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.

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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.

Review: Saanp Seedhi (Theatre) - Aadyam Productions - Kamani Auditorium Delhi

As I exited the Kamani Theatre in Delhi after watching "Saanp Seedhi," I bumped into a friend. Here's how our conversation unfolded:

Friend: "Saanp Seedhi" dekh ke aa rahe ho? Aadyam Productions ka hai na? Kaisa laga?

Me: Yaar, honestly, pehle pehle toh laga, "Yeh kya hai?" You know I love Aadyam’s programming. So expectations are always that there will be some dhamaal - big cast, bade sets ya phir complex narratives. Kuch toh hat ke hota hai hamesha. Aur yeh... Felt a bit... thanda.

Friend: Thanda? Like, boring?

Me: Nahi, nahi, boring nahi. More like, simple. You know, seedha-saadha. Just two characters and a living room. Linear narrative. It started ordinarily but then, dheere dheere, it got interesting.

Friend: What’s it about? You mentioned two characters. Who are they? Aur batao.

Me: Ok. First is Anil Wadhwa, Bollywood obsessed, maker of B Grade crime films. Aur there is Mayank, younger, bit stylish, architect. Anil ko pata hai ki Mayank ka chakkar chal raha hai uski wife Kavita ke saath. Aur woh Mayank ko apne ghar bulata hai, "Let’s have a chat," bolke.

Friend: Apne raqib ko apne he ghar bulaata hai?

Me: Haan. Unusual toh hai. Love Triangles toh bahut sune hain par a husband drinking and chatting with his rival in his living room is a first for me.

Friend: Phir?

Me: Anil, glib talker hai. And chaalu bhi bai. He appears nonchalant. He's like, "Okay, fine, she's leaving me for you. What can I say. But bhai, take it from me. I know her for 20 years. She's high maintenance. You need money, which I know you don’t have. But main hoon na - so don’t worry”. He suggests Mayank steal the jewels kept in his safe. Khud se chori karne ka plan samjhata hai usko.

Friend: Wait. Apni biwi ka lover. Apne hi living room mein. Aur khud se chori karne ko kah raha hai? That's quite a novel plotline.

Me: Exactly. Mayank, pehle toh suspicious ho jata hai. But then, he gets sucked into it. They start rehearsing the robbery. Aur phir, kab role-play role play hai aur kab real real hai gets blurred. Audience gets drawn in.

Friend: So, it's not just about the affair anymore?

Me: Nahi, that was just the trigger. It soon becomes about ego, pride and battle of wits. They vie for dominance in the verbal mind games. Saanp Seedhi title is perfect. Kabhi ek character metaphorical seedhi pe chadhta hai toh lagta hai woh aage hai, aur phir kabhi saanp ne kat liya toh woh phir neeche.

Friend: Hmmm. Phir?

Me: Phir - Is sab chori ke role playing ke beech, a gun gets fired and one of them slumps backwards on the sofa. The audience is caught by surprise.

<Lights Out> <Curtain Falls for the interval>

Friend: I think I’ll like it. Check karta hoon if they have tickets the next show.

<Friend leaves to check for tickets>

Well, I think you guys too get the drift. Overall, the storytelling is quite tight, flows well, and is quite funny in bits. Kumud Mishra (as Anil Wadhwa) is very good. Sumeet Vyas (as Mayank) seems tentative in comparison, especially in the first half. The direction by Shubrajyoti Barat is fine without being exceptional. The set design is more photogenic but clunky at some places.

By the way, the play itself is a Hindi adaptation of a Tony Award-winning play called “Sleuth” by English playwright Anthony Shaffer.

It’s certainly worth seeing, if you go without expectations. But I’ve seen better ones from the Aadyam stable.

My Rating: 3.5 Stars.

The Art and Science of Prediction

 We face danger whenever information growth outpaces our understanding of how to process it

Data driven predictions can succeed - and they can fail. It is when we deny our role in the process that the odds of failure rise. Before we demand more from our data, we need to demand more from ourselves.

Prediction is important because it connects subjective and objective reality.

We must become more comfortable with probability and uncertainty

How can we apply our judgement to the data - without succumbing to our biases.

The signal is the truth. The noise is what distracts us from the truth

We focus on those signals that tell a story about the world as we would like it to be, not how it really is. We ignore the risks that are hardest to measure, even when they pose the greatest threats to our well-being. We make approximations and assumptions about the world that are much cruder than we realize. We abhor uncertainty, even when it is an irreducible part of the problem we are trying to solve.

Hedgehogs are type A personalities who believe in Big Ideas - in governing principles about the world that behave as they were physical laws. (Specialised, Stalwart, Stubborn, Order-Seeking, Confident, Ideological)

Foxes are scrappy creatures who believe in a plethora of little ideas and in taking a multitude of approaches toward a problem. (Multidisciplinary, Adaptable, Self-critical, Tolerant of Complexity, Cautious, empirical)

Foxlike approach to forecasting: - Think Probabilistically, Good predictions  can and should change as more information becomes available, Look for consensus, Beware Magic-bullet forecasts

The word objective is sometimes taken to be synonymous with quantitative but it isn't. Instead it means seeing beyond our personal biases and prejudices and toward the truth of a problem. 

   

Chandni Raatein (Review) - Theatre

Chandni Raatein (Adapted and Directed by Purva Naresh)

My Rating: 4 Stars

The generation in India that once read Russian writers like Fyodor Dostoevsky (or Chekhov, Gogol, Tolstoy, Gorky, and Pushkin, for that matter) has passed. The romance of Tsarist times is long forgotten, and the short story as a literary form is fading. In this landscape, adapting a Russian classic for the Indian stage is an unusual and ambitious choice.

It takes courage for a young director like Purva Naresh to bring White Nights, a short story by Dostoevsky, to life as a large-scale theatrical production—especially for an Indian audience. Yet, she has done so with remarkable finesse, earning a standing ovation. This speaks not only to her creativity and theatrical craft but also to her deep understanding of Indian audiences. What likely drew her to this project is the timeless nature of love—proof that matters of the heart transcend geography and culture.

The Original Storyline

On the luminous summer nights of St. Petersburg, a lonely dreamer meets Nastenka on a quiet bridge. As they share their hopes and sorrows beneath the city’s glowing sky, a deep bond forms. He longs for love, while she waits for someone from her past. Over four nights, their connection deepens with laughter, confessions, and unspoken emotions. But as dawn approaches, the bridge that brought them together may also be where their paths diverge.

From White Nights to Chandni Raatein

In Purva’s hands, however, Chandni Raatein is to White Nights what a Margarita is to Tequila. The essence remains—Dostoevsky’s blend of melancholy and hope —but it is blended with additional characters, personas, and garnished with music and dance. The result is a sprightly cocktail that leaves you refreshed yet slightly intoxicated with emotion.

Performance and Production

Most of the cast delivers above-average performances, but Mantra Mugdh (as Deewaana) and Kaustav Sinha stand out. The set design and production are commendable, with the 19th-century bridge serving as the central motif, beautifully capturing the twilight of the Russian summer. One particularly striking detail is the human statue painted in silver, standing in a corner of the stage—an almost living prop that adds depth to the mise-en-scène.

Lighting, singing, and music are all well-executed, but what truly sets this production apart is its direction. The fluidity of movement, effective space utilization, and seamless transitions between parallel settings keep the audience engaged throughout. A particularly whimsical touch is the introduction of human personas who enact the inner emotions of the characters. Not only does this add humor, but it also serves as a bridge between the audience and the unfolding drama.

Striking the Balance in Adaptation

Adapting a work like White Nights is no easy feat. It requires a delicate balance between staying true to the original and making it relatable to contemporary audiences. Purva attempts to achieve this by blending Indo-Russian cultural elements into the play. While this works in many places, at times, it feels slightly force-fitted. Given that this was not a full-fledged musical, the production could have done with one or two fewer songs without losing its impact.

Aadyam

A word must be said about Aadyam. The development of art and culture has always required patronage. In earlier times, kings and rulers supported great artists, writers, and poets. Today, Aadyam, an initiative of the Aditya Birla Group, is playing a similar role in Indian theatre. By funding high-quality productions and keeping ticket prices manageable, it allows directors to focus on their art rather than commercial constraints.

Take a bow, Purva. Well done, Aadyam. Without your combined efforts, an adaptation of White Nights would likely have been confined to an Experimental Theatre @NCPA, Mumbai, playing to a small group of intellectuals—instead of filling a 600+ packed house at Kamani.

Visual Arts, Creativity and Gen AI

When it comes to AI, everyone has a crystal ball. So do I. Today, I asked mine to tell me what the future holds for all visual imagery being created by the likes of Midjourney, Stable Diffusion, and their cousins in the world of AI.

It thought long and hard—and this is what it said:

Generative AI will emerge as an independent art form, like painting, photography, digital painting, and visual effects. It will draw inspiration from these existing disciplines but mimic none of them.

Knowing well my penchant for a reasoned answer rather than mere soothsaying, it went on:

Let’s examine some traditional and current visual creation mediums along multiple dimensions and see where AI art fits on them.

Abstraction vs Realism Axis: A Picasso cubist painting is his imagination on canvas, with only a passing reference to the human form it depicts. Contrast this with Steve McCurry’s photograph of the Afghan Girl or Jeff Widener’s photo of the Chinese man standing during the 1989 Tiananmen Square uprising—they are as real as it gets. A painter lives in the abstract while a photographer creates very close to the physical world. Perhaps a VFX artist operates somewhere in between, often moving back and forth along this axis. What about AI art? While future advancements may blur these distinctions, at current levels of technology, AI art is easily distinguishable from a photograph. But this does not reduce its aesthetic appeal. As time goes by, AI artists will likely embrace the unique characteristics of their medium rather than be embarrassed by them, positioning their creations at points along this axis away from the extremes of total abstraction and physical realism.

Degree of Control and Flexibility in the Creative Process: A painter has maximum control, manipulating every brushstroke and colour as desired. A digital artist has a vast, yet finite, array of controls embedded in software menus. A photographer works with the few controls offered by the camera. When it comes to Generative AI, the artists have the least control. Even with rigorous prompt management, they must accept how the model interprets their textual or voice commands.

Human Instruments of Creation: Painters convey their ideas using their hands. Photographers use their eyes, looking through the camera lens. AI artists only need to type or talk. These different human mechanisms used in the creative process suggest that the art forms will also be inherently different, each with its own evolutionary cycle. The simplicity of AI art creation may invite a broader range of people to explore and contribute to this new medium.

Iteration and Reproducibility: Most painters create iteratively, starting with basic sketches and refining them until they are satisfied. They can redo parts of their creation if needed. However, even an accomplished painter would find it difficult to reproduce their own work. A photographer captures images instantly and can quickly decide if a retake is necessary, though their ability to make selective corrections is limited. AI artists, akin to painters, require iterations, but like photographers, their output is available for immediate evaluation. Their ability to correct parts of the creation falls between that of a painter and a photographer. Additionally, AI artists can never be certain that reproducing their work will yield identical results.

At this point, I wanted to get into the topic of copyrights but the crystal ball ran out of battery life. I will ask it more after I have recharged it.

But you get the drift. We have a new art form being created as we speak albeit with some ifs and buts.

The Thursday Murder Club Mystery - Richard Osman. A review

Imagine, if you will, a book where Wodehouse's humour ambles hand in hand with the intrigue of an Agatha Christie novel. Enter the realm of "The Thursday Murder Club Mystery", the inaugural instalment in a series of novels by Richard Osman, an English TV presenter and comedian turned novelist.

Set in the tranquil retirement village of Coopers Chase, deep in rural England, the novel centres on four septuagenarian residents—Elizabeth, Joyce, Ibrahim, and Ron—who assemble every Thursday to immerse themselves, just as a pastime, in the delightful business of piecing together murders that lie buried in police files. Hence the name "Thursday Murder Club".  It's as though the spirited children from Enid Blyton's mystery series (remember Fatty, Larry, Bets et al.?) have journeyed through a time warp and are now confronting the perils of old age with unchanged enthusiasm for crimes in their backyards.

The setting of this secluded village in the verdant English countryside, nestled against a chapel, a forest, and a graveyard atop a gentle hill, appears idyllic—a full-service terminus for life's natural conclusion, and as we soon discover, for some premature endings as well.

The residents of Coopers Chase, each bearing a backstory as rich as the next, are united by their stage in life as well as a shared determination to protect their haven from disturbance. The humour here is dry enough to necessitate a refreshing sip, but refrain from overindulging, for the plot thickens at a brisk pace, with new characters frequently entering the fray (and some readers may justifiably bemoan their abundance)—you'll want to stay clear-headed to keep track of the comings and goings.

Our spirited club, under the leadership of Elizabeth, starts connecting the maze of dots, with a dexterity that belies their years, earning the reluctant friendship and admiration of the local police duo, Donna and Chris. Osman unfolds each revelation with the flair of a conjurer revealing rabbits from a hat—if, that is, the rabbits were red herrings and the hat the list of suspects, young and old.

This is a story that elegantly bridges the cosy and the clever, the light and the poignant, in a uniquely lovable and funny way. It's a tale that recognises life's value at every stage, suggesting that the purest joy comes from shared laughter amongst friends, ideally nestled in a comfortable chair, with a tantalising murder mystery to unravel before bedtime.

If you are looking for something to read that is light and yet engaging, put this one on your shortlist.

I have the next three adventures of the Thursday Murder Club quartet, waiting on my bookshelf, but before them, I must get back to reading yet another non-fiction book, which I had paused a few months back—"The Pashtuns: A Contested History" by Tilak Devasher.