Data Leadership Claims Its Permanent Seat At The Board Table To Answer For AI

The executive org chart is getting crowded, and AI is why. Rather than sorting out who owns the data and who owns the systems, some organizations are simply inventing new acronyms. As the CIO role expands to absorb data strategy, AI governance, and workforce orchestration, the boundaries between technology leadership and data leadership are harder to draw than anyone anticipated. These new titles are a way to pass the buck on AI rather than changing how work actually gets done.

Caroline Carruthers is the Co-founder and Chief Executive of Carruthers and Jackson, a specialist data consultancy. One of the UK's first Chief Data Officers, she held the role at Network Rail before co-founding the firm, and is the co-author of several books on data leadership, including The Chief Data Officer's Playbook and Data Driven Business Transformation. She has spent a decade demonstrating that data leadership endures not because it is fashionable, but because data is a core organizational asset, and that clarity of ownership is what separates enterprises that scale AI from those that stall.

"The most durable C-suite roles are the ones that sit around an asset: finance, people, and data. Those are the roles that survive every trend cycle," said Carruthers. It is an argument she grounded in history. Before the 1970s, the CFO had no guaranteed seat at the board table, a fact that now seems almost inconceivable. She has watched the same cycle play out with data leadership, and expects it to repeat as AI forces organizations to decide which new roles are genuinely asset-driven and which are trend-driven.

Asset ownership on paper and authority in practice are not the same thing. As AI expands the scope of both the CIO and CDO, the question of who holds genuine decision-making power over data and systems is becoming harder to answer, and more consequential when left unresolved.

• Architecting the gap: "Chaos loves a gap. That's the part in an organization where you don't know who to ask the ultimate questions," said Carruthers. "That's where complete and utter total nightmares happen." The instinct in many organizations has been to fill that gap with a new title rather than resolve the underlying question of who is actually responsible.

The C-suite roles that endure are the ones built around core assets, not trends. Finance, people, and data have held their place at the board table because they are foundational to how organizations function, not because they were fashionable. Experimenting with new acronyms for AI might feel like progress, but it often distracts from whether those underlying assets are being led coherently. Her skepticism about new titles comes down to resource efficiency. Companies do not necessarily need to hire a new executive; they just need to foster a symbiotic relationship between the CIO and the CDO.

• Assets over acronyms: "Roles that basically center around an asset are the ones that achieve longevity. Before the 1970s, the CFO wasn't a regular part of a board, and the thought now of having a board that didn't have a Chief Financial Officer is ridiculous," she said. Data, in her view, belongs in the same category, not because it is fashionable, but because it is foundational.

• Old MacDonald’s C-suite: "What I find interesting is where we're getting people being Chief AI Officers or Chief Data and AI Officers, which is starting to make me sound like I'm singing 'Old MacDonald Had A Farm'. If you have that true symbiotic relationship between your CIO and the CDO, you have the two components you need to make AI work in your organization," she added. The debate over dedicated AI officers does not resolve the underlying question of who owns what.

When CIOs and CDOs overlap, it is rarely a power struggle. The CIO's job has grown from infrastructure to security, applications, integration, and now AI. The ecosystem has simply outgrown any one role. Carving out data leadership does not mean the CIO lost a turf war. Carruthers noted that the relationship works best when both sides treat their responsibilities as complementary rather than competitive. That reframing is happening, and not only because it is the right thing to do, she observed. CIOs who have made peace with AI scaling across the enterprise have found it to be very much in their own interest.

• Buckets and water: "The CIO is responsible for the bucket, to make sure there are no holes in it, that it's the right size and in the right place. The CDO is responsible for the water: where it comes from, where it goes, making sure it gets to the right people in the right way," said Carruthers. "The CIO cannot suddenly move the bucket without telling the CDO, because then the water's going to the wrong place." The same logic applies to AI accountability. When data quality and system design are jointly responsible for an outcome, isolating a single point of failure is rarely possible, and what matters is shared accountability for outcomes, the way every member of an F1 team owns the result regardless of whether it was the car or the fuel that failed.

• Dodging the drop: Today, as pressure to show AI returns intensifies, many CIOs actively cooperate with their data counterparts out of strategic self-preservation. "More often than not now, when I'm speaking to CIOs, they're what I would call the new version of the CIOs, the ones that want to work with the CDOs, that understand it and actually recognize that if we work nicely with the CDOs, we don't have a CAIO being dropped on top of us," she explained. It is a shift she described as both cultural and pragmatic: CIOs who once felt threatened by data leadership roles now see the CIO/CDO partnership as the most effective argument against adding yet another executive to the org chart.

When AI outcomes go wrong, who owns the failure? The struggle for good AI governance has moved well beyond compliance checkboxes. Carruthers distinguished between data governance, which ensures the right systems and controls are in place, and AI governance, which is accountable for what those systems actually produce. As AI governance regulations tighten, she saw the need for both broad participation and a clear owner. Accountability holds when oversight is collaborative but not diffuse. Her model: a board drawing on the CIO, CDO, security, and operations, with a single chair who keeps decisions moving rather than letting them stall. Data leaders are increasingly stepping into that chair, but only where governance has a named owner. Without one the conversation drifts. Governance boards without a named owner tend to cycle through hypotheticals rather than reach decisions.

• The Incredibles effect: "You need to have one person who needs to bring the systems together. You will need a process to look at AI ethics, for instance, and AI governance. You will need somebody who will sit on a board to make those decisions," said Carruthers. "But you need a chair. It's a little bit like The Incredibles where somebody goes, 'Oh, everybody's special.' If everybody's special, nobody is. You can't have that lack of accountability." The Incredibles analogy cut to the core of her argument: distributed ownership without a single point of accountability is not governance, it is the illusion of it.

• Flying hippos and hypotheticals: "If you constantly talk about the if-then-else scenarios, you could talk about, I don't know, hippopotamuses descending from the sky if you get ridiculous about it. We get stuck with ethics like that because we just talk in circles," she noted. "But if you focus on the practical, tomorrow we're going to solve this problem. How do we solve that problem together and come at it from that angle? It makes things so much more simple." For Carruthers, the test of any governance framework is whether it can answer a concrete question by the end of the meeting.

For Carruthers, the same outcomes-first logic applies to data itself. "I don't think data has an intrinsic value," she said. "To me, what has the real value is the purpose of what you're using the data for. Once you understand what problem you're trying to solve, it's the outcomes that we should be valuing, not just an inert asset sitting over here." It is a liberating insight for teams drowning in data but starving for ROI.

Questions about who owns the data and systems get much easier to answer when everyone works backward from the same practical goal. Carruthers brought that thinking to developing future leaders through her free, annual CDO Summer School, now in its eighth year. The program brings together hundreds of aspiring and current data leaders to build practical data strategies, work effectively with CIO counterparts, and navigate the realities of modern executive leadership.

Carruthers also pushed back on fears that AI will simply replace senior roles wholesale. She preferred the term "augmented intelligence," emphasizing that the technology is best used to remove drudgery rather than decision-making. "If you are not using AI in some way, shape, or form, it is what you are using it for that I would like people to think carefully about. I have got a little Roomba that goes around and hoovers my floor. If you want to get technical about it, that has stolen my job and it can have it," she added. "How do we think about using AI? I much prefer the term augmented intelligence."