In this episode, Nitin Kumar, Director of Data Science and GenAI at Marriott International, joins CDO Magazine to discuss how enterprise data leaders are rethinking data readiness as the foundation for AI at scale.

In conversation with Ben Blanquera, VP of AI and Sustainability at Rackspace Technology, Kumar explores:

💠Why AI success is constrained by data, not models

💠How responsible AI becomes an engineering reality

💠What democratizing AI with guardrails actually means

💠How Marriott approaches Customer 360 using structured and unstructured data

💠Why agentic AI and multimodal systems will define the next phase of enterprise AI

This episode is part of CDO Magazine’s executive interview series focused on real-world AI leadership, governance, and value creation.

🎧 Listen now.

As enterprises move from generative AI (GenAI) experimentation toward scalable, production-ready capabilities, leaders are being forced to rethink how AI fits into operating models, how it is adopted by employees, and how trust is established across the organization. The shift is no longer about proving technical feasibility. It is about aligning data quality, governance, and everyday usage to support sustainable enterprise-wide impact.

Johnson & Johnson’s (J&J) Global Services organization plays a central role in operational transformation by delivering scalable capabilities across data, digital solutions, and business services to various stakeholders.

In Part 1 of this three-part series, Ajay Anand, SVP of Strategic Solutions and Commercial Services, Global Services at J&J, frames GenAI as a stakeholder-first transformation discipline that only scales when it is grounded in high-quality data, governed content, deep domain understanding, and consistent adoption across the enterprise.

In this second installment, Anand continues the conversation with EY’s Kevin Barboza on how Global Services balances near-term GenAI delivery with longer-term agentic AI strategy, how enterprise adoption is driven through structured change management, and why AI governance, accessibility, and disciplined data management form the foundation of trust as organizations prepare to scale AI responsibly into 2026.

What does success look like in data and AI governance when KPIs alone are not enough?

In Part 2 of this three-part series, Jo O’Hazo, Chief Data Officer at Advantage Solutions, joins Nathan Turajski of Informatica to discuss how data leaders measure progress in ways that actually change behavior.

The conversation covers:

♦️Moving from siloed KPIs to integrated business metrics

♦️Why stakeholder trust is a leading indicator of data maturity

♦️How compliance and ethics support innovation instead of slowing it down

♦️The real risk of prioritizing speed over accuracy

O’Hazo explains why governance embedded into the core enables reusable trust, faster delivery, and scalable AI outcomes.

Listen to Part 1 here.

In this episode, Nitin Kumar, Director of Data Science and GenAI at Marriott International, joins Ben Blanquera, VP of AI and Sustainability at Rackspace Technology, to discuss how Marriott applies data science and generative AI to personalize guest experiences and drive measurable business outcomes.

This conversation explores:

🔶The shift from data stewardship to enterprise value creation

🔶How AI is changing loyalty strategies in hospitality

🔶Why modern data leaders must translate AI into business language

This episode is Part 1 of a four-part series on enterprise data leadership and GenAI.

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The federal government makes trillions of dollars in payments each year, making payment integrity one of its most complex and critical challenges.

In this first episode of a three-part series, Justin Marsico, Assistant Commissioner for Fraud Prevention and Financial Integrity at the U.S. Department of the Treasury’s Bureau of the Fiscal Service, joins Carly Mitchell, Partner at Guidehouse, to discuss how Treasury is strengthening the Do Not Pay Program.

They explore why fraud prevention has become a top administrative priority, how OMB memo M-25-32 is removing long-standing barriers to adoption, and what agencies must do now to move from limited usage to full participation — while remaining compliant with privacy and legal requirements.

This episode provides a clear view into how policy, data, and governance intersect to protect public funds at scale.

🎧 Listen to Part 1 of the series now

Ajay Anand, SVP of Strategic Solutions and Commercial Services, Global Services at Johnson & Johnson, shares how the Global Services uses data quality, content governance, and domain expertise to scale GenAI responsibly. He explains how the chatbot JAIDA, Johnson & Johnson Artificial Intelligence Digital Assistant, supports more than 138,000 employees.

Anand breaks down:

🔹Why AI must be treated as a stakeholder-first discipline

🔹Why JAIDA is the launchpad for GenAI at enterprise scale

🔹How Global Services operationalizes AI for employees

🔹Why data and content quality define whether GenAI delivers actual value

🔹How to integrate GenAI without adding friction or compromising experience

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Jo O’Hazo, Chief Data Officer at Advantage Solutions, joins Nathan Turajski of Informatica for a deep dive into the foundations of enterprise-scale data and AI.

O’Hazo explains why her work begins with people rather than platforms, how micro successes compound into large transformation milestones, and why trust must evolve through listening, alignment and repeatable outcomes.

She also discusses how AI is revealing the gaps many organizations have ignored, and why strong governance, accuracy and architectural consistency matter more than ever.

Listen Now.

In this concluding episode of a three-part series, Andrew Foster, Chief Data Officer at M&T Bank, joins Parker Thompson of Denodo to discuss what it really takes to lead data initiatives in a large, regulated enterprise.

Foster shares candid lessons from M&T’s data journey, including how to adapt when progress does not move as planned, why CDOs must rely on influence rather than authority, and how the bank’s Data Academy is helping employees build data skills while reframing governance as a value-add.

A practical conversation for data leaders navigating execution, talent development, and organizational change.

Most AI challenges are not technology problems. They are foundation problems.

In the final episode of a three-part conversation, Chris Goodale, VP of Enterprise Data and Analytics Enablement at Sun Life, sits down with Jason Sturgess of Denodo to unpack how semantics, governance, and value discipline shape successful AI at enterprise scale.

The discussion explores why semantics act as a “Rosetta Stone” across business, technology, and AI, how Sun Life evaluates and prioritizes AI investments, and what it takes to consistently move from pilot to production in a highly regulated environment.

This episode is a practical guide for leaders focused on scaling AI responsibly while delivering real business impact.

Listen now and read the full conversation.

Andrew Foster, Chief Data Officer at M&T Bank, continues his conversation with Parker Thompson, Regional VP and General Manager, East at Denodo.

Moving beyond strategy, this discussion dives into execution. Foster shares how M&T Bank operationalizes data and AI across a 23,000-employee organization through federated stewardship, disciplined governance, and realistic planning horizons.

Hear insights on:

💠Building credibility through delivery, not promises

💠Why well-governed data is foundational to AI readiness

💠How to pace organizational change without disruption

💠Measuring value and sustaining momentum beyond initial wins

A must-listen for CDOs and senior leaders focused on turning data and AI ambition into measurable results.

Listen to part 1 here: [Link to first article]