniformly recognized as the foundation for the most transformational technology in a generation — artificial intelligence (AI). At the same time, organizations continue to struggle with issues of data quality and acceptance of the role of the Chief Data Officer (CDO), which emerged as data gained organizational prominence.

These were among the topics discussed and debated at the 19th CDOIQ Symposiumin Boston July 15-17, a gathering of some of the best and brightest CDOs and data leaders from Fortune 1000 and global 2000 companies, and federal and state governments. This year’s event featured over 1,000 attendees from 47 countries, with over half holding the CDO title or reporting into the CDO.  

While the CDO role has become ubiquitous, with reportedly 84% of organizations having appointed a CDO (up from just 12% in 2012), the role has been plagued by short tenures (2-3 years on average), misunderstanding of the scope and mandate, and doubts as to whether the CDO is a permanent (or only a) transitional role. These issues have been magnified by the transformational emergence of AI.

The energy at this year’s Symposium was palpable throughout. Manav Misra, Chief Data & Analytics Officer at Regions Bank, notes, “As a first-time attendee, I was impressed by the quality of content and attendees at the conference. It was good to see several of my peers from across industries and discuss topical themes that we are all facing. The conversations in the corridors were as valuable in many ways as the sessions.”

Powerhouse panel challenges CDOs to adapt to stay relevant and have business impact

I was honored to host a panel of leading industry CDAOs for the 11th consecutive year. The focus of our discussion was how the Chief Data Officer role must evolve to stay relevant, drive business value, and harness the full potential of AI. The panel featured four powerhouse CDAIOs: 

• Teresa Heitsenrether – JPMorganChase Firmwide Chief Data & Analytics Officer
• Chandra Donelson – U.S. Space Force Chief Data & AI Officer
• Ryan Swann – Vanguard Chief Data Officer
• Don Vu – New York Life SVP, Chief Data & Analytics Officer

All agreed that the age of AI has elevated the role of the CDO. Heitsenrether comments that a key accelerant in her organization has been executive alignment. By making the CDAO role part of the firm’s operating committee, and having it report directly to the CEO, JPMorganChase has signaled that the CDAO isn’t just a technical function anymore — it’s a commercial, business-driven initiative.

Heitsenrether continues, “We’ve put the technology into people’s hands — 200,000 employees using AI tools daily. The challenge now is translating how data quality underpins all of that. I see my role as the ‘chief translator,’ helping the business understand why data matters in their own language.” She notes the need to balance top-down strategy with embedded business team alignment to ensure that data and AI leaders aren’t isolated in a center of excellence, but are fully connected to the line functions that generate impact.

Donelson offers a perspective on how the data leadership role has changed, commenting, “I used to walk into rooms as a data leader and get metaphorical tomatoes tossed at me. Now, I’m at the head of the table. We’re not blockers, we’re enablers of the mission.” She notes the cultural shift occurring even outside the walls of institutions, recalling that her eight-year-old son and his friends now come home talking about data, reminding us how AI has mainstreamed concepts like data ethics and decision-making across all walks of life.  

In discussing what lies ahead, Donelson challenges the audience to think bigger: “I don’t want to talk about generative AI anymore. That’s table stakes. Show me what’s coming next, that’s what I want to talk about.” S he concludes, “I always ask — what problem are you trying to solve? Don’t lead with the solution. Align your strategy to real pain points, not your vendor’s pitch deck.”

In discussing how “data headwinds” have moved to “innovation tailwinds,” Swann notes that AI has flipped the script, commenting, “Data quality used to feel like pushing a rock uphill. But suddenly, because the entire organization wants to use AI, there’s an intense interest in data hygiene, lineage, and business context.”  

Swann uses the term “AI-ready data” to reference the level of structured and increasingly unstructured, clean, contextualized data that serves as the foundation for scalable AI. He adds that this is what data professionals have always aimed for, but now the narrative has shifted to not just about convincing people, but about enabling the AI capabilities they demand to address their business challenges.  

Both Donelson and Swann call out technology hype cycles, noting that these can create unrealistic expectations and commenting that, whether it’s “shiny-object syndrome” or pressure from business leaders who’ve used ChatGPT at home, not every solution needs AI.

Vu leads both AI and data in an integrated function reporting to the CIO. He highlights how this structure supports career pathing for data scientists, avoids siloed capabilities, and keeps strategy business-focused. He notes, “We see AI and data as inextricably linked. Keeping it under one umbrella helps keep governance tight and talent engaged.”

In referencing the emergence of agentic AI, Vu emphasizes the transformational potential of Agentic AI, autonomous decision-making systems capable of understanding business objectives and taking action, especially in reengineering legacy processes. From procurement to operations, he sees massive potential, but warns about cost and infrastructure complexity.

Ramon Chen, Technology Advisor to the CDOIQ program since 2017, succinctly summarizes the CDO panel takeaways: “As these leaders demonstrated, the ones who will succeed aren’t just fluent in models, they’re fluent in outcomes. The CDO of the future will not only be a technologist and a translator but a catalyst for reinvention on every level. And if this panel is any indicator, that future is arriving faster than anyone expected.”

CDAIO daily round-up captures key event takeaways 

Data industry veterans Carl Gerber and Mark Johnson summed up the major discussion points of the previous day for conference attendees each morning. They captured the key takeaways from the 73 symposium discussions led by distinguished industry CDOs, including Amy Lenander of Capital One, JoAnn Stonier of Mastercard, Manav Misra of Regions Bank, Andrew Foster of M&T Bank, Ursula Cottone of Huntington Bank, Elena Alikhachkina of TE Connectivity, and JD Williams of Zoetis, among many others:

• Data is the foundation for great AI — There’s no AI without data
• Successful leaders have champions cheering for them and make other executives successful
• Become your stakeholders’ advocate
• Data quality = Business quality
• Success is providing measurable business value from Data, Analytics, and AI
• Solve problems that people care about
• Credibility is earned — you have to fight for it
• Large Language Models (LLMs) were last year’s buzzword; Agentic AI is this year’s.

Reflecting on the 2025 CDOIQ Symposium, TE Connectivity CDO Alikhachkina says, “The most effective CDOs are no longer just stewards of infrastructure — they’re enablers of confidence, alignment, and decision velocity. I’m energized by new ways we can surface how teams work with data in real-world contexts — not just what they know, but how they move. That’s where our future leadership mandate is headed.”

M&T Bank CDO Foster sums up this year’s event: “The CDOIQ conference remains at the top of its game. I reconnect with my CDO peers, share concepts and ideas, then deep dive with industry thought leaders and investors to explore what the next few years hold for our industry.”

We are already looking forward to celebrating the 20th CDOIQ, scheduled for July 2026.

About the Author

Randy Bean is the author of “Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI,” and a contributor to Forbes, Harvard Business Review, and MIT Sloan Management Review.  He has been an advisor to Fortune 1000 organizations on data & AI leadership for more than 4 decades.