Understanding AI by Nicolas Sauburet (2019) AI 2041 by Kai-Fu Lee & Chen Qiufan (2020) Nicolas Sauburet’s Understanding AI (2019) tried to make sense of “intelligent machines” at a time when most people were still guessing what that meant. He talked about the computational complexity of real-world problems, that some might remain beyond the reach of even the fastest computers. He was spot on about one thing: AI would need massive processing power. What he probably didn’t imag

The fact that AI is now firmly inside the enterprise gets reinforced by the year end compilations from consulting firms and research institutions. The adoption is widespread, pilots are common and confidence in AI’s strategic relevance is indisputable. There is, however, a striking pattern that emerges from these publications. Few findings illustrate the pattern: - “88% of companies use AI in at least one function, but only 39% see impact on EBIT and most see less than 5%” (

If infrastructure and data architecture formed the technical core of Tata Steel’s transformation, the human system is what converted that foundation into sustained business value. Where many organisations treat the workforce as an obstacle in digital transformation, Tata Steel turned it into the primary enabler. Connected Workforce: The digital shift extended beyond machines into the workforce itself. Through digital IDs, safety wearables and an integrated workforce managem

If governance and strategy were the backbone of Tata Steel’s transformation, data architecture became the central nervous system that made real AI at scale possible. The Challenge - A decade ago, data sat in 30+ systems across IT and OT. Sensors streamed inconsistently. Networks couldn’t support real-time decisions. Everyone wanted AI, but the foundations were non existent. Tata Steel resisted the temptation to 'jump to the model' and instead rebuilt the stack in the right or

Governance & The One IT Shift Margin pressure didn’t break Tata Steel. It challenged them to reinvent how manufacturing is run. This is a three post series on how Tata Steel converted crisis into opportunity, even when others succumbed !!! A decade ago, Tata Steel faced a “perfect storm”: global overcapacity, shrinking margins, ageing assets and data scattered across 30+ systems. IT, Automation and Digital ran as separate functions and decisions relied on instinct rather than

This year’s Nobel Prize in Economics carries a message that feels uncannily relevant to the moment we are living through in AI. Joel Mokyr, Philippe Aghion and Peter Howitt were honoured for explaining how innovation drives long run growth and why that growth sometimes stalls. Joel Mokyr argues that inventions existed long before the Industrial Revolution, yet they rarely translated into sustained prosperity because useful knowledge was fragmented. Practitioners knew what wor

India’s digital scale has always been its strength, but over the last year, it has surged to become the new strategic frontier for the global AI race. We are witnessing a decisive moment where economics, infrastructure and policy are aligning at a pace few expected. Google has announced a $15 billion AI hub in Visakhapatnam, AWS has committed $12.7 billion toward cloud and AI-ready data centres in India and Microsoft announced a $3 billion investment toward cloud and AI skill

Further to my earlier post on Apple’s dilemma between perfection and pace on AI, where I had written about how the dawn of the AI era is proving to be Apple’s moment of reckoning, things now seem to be gathering pace at Cupertino. The headline development is Apple’s reported $1 billion annual deal with Google to access its Gemini model, featuring a staggering 1.2 trillion parameters, to run on Apple’s private cloud servers. The goal, a full Siri makeover, with Mike Rockwell n

Apple has never been first to arrive, only first to get it right. But in AI, even Apple might find that getting it right too late could cost it the lead. From Steve Jobs to Tim Cook, Apple’s story has been one of innovation, perseverance and trust. Yet as I followed the AI race between Google and Microsoft, one question kept coming up : why isn’t Apple part of the same conversation? The answer lies in Apple’s defining principle i.e. privacy. The same promise that built loyal

Every once in a while, a piece of writing reminds you why real journalism matters, the kind that doesn’t just inform but investigates, questions and connects the dots that others miss. R. Gurumurthy’s ET Prime article (Oct 10 2025) is one such work (Read here: bit.ly/ETPrimeAI10Oct ). It dives deep into how the AI race today is being driven as much by finance as by technology, a theme that echoed what I found earlier in Gary Rivlin’s AI Valley. Gurumurthy’s analysis “OpenAI

A review of AI Valley – Microsoft, Google and the Race to Cash in on Artificial Intelligence by Gary Rivlin Is AI already a high stakes game reserved for technology giants? That’s the question Gary Rivlin explores in AI Valley , a story that traces how a fascinating idea may still require the heft of economics behind it. The author follows the journey of Mustafa Suleyman, an International mediator & unlikeliest of protagonists, who would go on to co-found DeepMind with Shane