Who should own AI? I started with an incomplete answer - cio.com

Several months ago, I was invited to an event for CTOs. Just looking around the room, I could see someone had made an assumption about my title. I am a chief transformation officer, not a chief technology officer.

I stayed anyway to see how the other type of CTO thinks about AI. When a CISO got onstage and said, “This is our time,” my immediate reaction was cringe.

I remember thinking, AI is going to change jobs, workflows, skills and how people experience work. Tools and controls alone will not produce transformation. The real challenge is redesigning how work gets done.

I knew from the beginning that AI would require partnership across technology, security, legal, finance and the business. But I saw people and operating-model change as the center of the work, with technical and governance teams enabling it. After working to operationalize AI across a company, I can see what I missed.

Why I started with people and operating models

My original assumption was based on my own experience managing through change. Technology creates possibility; operating models create value. Access is not adoption.

A team can run an impressive pilot that never becomes part of how the function operates. Experimentation means very little if leaders have not defined the business outcome, how the workflow will change or how the team will sustain it once the pilot ends.

People leaders understand job design, learning, manager behavior and the emotional reality of change. People resist initiatives that feel disconnected from the work they are accountable for every day.

Organizations also tend to budget for technology and not for transformation, treating licenses, APIs and model usage as the whole investment. The real cost includes the time people need to learn and build fluency, and the clarity managers need about what good use looks like.

A technically strong AI program can fail because the organization never changes around it. AI raises the floor, but transformation raises the ceiling. The larger value comes from what happens around the technology, including where human judgment is still required and what the company can now do differently.

Research supports the importance of that organizational layer. McKinsey’s 2025 State of AI report found that redesigning workflows was the factor most associated with reported bottom-line impact of generative AI.

Operationalizing AI shaped my answer

The more I moved into execution, the more obvious it became that any single function can’t own AI transformation. Technology, data and security could not sit alongside the people transformation as support functions. Leaders across the business have to help design it.

At Branch, I am the executive accountable for AI across the company, including our enterprise strategy and the work of connecting governance, technology, priority use cases and organizational change. Once I started leading that work, I kept running into decisions my team could not make. We needed technology and data leaders to determine whether the architecture was ready and how models would connect to our systems. Security and legal had to establish the boundaries. Finance needed visibility into consumption. The business still had to decide which workflows deserved investment and own the result.

Every practical decision exposed another dependency. We needed an operating model that made routine decisions clear and gave higher-risk work the right review. Good governance should work like a freeway, with lanes, offramps and rules everyone understands, not a roadblock that stops progress.

Operationalizing AI taught me that no one function can own execution because the work happens across workflows rather than within the boundaries of the org chart.

After eight months of doing this work, I believe someone has to own the transformational work within the organization, but technology, security, legal, finance and people leaders each carry critical parts of the execution. Then, individual functions own their use cases and results.

Every company needs to know which executive is accountable. Whether that person needs the title of chief AI officer depends on the company.

A dedicated role can be valuable when AI activity is fragmented and the company needs to move from pilots to an enterprise operating model, but it can’t substitute for shared ownership across the leadership team.

That distinction is showing up in the role itself. CIO’s examination of the chief AI officer’s evolution describes a shift away from a central leader owning every AI activity and toward a model where the AI executive establishes strategy, standards and common capabilities while enabling the business to execute. In my experience, that is much closer to what the work requires.

The accountable executive should decide where the company will focus and make sure governance produces decisions quickly enough for teams to act. They need alignment from the leadership team on which risks the company is prepared to accept and how it will know the work is paying off. They also own how the organization changes around the technology. That includes how people learn, what managers expect, how workflows get redesigned and where the company reinvests the time AI creates.

They should not become an AI island. They can’t be the technical concierge for every tool request or the gatekeeper every function waits on. That structure gives the rest of the executive team permission to outsource responsibility for a transformation that affects all of them.

Finding someone who fits that profile is its own challenge. I would look for a transformation leader with real technical fluency. They need to work credibly with architecture, data and security leaders. Their job is to connect those decisions to workflow redesign and bring the organization with them.

In some companies, that person will be the CIO. The 2026 State of the CIO research describes CIOs increasingly acting as AI orchestrators and change management champions. In other companies, the accountable executive may be a chief transformation officer, a chief operating officer or a dedicated CAIO. The title matters less than the mandate, authority and ability to lead across boundaries.

When I think back to that CTO event, I understand why the CISO said, “This is our time.” AI has expanded the mandate of security and made its partnership with the business more important. I also understand why I reacted so strongly. People are the transformation. Ultimate accountability still sits with the CEO. Functional leaders own outcomes in their areas. The board needs visibility into strategy, material risks and oversight. The AI leader keeps those layers connected.