Latest news with #Nilekani
The Hindu
3 days ago
- Business
- The Hindu
Multiple colliding market trends made Infosys reexamine business fundamentals: Nandan Nilekani
Multiple trends were colliding, in the global markets, and that led Infosys to reexamine the fundamentals of its businesses, said Nandan M. Nilekani, Chairman, Infosys. 'As we contemplate the developments of the last few months, we know we are in an era of uncertainty that we have never seen before. Multiple trends are colliding and leading us to reexamine the fundamentals of our businesses,' he wrote to shareholders in the company's annual report FY'25. He said, 'As geopolitics becomes front and centre in our lives, we are having to take cognizance of the world not as one single global market but as fragmented blocs and countries. This means making strategic choices and even navigating between these blocs.' According to Mr. Nilekani, COVID brought into focus the critical and pressing need to de-risk the supply chain and build viable alternatives. 'It was no longer enough to deliver just-in-time; we had to also factor in for just-in-case,' he told shareholders. He further said, now tariffs were further driving home the point that the company has to diversify its sourcing. 'Tariffs will be differentiated across products and countries and will likely keep changing. Bilateral and regional rules of trade will dominate. Supply chains will continue to shift as tariffs become another form of arbitrage,' he pointed out. Uncertainty with AI On AI, he wrote, its advent with all its possibilities and potential created another arc of uncertainty. As enterprises looked at applying AI to every aspect of the business, some long standing challenges would become imperative and self-evident to firms. For example, the need to modernise legacy systems, and the need to create data architecture so that all the firm's data would become consumable by AI, in a holistic manner, could no longer be put off, he elaborated. 'Firms will need to have an AI foundry for rapid innovation and an AI factory to scale successful innovations across the enterprise. While embracing AI will bring a goldmine of opportunities, it will not be entirely without some foreseeable risks,' he further wrote. Mr. Nilekani also stated that regulatory variances across regions would need to be incorporated into one's strategy. 'The early learnings from enterprise AI adoption gives us a glimpse of these potential challenges that lie on the path ahead,' he said. Moving on changes in Earth's climate system, he cautioned, climatic change and the associated energy transition added to the crucible of uncertainties. So much of the future depended on innovation and the form of energy that would fuel us forward – solar, wind, batteries, pumped hydro, green hydrogen, nuclear, carbon capture and storage, etc, he added. 'Global climate deals will set the pace of change. The only thing certain is that electricity will play a much bigger role in the days ahead. And the pace of its rollout will be contingent on building new transmission lines, setting up charging stations, and acquiring more transformers.' However, he added, this transformation would naturally be constrained by regulatory cholesterol. The price of various commodities will rise, and fall based on the speed of transition. And many assets could well be stranded. There was not a sector that remained unscathed as rapid business and technological disruption forced businesses to adapt and advance, he said, adding every business vertical was facing challenges of various kinds. Car makers were dealing with the transition from ICE engines to batteries. Pharma companies were looking at accelerating the pace of drug discovery with AI. Logistics companies were dealing with the complete reordering of global supply chains. Financial service companies were considering the tokenization of their assets. Energy companies were assessing the long-term demand for their products. Utilities were facing a distributed future. Manufacturing companies are navigating the advent of robots and 3D printing. Service companies were dealing with AI agents performing their tasks, Mr. Nilekani wrote.
Economic Times
3 days ago
- Business
- Economic Times
World no longer single global market, firms must navigate between fragmented blocs, countries: Nilekani
PTI As AI rapidly transforms the business landscape, Nilekani underscored the critical importance for enterprises to modernise their legacy systems and build robust data architectures to fully harness AI's potential. NEW DELHI: Global businesses can no longer view the world as a single market but must now navigate a landscape divided into fragmented blocs and countries, said Infosys Chairman Nandan pointed out that multiple trends are colliding, forcing companies to reexamine their fundamentals and make strategic choices in the face of growing geopolitical Infosys' annual report for FY25, Nilekani explained that as geopolitics comes to the forefront, companies are required to adapt their strategies and even make decisions about how to operate between these different blocs. "As geopolitics becomes front and centre in our lives, we are having to take cognisance of the world not as one single global market but as fragmented blocs and countries. This means making strategic choices and even navigating between these blocs," Nilekani said. The COVID pandemic brought to spotlight the pressing need to reduce risks in supply chains and develop reliable backup options. Relying solely on just-in-time delivery was no longer sufficient; companies also had to prepare for unexpected disruptions, the IT veteran noted. "Tariffs are further driving home the point that we need to diversify our sourcing. Tariffs will be differentiated across products and countries and will likely keep changing. Bilateral and regional rules of trade will dominate. Supply chains will continue to shift as tariffs become another form of arbitrage," Nilekani said. He added that artificial intelligence (AI), with its possibilities and potential, creates another arc of uncertainty. As AI rapidly transforms the business landscape, Nilekani underscored the critical importance for enterprises to modernise their legacy systems and build robust data architectures to fully harness AI's potential."The advent of AI with all its possibilities and potential creates another arc of uncertainty. As enterprises look at applying AI to every aspect of the business, some long standing challenges will become imperative and self-evident to firms," he need to modernise legacy systems, and the need to create a data architecture so that all the firm's data is consumable by AI, in a holistic manner, can no longer be put off. He urged enterprises to have an AI foundry and an AI factory to fuel innovation and scale. However, Nilekani also cautioned that the adoption of AI comes with risks, particularly due to varying regulatory frameworks across different regions. "While embracing AI will bring a goldmine of opportunities, it will not be entirely without some foreseeable risks. Regulatory variances across regions will need to be incorporated into one's strategy," he said.
Time of India
3 days ago
- Business
- Time of India
World no longer single global market, firms must navigate between fragmented blocs, countries: Nilekani
NEW DELHI: Global businesses can no longer view the world as a single market but must now navigate a landscape divided into fragmented blocs and countries, said Infosys Chairman Nandan Nilekani . He pointed out that multiple trends are colliding, forcing companies to reexamine their fundamentals and make strategic choices in the face of growing geopolitical uncertainty. In Infosys' annual report for FY25, Nilekani explained that as geopolitics comes to the forefront, companies are required to adapt their strategies and even make decisions about how to operate between these different blocs. "As geopolitics becomes front and centre in our lives, we are having to take cognisance of the world not as one single global market but as fragmented blocs and countries. This means making strategic choices and even navigating between these blocs," Nilekani said. The COVID pandemic brought to spotlight the pressing need to reduce risks in supply chains and develop reliable backup options. Relying solely on just-in-time delivery was no longer sufficient; companies also had to prepare for unexpected disruptions, the IT veteran noted. Live Events "Tariffs are further driving home the point that we need to diversify our sourcing. Tariffs will be differentiated across products and countries and will likely keep changing. Bilateral and regional rules of trade will dominate. Supply chains will continue to shift as tariffs become another form of arbitrage," Nilekani said. He added that artificial intelligence (AI), with its possibilities and potential, creates another arc of uncertainty. As AI rapidly transforms the business landscape, Nilekani underscored the critical importance for enterprises to modernise their legacy systems and build robust data architectures to fully harness AI's potential. "The advent of AI with all its possibilities and potential creates another arc of uncertainty. As enterprises look at applying AI to every aspect of the business, some long standing challenges will become imperative and self-evident to firms," he said. The need to modernise legacy systems, and the need to create a data architecture so that all the firm's data is consumable by AI, in a holistic manner, can no longer be put off. He urged enterprises to have an AI foundry and an AI factory to fuel innovation and scale. However, Nilekani also cautioned that the adoption of AI comes with risks, particularly due to varying regulatory frameworks across different regions. "While embracing AI will bring a goldmine of opportunities, it will not be entirely without some foreseeable risks. Regulatory variances across regions will need to be incorporated into one's strategy," he said.
Indian Express
03-05-2025
- Health
- Indian Express
Opinion AI isn't about to save us or kill us all. We must rethink the hype around it
In November 2024, The Washington Post carried a year-end article headlined, 'This year, be thankful for AI in medicine'. The gratitude was meant for, among other things, the remarkable accuracy with which chatbots are reportedly able to diagnose health conditions compared to doctors — even doctors assisted by the same technology. Infosys co-founder Nandan Nilekani recently pointed out, in a talk on AI hype, that we see hundreds of people injured daily in accidents caused by human-driven cars, but when an autonomous car causes even a minor accident, the manufacturer has to go back to the drawing board for two years to redo the technology. This, according to Nilekani, is because of the higher expectations we have of technology. The correct way of looking at it is that we know the technology does not know what it's doing, be it right or wrong, and so it cannot take blame or credit. So, a victim of an accident caused by an autonomous car has no remedy against anyone if the technology itself is legally approved. Similarly, if medical diagnoses by chatbots have 90 per cent accuracy as opposed to 74 per cent for doctors, it means the chatbot has been fed with enough data, trained well and equipped with the best hardware architecture. It also means chatbots could be extremely useful to doctors in treating people. To go a step further, as Bill Gates has done, and include medicine in the list of professions that AI will replace in future, would require AI to be able to reason like humans — or better — become conscious. Only then could even 100 per cent accuracy in medical diagnosis, the most brilliant legal analysis of a case or good performance in any field that requires dynamic and contextual input be considered trustworthy. Some reputed scholars back claims that AI will become conscious or truly intelligent soon, but there are reasons to believe they are feeding into a baseless frenzy. From the technological point of view, it is sufficient to know that the recent popularity of AI owes its origin to AI models called Large Language Models (LLM) that use neural network techniques or techniques inspired by biological neural networks. All famous AI applications like ChatGPT, Gemini and Llama are examples of this model. Yet, one of the 'godfathers' of AI, Yann LeCun, has recently gone on record to claim that LLMs will become obsolete in a few years. His advice to young techies is to work on 'next-gen AI systems that lift the limitations of LLMs'. The hope that some future AI model will emerge to remove the limitations of LLMs (rid them of hallucinations, make them understand natural language and make them conscious) cannot justify the hype today. LeCun's views align with those of longtime AI critics like cognitive scientist Gary Marcus, who has always held that problems like hallucinations and bias are inherent to such AI models and the industry is not being honest about their true potential. As Arvind Narayanan and Sayash Kapoor of Princeton's computer science department point out in their book, AI Snake Oil, 'Even if AI developers were to somehow accomplish the exceedingly implausible task of filtering the training of dataset to only contain true statements, it wouldn't matter. The model cannot memorise all those facts, it can only learn the patterns and remix them when generating text. So, many of the statements it generated would in fact be false.' They add that 'companies rarely share crucial information about leading language models' which may help researchers identify problems and warn users about when not to use them. The problem with the hype is not that AI is attracting attention. After all, there can be no doubt that the technology is proving to be extremely useful in diverse areas. There is also room for improvement, which requires investment and research. But when people are led to believe that the possibilities are limitless, they tend to ignore harms and abuses as side-effects or short-term sacrifices. In his book Taming Silicon Valley, Marcus mentions three tricks used by companies to feed the hype on AI: Claiming repeatedly without any tangible evidence that LLMs or today's AI models will lead to 'Artificial General Intelligence', creating a scarecrow out of China, and pretending that we are close to an AI that is going to kill us all (or save us all). This, according to Marcus, has got major governments of the world to take the narrative seriously and has made 'AI sound smarter than it is, driving up stock prices'. The hype is distracting us from what Marcus calls 'hard-to-address… risks that are more imminent (or already happening)… such as the damage to democracy from… misinformation, cybercrime etc'. In the name of 'scaling' or improving AI accuracy, companies are using bigger and bigger datasets without having to disclose how much copyrighted content they contain. More importantly, training LLMs requires humans to scan these datasets for toxic and harmful content. As Narayanan and Kapoor point out, 'labelling or annotating such content can be brutal'. Most of this work is done in developing countries, where labour is cheaper and less regulated. The hype is taking attention away from this human cost as well. To sum it up, if the goals of AI are only to increase efficiency in repetitive tasks or, in the words of the AI critic and philosopher Hubert Dreyfus, 'in isolated domains that do not connect with the rest of human life', then people will know when the resources that go into AI development are disproportionate. If, on the other hand, the goal is to replicate human intelligence, governments will have to make people literate about how this is going to be achieved. This is not just because public funds are being provided for AI initiatives but also because caution should not be thrown to the wind. There could also be more pressing research needs in areas like the life sciences from which private resources are being diverted. It is worth recalling Dreyfus's analogy about the AI situation way back in 1965, 'Alchemists were so successful in distilling quicksilver from what seemed to be dirt, that after several hundred years of fruitless effort to convert lead into gold, they still refused to believe that on the chemical level one cannot transmute metals. To avoid the fate of alchemists, it is time we ask where we stand.' 60 years later, I am afraid, we still have to ask the same question.
India.com
01-05-2025
- Business
- India.com
Indians hit JACKPOT..., India has treasure worth USD 3.3 trillion, Infosys co-founder Nandan Nilekani explains how
Nandan Nilekani believes India's real estate market could be a $3.3 trillion jackpot. (File) There is a massive jackpot worth a staggering $3.3 trillion waiting to be unlocked in India's real estate, and Infosys co-founder Nandan Nilekani has explained how Indians can unlock this gargantuan bounty by overcoming some major challenges in the coming future as the country heads towards becoming an $8 trillion economy by 2035. India's $3.3 trillion 'jackpot' In his report titled 'The Great Unlock: India in 2035', Nandan Nilekani notes that Indians hold around 50% of their assets in real estate with bank deposits coming in at a distant second at 15%. According to a Fortune report, the land capitalisation rate India stands at 5%, compared to almost 40% in the United States, which increases the likelihood of a surge in the rate of monetisable land assets with the creation of a unified ledger and a credible verification process, Nilekani's report says. Major hurdles must be overcome However, as per Nilekani's study, some difficult obstacles stand in the way, such as increasing income disparity, limited market access, low levels of formalisation, and low productivity. The study also points out that India's growth remains a concentrated to major urban areas, with 13 out of the country's 788 districts contributing to half of the GDP. Additionally, the top 10 percent among the wealthy account for around 60 percent of India's total income even as the phenomenon of migration driven by economic factors continues to rise, with over 200 million workers from poorer states migrating to other regions in search of better opportunities. What is real estate tokenization? The study by Nandan Nilekani advocates real estate tokenization which is the process of converting the value of a physical property into digital tokens that can be sold, traded on a blockchain platform. In this method, each individual token represents a fractional ownership stake in the property, which allows small-time investors who lack any major capital to participate in real estate markets. Experts assert that apart from boosting the accessibility to real estate investments, real estate tokenization also improves liquidity and transparency in the real estate market, the study notes. As per a EY report, tokenization would allow investors to buy and sell fractional shares, making entering and exiting investments very flexible.
