A successful AI initiative needs more than a working model. It needs a business outcome that matters and access to data that may sit outside the control of the team responsible for delivering it.

Those two challenges brought data, AI and technology executives together for the CDO Magazine Dallas Executive Boardroom Dinner on October 13 at Del Frisco’s Double Eagle Steakhouse in Plano, Texas.

With Moving from AI Experimentation to Production as the evening’s theme, the discussion centered on a practical tension: organizations are under pressure to demonstrate AI’s business value, even as the data needed to deliver that value remains distributed across different owners, systems and business functions.

Measuring What AI Actually Delivers

The Dallas discussion put business outcomes at the center of AI success. Rather than measuring progress by the number of pilots or models developed, the focus was on whether AI initiatives were creating meaningful value within enterprise operations.

Atul Jain, Verizon Global Head, Cloud, AI and Data, offered this perspective:

“Move from experimentation to business outcomes. The true measure of data and AI maturity is not the number of pilots or models, but the measurable business value created by embedding AI into real enterprise workflows.

Connect data across silos without necessarily centralizing it. When data is distributed across multiple owners and systems, the key is to make it discoverable, trusted, governed, and accessible to the right people and AI systems.

Ultimately, success comes from turning data into trusted, actionable intelligence that drives business value.”

Jain’s perspective connects the measure of AI success to the conditions needed to achieve it. Delivering business value depends not only on what AI can do, but also on whether organizations can make distributed information usable without necessarily bringing it all into one place.

Accountable for Data You Don’t Control

That challenge becomes more complicated when responsibility for AI outcomes rests with teams that do not own the underlying data.

For organizations working across different business units and systems, data ownership raises questions about access, consistency and accountability. The relationship between ⁠AI governance and data governance becomes particularly relevant when organizations need to make distributed information usable for AI.

Chris Tambos, Everpure Strategic Advisor, shared an observation from the evening:

“What stood out to me was that organizations are finding real, measurable value from AI, but achieving that often depends on data they don’t fully own or control. The challenges aren’t just technical. They’re about understanding what data means, how it can be used, and who is accountable for making it usable.”

Tambos’s observation adds another dimension to Jain’s point about connecting data across silos. Access alone does not resolve the challenge. Organizations also need clarity about the meaning of their data, the conditions under which it can be used and who is responsible for making it reliable.

When Governance Becomes an Enabler

The questions around data ownership led naturally to another issue addressed during the Dallas dinner: whether governance can help organizations move faster rather than simply adding controls.

⁠AI governance is often associated with managing risk and establishing oversight. In the context of production AI, it also raises practical questions about how organizations make information discoverable, understandable and available to the right people and systems.

Jain’s emphasis on trusted, governed data and Tambos’s focus on accountability reflect two sides of that challenge. Both perspectives point to the importance of establishing clear responsibilities when AI initiatives depend on information spread across an enterprise.

The Value of Different Perspectives

The Dallas gathering brought together executives from organizations across financial services, telecommunications, retail, healthcare and other industries. While their operating environments differ, the evening’s central questions about AI value, data ownership and accountability have implications across sectors.

Jenna George, CDO Magazine Community Director, offered this reflection on the importance of those exchanges:

“What makes these dinners valuable is the opportunity for leaders to speak openly about what they’re actually experiencing. In Dallas, the focus was on making AI deliver real business value, including the challenges that come with data ownership and accountability. Bringing together executives from different industries gives everyone a chance to learn from perspectives they might not encounter in their day-to-day work.”

The Dallas gathering continued CDO Magazine’s focus on creating opportunities for data, AI and technology leaders to connect through candid, peer-level discussions.

CDO Magazine thanks Everpure for supporting the Dallas Executive Boardroom Dinner and contributing to the exchange of ideas.

Most importantly, thank you to the Dallas data, AI and technology leaders who shared their perspectives and experiences. The value of these gatherings comes from bringing peers together to examine the decisions behind enterprise AI, including the difficult questions about business outcomes, data ownership and accountability that cannot be resolved through technology alone.

Data, AI and Technology Leaders Who Joined the Dallas Conversation:

• Shuchi Agrawal, SMBC Group Head of AI Execution/ Commercialization
• Aamer Charania, Best Buy Head of Applied AI
• Mahdi Esfahanian, Digitas North America VP Data Science
• Ravi Gedela, Ericsson Executive Director – Technology, Engineering & Product Development
• Malcolm Hicks, Former Bank of OZK CDO
• Atul Jain, Verizon Global Head of Cloud, AI and Data
• Livia Kessler, Bon Secours Mercy Health Head of Analytics Delivery
• Vino Kingston, Lockheed Martin Knowledge-Driven Enterprise & Agentic Automation Leader
• Biswajit Mahapatra, Texas Capital Bank Director- Data Platform
• Rajat Mehrotra, Cisco Meraki Director – Networking Data Science and AI Platform
• Deepak Mutkule, Hertz Director Data Platform & Analytics
• Justin Nguyen, The Home Depot Technology Director, Enterprise Data & Analytics
• John Porter, Albertsons Companies Corporate Vice President – Finance, Supply Chain Transformation
• Arjun Puri, DTCC Director, Cloud Data Engineering & Analytics
• Bart Slowik, Dallas Regional Chamber Managing Director, Innovation
• Jagadeesh Tupakula, Former UNFI Enterprise Platform Engineering, AI, & Data Transformation Leader
• Cheryl Hayes, Everpure Vice President of Growth Marketing
• Seth Jamison, Everpure AVP, Americas Field Solutions Architecture & Technologists
• Chad Primakow, Everpure AI & Data Leader
• Doug Robertson, Everpure AVP Commercial Systems Engineering
• Patricia Scupeliti, Everpure Director, America’s Commercial Marketing
• Allegra Stratton, Everpure Enterprise Account Executive
• Chris Tambos, Everpure Executive Advisor Data & AI
• Jenna George, CDO Magazine Community Director
• Anthony Losanno, CDO Magazine Managing Director