The Chief Data Officer Role: What’s Next

The Chief Data Officer Role: What’s Next

Given the importance of AI strategy and data strategy, deciding who can best lead data efforts is an important C-suite issue. At the moment, chief data officers face some headwinds.?

Consider this: Some 84.3% of organizations have appointed a chief data officer (CDO) or chief data and analytics officer (CDAO), up from just 12% in 2012, according to recent research.?

But only 47.6% of organizations characterized their CDO role as “very successful and well established.” And more than half of CDOs have a tenure of less than three years. What do companies need to do to improve the data leadership situation? Read the full article below, by Ryan den Rooijen , Wade Munsie , and Randy Bean .

Laurianne McLaughlin, senior editor, digital, MIT Sloan Management Review


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The Chief Data Officer Role: What’s Next

by Ryan den Rooijen , Wade Munsie , and Randy Bean

The rise of generative AI has inspired a wave of transformation ambitions as organizations seek to reimagine everything from customer engagement to operational efficiency.

The evidence is compelling: According to the Data & AI Leadership Exchange’s 2025 AI & Data Leadership Executive Benchmark Survey, 98.4% of organizations are increasing their investment in data and AI, up dramatically from 82.2% just a year ago. At the core of those AI capabilities lies a fundamental resource: data. Some 20 years after people started saying “data is the new oil,” the refrain rings true, with 93.7% of survey respondents indicating that interest in AI is leading to a greater focus on data initiatives.

Yet the path forward for data leadership is more nuanced than those trends might suggest. Some 84.3% of organizations have appointed a chief data officer (CDO) or chief data and analytics officer (CDAO), up from just 12% in 2012, according to the survey. But while the CDO numbers continue to grow, these leaders face significant headwinds.

Only 47.6% of organizations characterized their CDO role as “very successful and well established”; the majority viewed the role as nascent, evolving, or even failing.

The tenure statistics are particularly telling: More than half of CDOs (53.7%) serve less than three years, and 24.1% last for less than two years, according to the Data & AI Leadership Exchange’s 2025 survey respondents. Whether these CDOs are being pushed out for ideological reasons, made redundant due to cost pressures, or seeing their mandates and budgets evaporate, the pattern is clear — on a global scale, data leaders are losing their jobs at an alarming rate.

“I have spoken with more data leaders looking for work in the past year than in all my previous years working in this space,” one executive recruiter told us.

This is happening against a background where hiring for AI skills is rising and the unemployment rate for tech roles overall in the U.S. is hovering at just 2.5%, according to December 2024 Bureau of Labor Statistics data. This phenomenon raises a pressing question: Why are data leaders being displaced at a time when the role of data is more critical than ever to commercial and operational performance?

Here’s how the CDO of a global enterprise organization described their experience: “Working in the energy industry, I found the role of the CDO was often misunderstood. Data investments were expected to be a quick fix, and we faced significant challenges due to lack of direct profit-and-loss accountability. As data was not recognized as a balance sheet asset, the credibility and influence of CDOs was questioned — leading to the role being made redundant. In the end, there was simply no tangible measure of the value data brought to the organization.”

We have seen this scenario play out for CDOs across industries as diverse as retail, financial services, energy, transport, mining, and even technology. But why is this happening, and what comes next?

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Three Forces Affecting the Chief Data Officer Role Now

While there are many different drivers behind the shift in fortunes for CDOs, three forces often interact to seal the fate of data leaders. These forces are related to strategic value creation, operating model evolution, and generative AI disruption.

1. Strategic Value Creation

Like many investments, data initiatives are easier to justify when times are good and profits are growing. However, the past 12 to 18 months have brought financial pressures that have forced executive teams to reexamine organizational budgets. This heightened scrutiny has illuminated a frustrating gap between the promise of data investments and their tangible impacts on operating margins.

Despite organizations investing heavily to build their data capabilities, measurable returns remain elusive for many. Often, instead of delivering an organization driven by data, the CDO delivers a business drowning in data.

In fact, the greatest struggle that most CDOs/CDAOs face is demonstrating business value from data and AI investments. In large part, this occurs because of data and AI initiatives that were not tied to business initiatives and business outcomes.

For years, many CDOs have focused on data preparation — organizing data, cleaning data, making data accessible — and other architecture and engineering tasks. These CDOs have operated with an implicit level of exemption from revenue and margin targets. That leeway has stemmed partly from the novelty of the role and partly from the broad belief that data can be a silver bullet for achieving strategic goals. However, as economic conditions have deteriorated, that narrative has been challenged. CDOs report that they now face the same profitability demands as their peers in sales, operations, and product development. Data strategies are no longer protected by perceived potential; instead, they are judged by their contribution to the bottom line.

“All we have to show for [our data investments] are prettier dashboards,” reflected one retail group’s CFO.

2. Operating Model Evolution

In the past, building data capabilities often meant establishing a centralized data office with some combination of data analytics, engineering, science, architecture, governance, quality, and product management teams. As organizations have increased their data maturity, there has been a trend toward decentralization as business units seek to take ownership of their data assets, data talent, and, perhaps most critically, data budgets. Often, the importance of the CDO role decreases as that evolution happens.

One could argue that effective decentralization at scale requires strong central governance. But this holds true only if strong relationships exist between the CDO or data office and the other business functions. Regrettably, in many organizations, the rarified positioning of the data teams means that they lack critical relationships with the C-suite. For example, how many chief marketing officers would describe the CDO as an essential partner? We’re not attributing blame, but it’s disheartening to hear some data leaders complain about “the business” — as if they somehow stand apart from it.

Some organizations have celebrated progress in building a data culture, but when this culture becomes cultish, it can drive a wedge between data teams and their business stakeholders. In short, CDOs/CDAOs need to deliver practical and measurable business value, not just clean and well-organized data. Perhaps it’s no surprise that 91.2% of data leaders cite cultural challenges as the primary impediment to their organizations becoming data-driven.

“We’re seeing a shift in where ownership for strategy and impact around data really sits. CDOs are increasingly second in command,” one CEO of a data and AI consultancy said.

3. GenAI Disruption

In many organizations, the majority of data-driven value creation occurs when AI is deployed and scaled, whether it’s during projects involving forecasting models, recommendation engines, or process automation. However, we have found that many data leaders have failed to sufficiently engage with AI to understand and appreciate its business and productivity potential. Many CDOs overindex on data architecture, suffer from dashboard overload, or become stuck in AI pilot purgatory. Only a minority of CDOs have managed to deploy AI to the satisfaction of their organization’s board.

Worth noting: Board members themselves are struggling to understand AI’s transformational impact, as well as the safeguards and guardrails that must be established to ensure responsible AI use. In a 2024 survey, executives reported that just 51.4% of corporate boards were well versed in data and AI issues and responsibilities.

Given the perceived business stakes of generative AI, it is perhaps not surprising that organizations have recently found it easier to appoint a new AI leader — as 33.1% have done, per the Data & AI Leadership Exchange’s 2025 survey — or to assign responsibility for GenAI initiatives to other executives. Often, it’s the CTO or the CFO, given their well-recognized, enterprisewide mandates.

Another benefit is that these alternative sponsors of data efforts often have stronger relationships across the business and a deeper understanding of the relevant business processes. Finally, they are also seen as stronger governance leaders — critical for the organizational need to balance both GenAI risks and opportunities.

“While data leaders will talk about owning the GenAI strategy, in practice, we never work with the CDO; it tends to be the CFO or CTO,” a strategy consultant noted.

What’s Next: New Business Leadership Roles for CDOs

While ROI challenges, operating models, and generative AI pose formidable challenges for CDOs, these three factors do not change the importance of data capabilities to organizations. After all, particularly when an organization seeks to harness AI to improve its operating margins, the ability to manage and exploit data is critical. Logically, someone in the business will still need to own this responsibility.

Fundamentally, we have come to believe that reconsidering the need for dedicated data leaders is key to any solution. We propose that organizations aim to develop C-suite leaders who have both deep domain expertise — gained through roles with revenue or customer responsibilities, for example — and strong data and analytics skills. This goes beyond data literacy; these executives need to understand the constituent parts of a successful data strategy and have the ability to build and manage teams that can deliver on that strategy. Such an approach could resolve tensions around value creation, operating models, AI adoption, and related challenges.

This path is less radical than it might seem, given that 36.3% of data leaders already report into business leaders, per the Data & AI Leadership Exchange’s 2025 survey. While the CDO role has been hailed as a career destination over the past two decades, perhaps we would be better off viewing it as a waypoint en route to a broader executive role, including in business leadership.

For example, we can envision a CDO becoming CEO of an international business unit. This would be a natural next step for an experienced data leader. At the same time, developing these pi-shaped leaders (those with both broad and deep competencies — in this case, domain and data expertise) has been a priority in organizations with high digital maturity for several years now. The approach we propose also overlaps with McKinsey’s decade-old concept of a digital quotient.

While some CDOs might see this as an attack on their hard-fought ambitions, we consider this an exciting opportunity. After all, while finance, operations, and commercial executives are generally seen as the leadership profiles to invest in, arguably CDOs have been overlooked. This is part of the reason why so few data leaders sit on the executive committee or have managed to make the leap to a broader commercial or operational leadership role. Yet we know many data leaders who would make great C-suite executives — if given the chance.

As one executive recruiter put it, “We have been so focused on the word data in data leaders, in many cases we have failed to put sufficient emphasis on the word leaders.”

So how do we see data and AI leadership evolving, and where do we think current CDOs would be well placed to make their mark? Here are three options.

The Commercial and Operational Leader

In commercial and operational roles, data is key to unlocking both growth and margin expansion. Whereas the average CDO might struggle to articulate their P&L impact, no chief operating officer (COO) or chief commercial officer (CCO) faces the same obstacle. While historically, a background in merchandising or supply chain would have been expected for a CCO or COO leadership development trajectory, we believe that the CDO is well-placed to take on this role. This truth is underscored by the executives currently in these roles who are increasingly taking ownership of data and analytics capabilities.

“We have noticed that while organizations are still recruiting for data analysts and data engineers, it is often no longer the CDO driving this,” a recruitment agency CEO told us. “Instead, we see commercial or operational teams taking ownership of their data as a function of their maturity.”

The Technology and Product Leader

Chief technology officers need to have experience in enterprise architecture, vendor management, and data integration to empower the business. Similarly, successful chief product officers (CPOs) are able to close the loop between consumer-insights signals, feature development, and performance measurement using real-time data to optimize decision-making and product road maps. In both CTO and CPO roles, an executive with data capabilities can help organizations ensure that investments are closely aligned with customer needs — accelerating innovation, improving agility, and reducing cost.

“They are making my role redundant, as they want to drive efficiencies by bringing the data engineering team under the CTO and folding the analysts into the product function,” said the CDO of a company listed on the FTSE 100 Index.

The Governance Leader

Many CDOs are frustrated by their organization’s lack of engagement with the thorny topics of data quality and data governance. But instead of compelling their CDOs to fight for an exclusive — and often elusive — mandate, perhaps organizations would be better off calling on the executives who own this mandate by default, CFOs and chief legal officers (CLOs). After all, who owns audit and risk processes? Who owns information assets at the board level? Where does the buck stop when it comes to the ethics of data capture or AI? As data grows in importance, CDOs with the right background could make great governance leaders.

Data Leaders Should Sit at the Heart of the Business

Looking ahead, the continual evolution of data and AI leadership roles reflects a broader maturation of these capabilities — and the organizations that have invested in them. Just as “digital” roles have become embedded throughout successful businesses rather than siloed in dedicated teams, a similar trajectory for data leadership is emerging. Much like the prevalence of chief digital officer roles has decreased, we expect to see a similar trend for chief data officers — and for AI leaders, in due course.

One note: It is interesting that 70.8% of the Data & AI Leadership Exchange’s 2025 survey respondents said they believe that CDO will become a permanent C-suite role, given the volume of evidence to the contrary that CDOs report. While we agree that accountability for data should sit within the C-suite, we expect that this will not take the form of the CDO role over the long term and instead should be incorporated into existing C-suite roles. Through this lens, perhaps the high percentage above is mostly an indicator of how many people believe that accountability for data is a C-level matter.

We think that having a data leader who is a CDAO in responsibility set but also a CCO, COO, CTO, CPO, CFO, or CLO in practice makes sense. The CDO needs to be a well-rounded business leader with an end-to-end understanding of the organizational impact of their role.

One of us (Randy) holds the view that the data and AI leadership role, be it a CDO/CDAO, CAIO, or one of the titles above, should be a business role that sits within the business organization. This year, 36.3% of companies indicated that the CDO/CDAO reported to a business leader — CEO, president, or COO, according to the Data & AI Leadership Exchange’s 2025 survey. While the majority of CDOs/CDAOs (47.2%) still report into technology leadership, this is changing.

Other AI trend experts, including Thomas H. Davenport, argue that having a “super CIO,” a new kind of overarching tech leader that some companies are appointing, makes more sense than having a dedicated CDO/CDAO. This super CIO typically reports to the CEO.

At the end of the day, the challenge is not about proving the relevance of data and AI leadership. Rather, it is time to reimagine how this leader operates within the organizational fabric to drive meaningful change.

Evolving the role of data and AI leaders to sit at the heart of the business, and giving these executives expanded commercial and operational, technical, or governance mandates, will help businesses unlock success in the coming decade.


Ryan den Rooijen is a commercial and technology leader who has held roles including chief data officer, chief e-commerce officer, and chief strategy officer. Read his insights at Qstar.ai. Wade Munsie is a data and technology leader who has served as CDO or CTO in organizations ranging from Fortune 500 companies to startups. He also served as a senior adviser for McKinsey & Company. Randy Bean is the author of Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI (Wiley, 2021). He is an adviser to Fortune 1000 organizations on data and AI leadership and is the founder and former CEO of NewVantage Partners.


Vivek Amarnani

Digital & Technology Director | CIO | CTO | Management Team | Digital Transformation | Data Science & AI | Process Automation | Digital Innovation | C-suite | Harnessing technology to transform businesses

12 小时前

As AI evolves toward more autonomous, agentic systems, the need for a deep architectural understanding of data and AI infrastructure has never been greater. Many organizations struggle not because they lack AI ambition, but because they lack the data engineering foundations to make it work. Immaterial of whether it is a CDO or a ‘Super CIO’— one needs to understand business processes, data engineering and AI architecture—to bridge this gap and unlocking real value from AI.

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Vanel Beuns

A visionary and results-driven leader in sustainable development and public service, specializing in Bold Strategic AI (SAI) Leadership to drive innovation, efficiency, solutions, and positive global impact.

20 小时前

As a stellar Servant, Authentic, Visionary and Transformational leader with purpose and hands-on expertise, I play my part successfully. As a UN Global Climate Champion, I take pride in making a positive difference. As an outstanding steward of public service and as a career civil servant, I helped safeguard the financial system and promote operational efficiency by educating customers and enforcing compliance with applicable laws and regulations. Does SAI have the potential to help countries, organizations, institutions and businesses SAVE billions of dollars from Fraud, Waste, Abuse, and Mismanagement? The Economics of Strategic AI (SAI) and Global STEM Talent: - From Digital Transformation to BOLD Solutions: We improve organizational efficiency, enhance effectiveness, streamline inefficient processes, strengthen controls, re-engineer antiquated systems, and mitigate risks for success.? Better Policies for Sustainable Results and Solutions: What is the list of the world's TOP 100 High Risks and Global Challenges in 2025? As a results-driven servant leader, my expertise lies in leveraging AI to close digital divides, bridge skills gaps, unlock human potential and unleash productivity, resulting in significant cost savings.?

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Jasper Hegarty-Ditton

People-focused Digital & Data Transformation

20 小时前

Reading, I was reminded of the ‘Cliff of Reality’ (Carruthers & Jackson Summer School) Rather than the CDOs & orgs referenced who seem to throw their hands up, we’ve: ? Accepting where efforts aren’t working - pivoting to outsourcing + in-house ? Stopped waiting for full integrated data stacks, getting value by commissioning dashboards closer to the data ? Repeating data presentations in our staff conferences, again and again, so the data culture builds ? Delivering value across the whole organisation - yes, dashboards for teams with large P&Ls, but smaller data/insight issues from fixing sales attribution issues in ticketing platforms to creating better customer feedback loops Our latest initiative sees a reinvigorated process around our strategic impact data - improved data visualisations & storytelling, with ‘actions to work on’ distributed to managers throughout the organisation. This creates accountability for future action & current reporting (many actions were already in focus). Looping into our Compliance & Risk Working Group brings data + insight to the heart of the organisation!

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Dr. Heera Lal Patel IAS

Climate Action Leader Saving Mother Earth | Author | Changemaker | Social Media Influencer For Public Welfare | Social Entrepreneur | Inspirational Speaker

21 小时前

Join Dr. Shishir Srivastava in a powerful conversation with Dr. Heera Lal Patel, IAS, a visionary leader driving climate action and rural transformation in India. Discover his pioneering initiatives, including Model Gaon, and how governance can create a greener, self-reliant future. https://youtu.be/zI3aOuFvsxs

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