The Future of Data Leadership: Why CDOs Must Evolve

For over a decade, data leaders have promised transformation: better decisions, stronger performance, and competitive advantage through data. But in today’s climate of tighter budgets and AI-driven urgency, data leaders are confronting a new reality: the need to deliver business outcomes – and fast.

In a recent episode of Data Radicals, host Satyen Sangani sat down with two experienced voices in the data world today—Ryan den Rooijen and Wade Munsie—to unpack what’s changed, why data leaders are struggling, and how they can chart a new path forward. Their message is clear: chasing data perfection is a losing battle. Pragmatism, value creation, and adaptability are the future.

Ryan den Rooijen is a seasoned commercial and technology leader who’s held executive roles, including Chief Strategy Officer at Appsbroker CTS, Chief Ecommerce Officer, and Chief Data Officer at the Middle East’s largest luxury retailer. He’s also led data initiatives at Dyson and Google. Wade Munsie is the only person to have twice won DataIQ’s Data & Analytics Leader of the Year award, with prior CDO and CTO roles at Royal Mail, GSK, and Controlant. Together, they bring decades of cross-industry experience and hard-won perspective to the challenges facing today’s data leaders.

Data leaders are in trouble

Den Rooijen and Munsie began their conversation by reflecting on a troubling pattern: many Chief Data Officers (CDOs) don’t last long in their roles. At a major data and AI event late last year, they noticed that many of the data leaders in the executive lounge had left their jobs rather recently.

“There was a theme that very few people were in the same job they were in the year before,” Munsie explained. “And a lot of them, even though their badges had the company on it, they said, ‘Oh, I’m moving on from there, or I’m no longer there anymore, or something’s happened.’”

The data reflects this anecdote. According to the 2025 Data & AI Leadership Executive Benchmark Survey, more than half of CDOs (53.7%) serve less than three years, and nearly a quarter (24.1%) exit in less than two years

This realization sparked deeper reflection. “We were both quite shocked about it at the time,” Munsie continued. “And we were looking down over the balcony at all of the stands down there and all of these people walking around in this AI and data bliss thinking this is a wonderful environment, but actually the leaders who are behind it are going, this is not so great, there's something wrong.” This aha moment led the two friends and data executives to co-author a series entitled, “Chief Data Officers Are in Trouble”, which explores the shifting landscape of data leadership. 

Chasing perfection at the expense of progress

Investment in technology alone is not enough. Munsie highlighted this as a recurring issue: organizations expect instant value from data investments without appreciating the time and complexity required to see a return. 

When asked why people are let go so quickly after being hired, he replied, “The biggest thing is the reality didn’t meet the expectations. So people think data is so easy to manipulate and turn around and the value is just going to appear and that just doesn’t happen.”

He also reflected on a long-held belief in perfect data. “Traditionally CDOs were in place to wrangle and collate the data and curate the data to a point that it was perfect and that was the ideal for a long time,” he noted. “I think that’s probably an impossible task these days… But also, is it needed?” With the rise of AI initiatives, and the corpus of analytics-ready data expanding to include unstructured data (like text documents), the dream of perfecting this vast data estate seems far-fetched.

What’s more, many organizations boast tech stacks that are far more complex than the use cases they support – like a household with ten cars but only one driver. Den Rooijen summoned a metaphor to illustrate this shift: “Five years ago you talked to some organizations and they say, ‘Oh, we’ve got a massive Hadoop platform,’ right? Or we’re going really big on BigQuery or Snowflake or whatever the flavor of the month is. And nobody even asked, well, what are you doing with it?... Now seriously though, what are we doing with all these investments? Why do we have 10 cars? 

“And it turns out that for most households, it turns out you don’t need 10 cars. But what you definitely need is somebody who knows how to drive.”

The three types of data leaders

Den Rooijen introduced a helpful framework for understanding the most common types of data leaders and why their impact often falls short. First, he described “the kind of command and control kind of folks… who want to catalog everything. They want to have MDM for everything, they want to govern everything.”

Then there are the technologists—“these technology CTOs who kind of came in very much with engineering hat to say, hey, data is going to be an integral part of our capabilities as an organization in the future.”

And finally, commercially-minded data leaders, who have “a very kind of practical lens on, well, I just want to be able to do X with the data. I want to be able to segment this. I want to be able to create a journey a certain way.”

But across all three types, Den Rooijen observed, the focus often becomes the tooling itself—regardless of whether it delivers value.

Systems thinking as a superpower

Systems thinking is the ability to see the bigger picture — to understand how different parts of a business interact as a whole. It’s about looking beyond individual functions or silos to optimize the performance of the entire organization. For data leaders, this mindset is not just useful — it’s essential.

Sangani noted this, saying: “I think the data role has this one incredible advantage, which is that often data leaders are system thinkers… but they've been focused on the wrong system. What they're trying to optimize is the data stack within a company; what they should be optimizing is the system of the business.”

Den Rooijen agreed, highlighting that data leaders naturally work across functions. “As a data leader… you have to work transversely across the organization. You’re dealing with very kind of complex stakeholders usually. So in theory, the ingredients are there for you to have that much broader scope of impact.”

But as den Rooijen and Munsie both suggested throughout the episode, having systems-thinking capabilities isn’t enough. What matters most is how data leaders apply those capabilities — not just to data ecosystems, but to business ecosystems. By shifting their focus from optimizing data infrastructure to optimizing value across the enterprise, CDOs can position themselves as true business leaders.

Beyond the CDO role

For years, the CDO has been treated as a specialist role—valuable, yes, but rarely seen as a stepping stone to broader executive leadership. That, den Rooijen and Munsie argue, is a mistake.

“I think in so many roles that succession conversation is just part and parcel of your development,” Den Rooijen reflected. “If you are an incredibly strong finance business partner, there's probably going to be a discussion about the head of finance role… Do you want to be CFO track? Do you want to move into a GM role, maybe divisional management?”

But for data leaders, that conversation rarely happens.

“On the data side, it's kind of just been, yeah, you're data,” den Rooijen noted. “Whether your title is head of data, director of data, or CDO, it doesn't matter because they're all used interchangeably.”

He recalled a telling insight from an executive recruiter: organizations tend to evaluate CDOs solely based on their technical expertise—what tools they know, how deep their data chops run—not on their leadership potential. As a result, most CDOs never get a chance to grow into broader roles, like their peers in finance, marketing, or operations.

And yet, that path is not only possible—it may be essential for the evolution of the enterprise. As Munsie noted, the data team of the future may be smaller, more distributed, and embedded across business units. As that happens, the CDO title may become less relevant—but the leadership potential of the people in those roles should only grow.

“Do I feel that data leaders such as ourselves are in a place where we should be stepping into those kind of… true C-suite roles?” den Rooijen asked. “No, because I think most of us haven't had that type of investment.” But he’s hopeful that could change. “With just a little bit of love and watering and sunlight, I think we could have a fantastic crop of future executives.” Current company hierarchies may be to blame. Just 36.3% of CDOs currently report to a business leader like the CEO or COO, while 47.2% still report into technology leadership—a structure that may limit their upward mobility (source).

Today’s CDO could be tomorrow’s COO, CMO, CFO—or even CEO. The qualities that make a great data leader—systems thinking, cross-functional influence, fluency in AI and analytics—are increasingly central to the modern C-suite. But getting there requires a mindset shift—from seeing the CDO role as a destination to seeing it as a launchpad.

As organizations rethink data strategy in the age of AI, they also have an opportunity to rethink data leadership. The next wave of business leaders won’t just understand the numbers—they’ll have built the platforms, partnerships, and strategies that made those numbers possible.

AI, agents, and the next frontier

No 2025 data conversation would be complete without a discussion of AI. Ryan and Wade expressed both optimism and realism.

“There is a lot of good there,” Munsie said. “The copilots of the world are fantastic.” But he added, “There’s not a lot of AI running or especially GenAI running at scale in most organizations. In fact, very few from what I can tell.”

Den Rooijen pointed out that many companies are chasing hype before mastering the basics: “Organizations that don’t even have their customer data or product data or supply chain data or whatever, or even have, I don’t know, standardized date definitions… shouldn’t be thinking about hyper sophisticated microservices making decisions.”

Still, he acknowledged potential, especially in how AI might reshape software interaction. “I think there’s a lot of potential there,” he noted.

Conclusion: A new chapter for data leadership

The era of data for data’s sake is over—but that doesn’t mean the future is bleak. Quite the opposite. As Ryan, Wade, and Satyen all emphasized throughout the conversation, this moment of reckoning for data leadership is also a moment of reinvention.

The path forward isn’t about bigger teams or more dashboards. It’s about aligning with business outcomes, embracing systems thinking, and stepping into roles that shape the strategy—not just the stack. It’s about moving beyond the title of Chief Data Officer and into the mindset of a transformational leader—one who’s ready to grow into a COO, CMO, CFO, or even CEO.

At the same time, the tools we use are evolving to meet us where we are. AI, especially in its more intelligent and agentic forms, offers a new kind of partnership—one that can help unlock the full potential of data leaders and the organizations they serve.

As Sangani put it: “To do this data management stuff or to do anything, you have to know things like Alation, you have to know things like data governance best practices, you have to know the policy, you have to know the context in your organization. And if you can digest all of that knowledge and allow the agent to prompt you through the actions, then you can create something that allows you to be met where you happen to be.”

That’s the opportunity in front of today’s data leaders: not just to clean, govern, or catalog data—but to guide organizations through complexity, shape decisions in real-time, and lead the business into what’s next.

The role may be changing. The team might be smaller. The title might evolve. But the mission—delivering value, driving innovation, and connecting data to business outcomes—has never been more important.

And for those bold enough to embrace that challenge, the future is wide open.

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