Will AI Get Its Own Chief? Yes. But Probably Not the One You're Expecting.

Pick any large company and ask who owns AI. Odds are you will get three different answers from three different executives, each of them convinced the answer is obvious. The CTO sees it as the next chapter in digital infrastructure. The CHRO sees a workforce transformation challenge of historic proportions. And somewhere in a recently created office, a Chief AI Officer is busy writing a strategy document that will require sign-off from both of them.

That three-way confusion is not a temporary growing pain. It is the central fact about AI in the enterprise right now. And understanding why it exists is the key to figuring out where this actually settles.

Why a CxO in the first place?

C-suite roles do not appear by accident. Looking across how the CFO, CIO, CMO and CHRO all came into being, a pattern emerges. A function earns a permanent seat at the top table when three conditions are met: the work becomes too complex for a generalist to absorb, the cost of failure becomes high enough to demand a single accountable owner, and the activity develops a clean enough boundary to be managed as a distinct domain with its own metrics.

The most instructive case is the CMO. Marketing had real complexity and real risk. A brand crisis is genuinely costly. But it never developed a clean boundary. Marketing bleeds permanently into sales, product, and customer success. No one can agree where it starts and stops. The result: CMO tenure is the shortest in the C-suite and the title keeps getting renamed and reorganised. Two out of three conditions is not enough.

Now run AI through the same test. Complexity: obvious pass. Risk: increasingly clear pass, as regulators attach accountability to executive leadership and the cost of AI failures becomes material. Coherence: this is where the wheels come off.

AI is not one bounded thing. It is simultaneously infrastructure, data strategy, process redesign, workforce transformation, customer experience, and strategic advantage. Every function has a legitimate claim on some part of it. That is why three executives in the same company can each be convinced AI belongs to them, and none of them is entirely wrong. It is also why, just like marketing, a dedicated AI role struggles to develop the clean mandate that durable C-suite positions require.

Why Each Contender Falls Short

The CTO has the most intuitive claim. AI is a technology, the CTO owns technology, case closed. Except the CTO's domain has always been defined by a specific boundary: infrastructure, systems, uptime, security. Things that keep the business running. AI does not respect that boundary. It rewrites how finance makes decisions, how HR evaluates talent, how operations manages supply chains, how sales forecasts revenue. A technology that reorganises every function in the business is not an infrastructure problem. The CTO is the right person to build the engine. Deciding where the car goes is a different job.

The CHRO has a claim that is real but time-limited. AI is unquestionably the most significant workforce disruption in a generation. Reskilling, role redesign, managing the human side of automation: these are genuine CHRO responsibilities and no one should understate them. But they describe a transition, not a permanent ownership model. Once the workforce has been reshaped, the CHRO's specific claim on AI dissolves. You would not ask the CHRO to permanently own the internet because it transformed how people worked in the 1990s. Owning the disruption is not the same as owning the asset.

The CAIO looks like the obvious answer until you ask a simple structural question: what does this role actually own? Every durable C-suite position owns either an asset class or a risk class. The CFO owns capital. The CTO owns systems. The CHRO owns the workforce. The CISO owns security risk. The CAIO owns a method. AI is a type of technology, not an asset class and not a risk category. You would not create a permanent Chief Cloud Officer or a Chief Analytics Officer. CAIO is the same category of thinking, made more compelling only because the technology is more dramatic. The job descriptions confirm the structural weakness: they read as liaison briefs. Partner with, coordinate with, support. That is not the language of ownership.

Who Wins and How It Settles

When something starts behaving like capital, it migrates to whoever owns capital allocation. The data, fine-tuning, and institutional knowledge a company layers on top of a base model is proprietary, it compounds over time, and a competitor cannot simply buy the same thing off the shelf. That is not infrastructure and it is not a workforce programme. It is an asset, and assets raise questions that are already the CFO's territory:

•  What are we investing, and what are we getting back?

•  Is this building durable value, or a recurring cost dressed up as capability?

•  What is our exposure if we become dependent on one vendor or one model?

CFOs know this. CFO involvement in AI strategy has grown faster than any other function over the past two years. They did not wait to be invited. They followed the capital, as they always do.

Having said this, the most likely outcome in the short run is AI governance staying distributed across CTO, CDO, and CHRO, coordinated through standing committees, with the CFO holding real decision-making authority over investment, returns, and risk. The CAIO title will survive where regulators or boards want a named individual accountable for AI risk, for the same reason the CISO survived: when the risk is sharp enough, accountability needs a name on the door. But as strategic owner of AI as a firm-wide asset, that is not what the CAIO job description describes, and there is no structural reason to expect it will.

But once the dust settles, the answer, is probably not the one with "AI" in their job title. My bet is that it’ll be the CFO.

 

Book Review | AI Nation - Bharat’s Path to AI Power | Dr Ajay Kumar

Ajay Kumar has spent decades shaping India’s technology and defence landscape, including serving as Defence Secretary and currently as Chairman of UPSC. So when he writes about AI, he’s not looking at it as just another tech wave, but as something deeply tied to national strategy and sovereignty. The book, reflects that perspective. It’s not a “how AI works” book. It’s more a “what India must do next” book. And having read it I felt it needed to be reviewed. 

This is not a conventional book review - at least not in style . Instead, I tried to imagine a conversation with Ajay Kumar -  based on what his book  is really saying. The questions are mine. “Ajay Kumar’s” answers  are my interpretation of his ideas in the book.

A Conversation (Imagined but based on the ideas in the book)

Me: Ajay, let’s start simple. Everyone and their chachaji has an opinion on AI today. But your book feels very different - it’s less about tech, more about power. What made you write this now? And how should we read it?

Ajay Kumar: When the Printing Press was invented it just didn’t enable more people to read books. It changed power equations in society. It led to sweeping changes in European thought. It divided the church, and led to wars. Similarly when the Industrial Revolution began, it looked like it was about better machines. It didn’t look like a geopolitical shift. Only later did it become clear that those machines were quietly redrawing the balance of power between nations. We may be at a similar moment again. 

AI is no longer equitable in its implications. It is shaping economic competitiveness, influencing geopolitical balance, and even affecting democratic processes.

For India, this creates a dual reality. There is a significant opportunity to be capitalised on , but also a real risk of becoming dependent on external technological ecosystems. That is why this moment requires strategic thinking, not just technological adoption.

.

Me: We’ve always been told tech levels the playing field. You’re basically saying the opposite - that AI is widening the gap. And honestly, it already feels like a US - China game. Are we already too late to the party?

Ajay Kumar: The concentration you are observing is real, and it is the result of long-term structural advantages. Both the United States and China have built deep and integrated AI ecosystems over decades. These include world-class research institutions, access to vast datasets, significant computational infrastructure, and strong linkages between government, industry, and academia.

In the US, innovation has been driven by a combination of universities, venture capital, and highly dynamic private enterprises. China, on the other hand, has demonstrated the ability to align national priorities, mobilise state resources at scale, and rapidly deploy technologies across sectors.

Another important factor is continuity. AI did not become a priority overnight; it has been the result of sustained investment and focus. This has created a situation where AI increasingly rewards those who already possess scale - of data, compute, and talent - leading to further concentration of power.

However, it is important to recognise that AI is still evolving. Many of its most critical challenges remain unsolved. This provides an opportunity for countries like India to innovate in areas where incumbents are not optimised - such as population-scale applications, multilingual systems, and cost-efficient AI. The gap is significant, but it is not insurmountable - provided the response is strategic and timely.

Me: Let’s bring this closer home. Right off the bat you talk of 100 million jobs enabled by AI in India. This sounds huge and exciting ..... but also slightly “too good to be true.” When you look at compute, data, education and all of the other stuff you discuss - this feels too messy. Lagta hai ki, bhaiyya, itna toh hum se na ho paayega.  What actually needs to click for India to pull this off?

Ajay Kumar: You are correct in observing that this is a multi-dimensional challenge. The vision of large-scale job creation is anchored in India’s demographic and technological strengths. However, realising it requires alignment across several critical pillars.

First, human capital. India must invest in large-scale skilling and re-skilling, extending beyond elite institutions to reach smaller towns and diverse segments of the population. Second, infrastructure, particularly compute and data. AI development is inherently resource-intensive. Without access to computational capacity and well-governed data ecosystems, innovation cannot scale. Third, institutional collaboration. Industry, academia, and government must work in close coordination to ensure that education, research, and deployment are aligned. Fourth, strategic clarity. India must avoid the trap of imitation and instead focus on areas where it can build differentiated capabilities.

The risks arise when these elements evolve in isolation. Fragmented efforts, limited access, or delayed policy responses can significantly dilute the potential. In essence, the opportunity is large, but it is contingent on execution at scale and with coherence.

Me: This all sounds great on paper. But all of us know that India mein ground reality thodi different hai. Do we really get the urgency - or will we treat this like another policy ideation document?

Ajay Kumar: That is a legitimate concern, and one that must be addressed candidly.

Institutional readiness often determines the success of any large-scale transformation. But the good news is that AI itself, by its nature, compresses timelines of innovation and disruption, which can galvanise traditional policy processes. Also, India has demonstrated, through initiatives in digital public infrastructure and large-scale technology deployment, that it can execute complex programmes when there is alignment and clarity of purpose.

The key requirement now is to extend that capability into the AI domain. This involves building capacity within government, fostering deeper engagement with industry and academia, and adopting more agile and adaptive policy frameworks. Equally important is recognising the urgency. AI does not operate on conventional cycles, and delayed responses can have long-term consequences. 

The transition will not be automatic. It will require leadership, institutional learning, and sustained focus.

Me: Let’s drop the diplomacy for a second. What’s our biggest weakness in this race?

Ajay Kumar: Our greatest challenge is not a lack of potential, but timely execution at scale. India possesses significant advantages - talent, data, and a strong digital foundation. However, translating these into coordinated and sustained action is the need of the hour.

The window of opportunity is finite. If we act decisively, we can shape outcomes and create new areas of leadership. If we delay, we risk becoming dependent on external ecosystems. The choice is both strategic and immediate.

Me: Let me ask this bluntly. Do our policymakers really “get” how big this moment is? And, as Chairman of UPSC, are you now looking for a very different mindset in the next generation entering the system?

Ajay Kumar: Let me also answer it directly as there is no other way to do so. Yes many of policymakers do get it (perhaps more than what you may think)  and yes it’s also true many don’t. And I hope my book in a small way may help the latter category see new perspectives.  And not only the new aspirants but I hope every Indian will open their minds to the opportunities and challenges. 

AI is not just about what we build. It is about what we choose to become.

My Comments :

This book offers a clear and comprehensive view of the many ways AI will shape the nation - going beyond broad ideas to presenting concrete suggestions and actionable initiatives. More importantly, what Ajay Kumar has written is not a book with final solutions, but has initiated a conversation - one that all Indians, and particularly policymakers, need to engage with. The writing is lucid and accessible, and the structure of each chapter - with abstracts and conclusions - makes it easy to grasp key ideas quickly without losing depth.

Kudos Ajay.

My Book Rating : 5 stars.