The Rise of the Chief AI Officer: From Experiment to Imperative

NTT’s recent decision to appoint Abhijit Dubey as both CEO and Chief AI Officer marks a new phase in corporate leadership. It’s a public signal that AI is no longer a technical layer managed at the edges of an organisation—it has moved to the centre of business strategy.

For years, AI was treated like an optional tool: a promising pilot here, an experimental chatbot there. But those days are ending. As Dubey put it, AI is not an initiative. It’s the core of the company’s identity and the engine of its future. His dual role underlines a deeper truth: AI is now about strategy, governance, and culture as much as it is about algorithms and code.

From fringe to fixture
The Chief AI Officer (CAIO) role is spreading at remarkable speed:

• More than 1,800 people worldwide now hold the title, from NASA to L’Oréal to national oil companies.
• Gartner forecasts that 35% of large enterprises will appoint a CAIO by the end of 2025.
• Governments are moving too: in 2024, the U.S. required every federal agency to create a CAIO post.

This follows the path of earlier C-suite shifts—remember when few companies had a Chief Digital Officer? Within a decade it became common practice. The same pattern is now playing out for AI.

Why it matters
Without dedicated leadership, AI initiatives risk becoming scattered side projects—duplication in one department, experiments that never scale in another. The CAIO exists to prevent this fragmentation, bringing coherence and ensuring AI supports real business outcomes.

The responsibilities extend beyond strategy and projects:

• Governance & ethics: making sure AI systems are transparent, fair, and accountable.
• Talent & culture: attracting scarce AI talent while reskilling the wider workforce.
• Cross-functional alignment: ensuring AI impacts finance, operations, HR, and customer experience—not just IT.
• Sustained adoption: embedding AI into decision-making and day-to-day workflows, not just demos.

Challenges ahead
Of course, the role isn’t without tension. The boundaries between CIO, Chief Data Officer, and CAIO can blur. There’s also the risk of “title inflation”—LinkedIn is filling up with CAIOs whose real scope of authority is limited. Companies that treat the role as window dressing will quickly be exposed.

The difference will come down to credibility. Effective CAIOs bring a blend of deep technical knowledge, operational experience, and the ability to navigate ethics and regulation. They are as comfortable talking data architecture as they are addressing shareholder risk.

Impact beyond tech
What’s striking is that this shift isn’t confined to Silicon Valley or Tokyo. Consumer goods companies, energy firms, aerospace agencies, and public sector bodies are all embracing the CAIO model. Early research shows that companies with credible AI leadership are already outpacing their peers in growth and efficiency.

A strategic imperative
Abhijit Dubey’s move to combine the CEO and CAIO roles is more than a personal career statement. It reflects a new reality: AI has become a board-level responsibility. Companies that delay embedding AI leadership risk being left behind—not just in technology, but in talent, governance, and competitiveness.

The message is simple: whether you run a bank in Johannesburg, a retailer in Nairobi, or a global manufacturer in Frankfurt, the Chief AI Officer is no longer a nice-to-have. AI is shaping the future of work, and leadership has to rise to meet it.

References

• NTT DATA: Leading the Next Era (2025)
• NTT DATA: Agentic AI Report (2025)
• Technology Magazine: Abhijit Dubey: From Silicon Valley Consultant to NTT CEO
• Brunswick Review: The Rise of the Chief AI Officer
• MIT Sloan Management Review: Do You Really Need a Chief AI Officer?
• Dataiku: What is a Chief AI Officer?