Chief AI officer may be one of the most important executive hires companies make in this decade. It may also be one of the shortest-lived.
Just a few years ago, most boards probably would’ve questioned whether they needed a dedicated leader for artificial intelligence. But when ChatGPT started to dominate public consciousness in late 2022 and early 2023, the conversation changed. The rush began to launch AI practices, assemble AI task forces and committees, and of course, appoint chief AI officers.
The rationale for hiring a chief AI officer was and remains sound. Without a dedicated person owning AI strategy, initiatives can fragment across teams or lack clear connection to talent, risk, and business opportunity. And given how quickly I’ve seen the role gain traction in my work advising companies on technology leadership, I’m not surprised that a recent IBM study found more than three-quarters of organizations have a chief AI officer.
But as AI becomes an enterprise-wide capability, the logic of a single owner is harder to sustain. If AI is part of every role, workflow, and major decision, why is only one executive in charge?
That’s where the paradox lies: The better a chief AI officer does their job today, the less their organization may need the role in the future.
There’s precedent for this kind of executive lifecycle. Think about the trajectory of the chief digital officer (CDO), which grew from a niche position at just 6% of companies in 2014 to 21% of companies in 2018; the pace of hiring appeared to peak in 2016.
In that era, companies needed a point person to design and implement digital strategy. But as CDOs helped transform their organization, “digital” transitioned from a specialized capability to something integrated across every domain. And in some cases, CDOs who weren’t integrated with the core business or overlapped with other C-suite roles struggled to maintain relevance.
AI adoption will likely mirror that trajectory because it is another operating model change. In theory, AI should fundamentally reshape how work happens, from how finance operates to how HR recruits talent to how CEOs make decisions. The desired endpoint is AI as an underlying infrastructure.
This means that if a chief AI officer does their job correctly, they’ll eventually make their standalone role unnecessary. They’ll act not only as a technologist but a transformation expert who helps manage change, establish governance, and drive business value. Critically, they’ll also build AI fluency across the C-suite until AI becomes everyone’s responsibility.
However, obsolescence doesn’t need to be the endpoint for the chief AI officer. Instead, I see potential for these leaders to work themselves out of their role and into a different one through a three-stage evolution.
In the first phase, the chief AI officer is an evangelist. Their primary goal is to convince the organization that AI matters, building awareness of the technology and encouraging experimentation to support adoption. In 2026, most organizations have already moved past this phase.
The second phase is where most organizations are now: the shift from experimentation to accountability. The chief AI officer evolves into an operator, with the mission of driving value and demonstrating ROI for boards and investors.
The third phase is where the chief AI officer lays the groundwork for their next act. Over the next few years, they will become architects, building systems that enable other executives to take ownership of AI within their functions. They help distribute AI accountability, so the CFO owns AI-enabled finance, the CHRO owns AI-enabled talent, the COO owns AI-enabled operations, and so on.
In my work, I’m already seeing signs of this shift. AI competency is increasingly appearing in job descriptions across all C-suite roles. Executives are expected to be AI enabled themselves, and also enable their teams to use the technology effectively. At the same time, companies are embedding AI champions within each business unit to identify potential uses and govern adoption, rather than relying on a centralized AI “command center.”
A chief AI officer who successfully orchestrates this transition will reduce the need for a separate AI department and, in turn, their role. But they’ll also gain a unique understanding of the enterprise, spanning across technology, operations, talent, governance, strategy, and organizational change. That experience positions them to become a broader transformation leader, or even a strategic advisor to the CEO and board.
Right now, the vast majority of organizations still need a designated leader to prove where AI creates value and help embed AI as a capability within every executive role. But over the next five years, companies are more likely to eliminate standalone AI teams than create them.
Long term, chief AI officers will help their organizations win by embedding AI so thoroughly that it becomes nearly invisible. In doing so, they can prove their readiness for broader enterprise leadership. My bet is that some of the most successful chief AI officers will eventually move into COO, transformation, or even CEO succession pipelines.
While the specific role of chief AI officer may eventually disappear, the presence of these leaders doesn’t have to. Organizations that are intentional about recognizing and developing their potential can turn a transitional role into a training ground for future enterprise leadership.