Based on the sources, here is the full text of the article from the August 4, 2026, edition of Mint:
India’s data centre boom faces a gridlock
States race to build transmission lines as large data centre capacities loom
By Yadukrishna C.S. Mumbai
India’s booming data centre and artificial intelligence (AI) sector is hitting a power hurdle. Backed by massive global funding, these huge facilities are expanding beyond the metros into smaller towns, making the power grid infrastructure—transmission lines, transformers and substations—struggle to keep pace.
Over the past 12 months, domestic conglomerates, Big Tech firms such as Google, Amazon, Microsoft and Meta, and standalone operators have committed over $250 billion for data centre construction. On 27 July, the power ministry informed Parliament that data centres may add 26.3 gigawatts (GW) of load to the national grid by FY32, emphasizing the urgent need to expand infrastructure. As of June 2025, India’s operational data centre capacity stood at 1.12GW.
For operators, the primary bottleneck has shifted from land to power. "Securing adequate, reliable, and scalable power has become increasingly challenging," said Sunil Gupta, chief executive of Yotta Data Services, the Hiranandani Group's data centre and AI infrastructure arm. "The most significant delays come from constructing high-voltage substations and transmission lines, which require their own land acquisition, right-of-way clearances, and regulatory approvals across utilities and local authorities," Gupta added.
The grid crunch is already playing out at the state level. In Odisha, while current power infrastructure can handle existing demand, upcoming projects are pushing the grid to its limits. The state has enough infrastructure to support up to 80 megawatts (MW) of data centre load, but "scaling to hyperscale campuses will demand entirely new transmission infrastructure," said Hemant Sharma, Odisha's additional chief secretary for industries.
Addressing these bottlenecks will come with a massive price tag, with the net investment likely to run into “a few lakh crore rupees," said Sridhar Pinnapureddy, chief executive of Hyderabad-based CtrlS Datacenters. The cost-sharing model varies across states. State power distribution companies (discoms) typically fund substations—unless built inside a data centre campus—while developers pay for transmission lines, step-down transformers, and internal campus cabling.
Since releasing its data centre policy in April 2022, Odisha has drawn significant technology investments. Key projects include a ₹14,257 crore AI-ready data centre from HCLTech and unicorn Sarvam, an ₹800 crore investment by the Adani Group, and smaller sites such as CtrlS’s 5MW unit in Chandrasekharpur and Airtel subsidiary Nxtra’s 1 MW facility.
Now, the state is racing to install the required power infrastructure. Sharma told Mint, "we are installing a new 220kV substation... in 12-14 months". “We’re then installing a new 765kV power grid, which will take roughly 2.5-3 years to build," Sharma added. High-voltage power substations are crucial for running power-hungry facilities such as data centres without sapping the electricity meant for consumers and other industries.
Odisha is not alone in acknowledging the transmission infrastructure shortage. A senior official at the Maharashtra State Electricity Transmission Co. Ltd said the state’s power transmission infrastructure is under severe stress. The official noted that if a data centre wants 500MW or 1GW of power capacity within a year, that demand cannot be met. Mumbai's total demand currently stands at close to 4.5GW; supplying the next 5GW would need new 400kV and 765kV substations and high-voltage transmission lines. "Building this would take 4-5 years," the official said.
The state is working to meet this demand. On 13 March, Bajel Projects Ltd announced a deal worth over ₹700 crore from MSETCL to establish a 400kV power substation. In total, public and private firms have poured ₹1,500 crore into upgrading Maharashtra’s power infrastructure over the past four months. The state government said in March it has signed deals for ₹5 trillion of data centre investments and expects an additional 5GW by 2030.
Apart from infrastructure shortages, Chennai, India’s second-largest data centre hub, faces a challenge with land for new substations. “Existing data centres are accommodated, but expanding capacity takes years as land for new substations is scarce," a senior official said.
This mismatch between project construction and infrastructure deployment was echoed by Gupta. He noted, “Today, data centres are ready in 12-18 months and solar farms in 18-24 months. But transmission infrastructure still takes 3-4 years, which is why regulators, discoms, transmission utilities and private companies need to plan long-term”.
A July 2026 report by KPMG said the rise of AI workloads is expected to sharply increase demand for higher-capacity electrical infrastructure. AI racks typically require 50-60kW of power each, compared with 8-12kW for conventional data centre racks.
Based on the sources, here is the article titled "Why the IBC ruling is a win for homebuyers" from the August 4, 2026, edition of Mint:
Why the IBC ruling is a win for homebuyers
Promoters of insolvent real estate firms can no longer use the Insolvency and Bankruptcy Code (IBC) to fend off homebuyers’ legal action. The Supreme Court has ruled that the IBC moratorium protects only the company, not promoters or directors. Mint explains
By Yash Tiwari & Krishna Yadav
What was the case before the SC?
Homebuyers of Bengaluru’s Mantri Manyata Energia project moved the National Consumer Disputes Redressal Commission (NCDRC) in 2023 against the developer, its promoters, directors and others, alleging failure to hand over homes by the promised 31 December 2018 deadline despite receiving payments. After the company entered insolvency, the NCDRC stayed the case under the Section 14 moratorium, prompting the buyers to move the Supreme Court. A Section 14 moratorium pauses legal and recovery proceedings against a company during insolvency.
What did the Supreme Court hold?
A bench of Justices Vikram Nath and Sandeep Mehta on 27 July held that Section 14 moratorium applies only to a corporate debtor and cannot be extended to promoters, directors, subsidiaries, personal guarantors or other non-corporate parties unless the law specifically provides otherwise. The court said proceedings against promoters and directors may continue if based on their independent legal liability, even as cases against the company remain stayed. It also held that NCDRC should have stayed proceedings against the company and allowed the case against the remaining respondents to continue.
What does the ruling mean for promoters?
The ruling increases promoters’ accountability without automatically making them liable. Lawyers said creditors can pursue promoters during a firm’s insolvency, but their personal liability must still be established. They expect the judgment to have implications beyond real estate by clarifying the limits of the IBC moratorium where insolvency proceedings run alongside civil or criminal actions against promoters. It could also lead creditors to pursue promoters and guarantors earlier.
Why is real estate insolvency different?
Real estate insolvency is complex because it affects not just lenders but also thousands of homebuyers. Since the IBC lacks a project-wise insolvency framework, developers with multiple projects are resolved at a company level. As of September 2025, 221 ongoing real estate insolvency cases involved about 109,000 homebuyers. An Insolvency and Bankruptcy Board of India (IBBI) committee has recommended a project-wise framework to speed up project completion and improve protection for homebuyers.
What does the ruling mean for homebuyers?
Lawyers said the ruling clarifies that the Section 14 moratorium does not bar proceedings against promoters and directors, allowing homebuyers to pursue them, likely improving recovery prospects. Homebuyers made up 43.9% of the 5,785 complaints IBBI got, making them the largest stakeholder group under IBC, as per an IBBI Governing Board note (2022).
Based on the sources, here is the article "Will a pause put RBI behind the curve?" from the August 4, 2026, edition of Mint:
Will a pause put RBI behind the curve?
By Deepa Vasudevan
Amid rising inflationary risks from the West Asia war and El Niño, the RBI faces a dilemma over whether to hold repo rates or hike them to curb mounting price pressures.
When the Reserve Bank of India’s (RBI’s) Monetary Policy Committee (MPC) meets this week, it will face a choice between holding the policy repo rate and raising it from 5.25% currently. Both courses of action have some justification. A pause makes sense given that economic growth remains robust and inflation has surpassed the RBI’s 4% target rate only once this year (in June 2026).
A pre-emptive rate hike to shield against inflationary pressures and protect capital inflows also seems justified—after all, many advanced-economy central banks (Europe, Japan, Australia) began tightening earlier this year. If the RBI chooses to pause, as widely expected by market experts, will it fall behind the curve? A central bank is “behind the curve” if it fails to raise rates quickly in response to inflation. Naturally, the RBI is not expected to respond to a single over-4% inflation print with a rate hike. But if it waits too long and reacts too slowly, it risks a rapid build-up in inflation.
The MPC meeting is currently underway and a decision will be announced on Wednesday. All 10 economists polled by Mint expect a pause in rate and a neutral stance in the current meeting. Several economists described it as a policy “nonevent”, but said the RBI's communication is likely to strike a cautious, if mildly hawkish, tone.
TAYLOR’S RULE
In 2022, James Bullard, then president of the Federal Reserve Bank of St. Louis, identified two ways to assess whether a central bank was behind the curve. The first approach is to use monetary rules such as Taylor’s Rule to determine the appropriate level of policy rates. If the actual policy rate is below the recommended rate, then the bank is likely to be behind the curve. A simple Taylor specification for India, assuming a 4% inflation target, 7% potential growth rate, and equal coefficients on inflation and output gaps, suggests that monetary policy was tighter than prescribed until recently. However, the RBI seems to have fallen slightly behind the curve in April-June: according to Taylor’s Rule, a rate hike is recommended.
Of course, there are drawbacks to following monetary rules. Policy rates adjust slowly over a rate cycle; they cannot be instantly increased or decreased as per rule-based benchmarks. In addition, recommendations are only as good as underlying assumptions—even a slight change in model parameters can completely alter the interpretation. For example, if the neutral interest rate is set at 1.5% (instead of 1.65%), the Taylor Rule throws up a recommended policy rate of 5.20%, suggesting that the RBI may need to cut rates.
MARKET SIGNALS
A second, and more intuitive approach is to rely on market rates such as the highly traded 1-year Overnight Interest Swap (OIS) rate, which is a reasonably good predictor of the policy repo rate. The 1-year OIS rate has been on an uptrend since the US-Iran war started in February; it dropped slightly in June after measures were announced to shore up dollar inflows. By mid-July, renewed hostilities in Iran and rising oil prices pushed OIS rates up again. On 30 July, the 1-year OIS rate was about 5.95%. This suggests that markets expect the repo rate to rise by 70 basis points, which implies at least two 25 bps hikes in the current financial year.
INFLATION-RUPEE MIX
But monetary policy is much more than following a formula or reading market signals. Rate decisions need to reflect current economic reality while simultaneously being forward-looking. Three other factors are likely to influence the MPC:
- First, while inflation is rising, it has not yet become so broad-based. In June 2026, items with 32% weight in the CPI basket had inflation above 4%, and 24% had inflation over 6%. For comparison, during the previous high inflation episode in Jan-Dec 2022, the corresponding shares of over-4% and over-6% weights were 79.5% and 52.8%, respectively.
- Second, there is considerable uncertainty about the future path of inflation. The resumption of US-Iran hostilities could push up oil prices: indeed, the price of Brent crude has already surged above $100 per barrel in July. El Nino is another key risk: uneven rainfall distribution, delayed start of monsoon, and lower reservoir levels add to inflation risk. The fact that inflation is not broad-based across all items favours a pause, but the threat of El Nino fuelling food prices favours a hike. Uncertainty over inflation trajectory is not limited to India: last week the US Federal Reserve, the Bank of Japan and the Bank of England all opted to pause rates.
- Third, the rupee continues to fall, despite RBI intervention and the prospect of dollar inflows through the Foreign Currency Non-Resident (Bank) and External Commercial Borrowing route. The total amount of dollars mobilized will be known only by September. Until then, it is tough to predict whether these flows will stabilize the rupee.
POLICY ROOM
The August MPC is important because there are consequences to falling behind the curve—once inflation is high and entrenched, it is harder to manage with monetary policy. But it is not a now-or-never decision. IMF research shows that a small delay, when combined with aggressive rate action, is equally effective in controlling inflation. We saw this in the last two rate hike cycles: RBI started raising rates after some months of over-4% inflation, but made up for it with rapid rate hikes that brought down actual inflation as well as household perceptions of inflation.
Hence, pausing now may not mean falling behind the curve, provided the RBI signals a willingness to act swiftly if inflation pressures build up in the coming months.
The author is an independent writer in economics and finance.
AT A GLANCE
- The Reserve Bank of India faces a critical choice between maintaining the 5.25% repo rate or raising it to manage emerging inflationary risks.
- Taylor’s Rule suggests policy was tighter than required lately, but recent economic shifts suggest the central bank may slightly lag behind inflation trends.
- Market indicators like 1-year Overnight Interest Swap rates show rising expectations for around two rate hikes due to geopolitical tensions and surging oil prices.
- While inflation remains contained within specific sectors, potential risks from uneven monsoon rains and energy costs may need future rapid policy adjustments by the RBI.
Based on the sources, here is the article "Iran déjà vu: Trump once again threatens, retreats" from the August 4, 2026, edition of Mint:
Iran déjà vu: Trump once again threatens, retreats
The hardball strategy aims to create movement in negotiation through pressure and chaos
AP WASHINGTON
President Donald Trump has played this hand before during the 5-month-old Iran war. It starts with a grim warning to Tehran that the Republican president is on the cusp of ordering US forces to “obliterate” its power plants or seize key parts of its oil industry if its leaders don’t quickly agree to US terms to end the war. It ends with him edging away with a last-minute declaration, sometimes at the behest of Gulf allies, that he’s going to give diplomacy more time.
The hardball strategy—one that Trump honed during his years competing in New York’s real estate scene and has employed in politics—aims to create movement in negotiation through pressure and chaos. But the tactic is facing a challenge with an Iranian theocracy that believes it holds a higher threshold for strategic pain than Washington.
While Trump has revelled in the US military decimating layers of Tehran’s leadership and devastating its air force and navy, Iran is betting it can outlast Trump as he faces diminished stockpiles of munitions and the difficulty of executing a war that is unpopular with the American electorate ahead of November’s midterm election.
The latest episode began on Friday when Trump, surrounded by his Cabinet, grimly declared that he was “losing faith” in negotiations with Iran and warned that the US military “will be hitting them very hard”. Hours later, the White House press secretary Karoline Leavitt heightened speculation in Washington—and around the globe—with an ominous statement asserting “Iran will continue to pay until they come to the table in, what President Trump deems, a meaningful way”.
But by late Saturday night, Trump declared on social media that there were signs of progress on reaching an agreement and he was calling off a plan to carry out new, massive strikes for the time being. The next day Trump emphasized that requests to give diplomacy more time from unnamed Iranian officials as well as leaders from Gulf allies—Qatar, Saudi Arabia, and the United Arab Emirates—were key to his about-face.
“It would have been disastrous for them. And they didn’t want us to do it,” Trump said of Iran as he spoke to reporters on his way back to Washington from a weekend at his New Jersey golf club. “And frankly, Saudi Arabia didn’t want it either. They thought that a deal is imminent”.
Trump may still come to the conclusion that a massive escalation in the conflict with Iran is necessary. But critics say his hesitation also might reflect an unspoken understanding inside the administration that US military might alone may not be enough to compel Iran to back down and bring an end to a now months long war that Trump had earlier downplayed as a weeks long excursion.
“I think what we’re seeing here is a president who has an approach that’s just rather erratic,” said Sen. Mark Kelly, an Arizona Democrat on the Senate Armed Services Committee, on CBS News’ “Face the Nation”. “At this point, he’s trying to get us back to February. And I think if he could—if he had a big reset button he could hit—he would certainly take that option”.
There have been several moments over the course of the conflict when Trump has demonstrated his proclivity for the bellicose only to back off at the last minute, while declaring his threats spurred progress. In early April, the US and Iran agreed to a two-week ceasefire in an announcement that came less than two hours before a deadline Trump had set for Tehran to capitulate or face attacks on bridges and power plants—strikes he said would mean “a whole civilization will die”.
After days of dire threats against Iran, Trump announced on 18 May he was holding off on a major planned military strike because “serious negotiations” were underway, crediting Gulf allies for persuading him to show restraint. With this latest episode, Trump suggested that Saudi Crown Prince Mohammed bin Salman played a particularly important role in him turning away from escalating the fight. The US president spoke by phone with the de facto leader of the kingdom on Saturday before announcing he was halting strikes that he later boasted would have been one of the biggest US operations since World War II.
Based on the sources, here is the full text of the article from the August 4, 2026, edition of Mint:
Amazon joins list of stocks to top $3 trillion in value
Amazon joins Nvidia, Alphabet, Microsoft and Apple as the only companies that have reached that size
Bloomberg
Amazon.com Inc. surpassed $3 trillion in market value for the first time, becoming only the fifth company to ever reach the milestone. The e-commerce and cloud-computing company’s shares rose as much as 5.3% as of 9:35am on Monday, adding to the raucous rally last week following second-quarter earnings that showed accelerating cloud-computing revenue.
Amazon joins Nvidia Corp., Alphabet Inc., Microsoft Corp. and Apple Inc. as the only companies that have reached that size. Amazon had been mired in a selloff for much of the last three months as investors soured on shares of companies that had committed to spending billions of dollars on artificial intelligence. Its stock sank nearly 18% between its May 6 record and the three-month low it hit last month.
Those fears were eased last week after the firm reported that revenue for its Amazon Web Services unit last quarter jumped by the most since 2021. Shares surged more than 15% in response, their biggest one-day jump in more than 14 years, to add nearly $400 billion in value. That’s helped propel Amazon back into position as the best-performing Magnificent Seven stock this year.
The gauge of its big tech peers has struggled this year, gaining only 2.1% compared to a 10% gain for the broader S&P 500 Index. While the rally has lifted Amazon’s valuation from the 17-year low it hit in late March, it’s still far below where it has traded historically.
At roughly 25 times forward earnings for the next 12 months, the stock is about 44% cheaper than its average over the last decade. It took Amazon just over two years to reach a market capitalization of $3 trillion after first hitting $2 trillion in June 2024. That’s faster than the more than six years between that milestone and when it first hit $1 trillion in late 2018.
Wall Street remains overwhelmingly upbeat on Amazon’s long-term prospects too. The average analyst price target calls for the stock to rise about 14% over the year from where it currently trades, according to data compiled by Bloomberg.
Based on the sources, here is the article titled "Inside the sudden layoffs at Visa India" from the August 4, 2026, edition of Mint:
Inside the sudden layoffs at Visa India
By Samriddhi Mahar Mumbai/Bengaluru
On an ordinary day, a Visa Inc. employee would log in, pick up work from the previous day and go through emails and routine tasks. In recent months, some found themselves with more time on hand as automation took over parts of their jobs. Few, however, expected the first email of the day to be their last in the company: from human resources informing them that they had been laid off. For employees in India, the emails came between 4 am and 5 am on 29 July.
Visa, the $40 billion San Francisco-based payments company, said on 28 July that it would cut about 7% of its workforce, roughly 2,600 roles. Chief executive officer (CEO) Ryan McInerney told employees the reductions were meant to drive efficiency. McInerney said on an earnings call on 28 July that AI is changing how work gets done at Visa. “Today, we announced that we are eliminating roles, with the majority being in our technology and product teams, to ensure that we are continuing to position Visa for future growth,” the CEO said. “Now, as we enter the era of agentic power of AI to execute work and tasks with our supervision”.
He said agentic commerce will expand the company’s addressable market and drive growth for Visa. Agentic commerce refers to the emerging use of autonomous AI agents to research, select, negotiate and make purchases on behalf of humans.
Visa did not say how many of the roles being eliminated would be in India, its largest technology base outside the US. Its global headcount rose about 8% in fiscal 2025 to roughly 34,100. While the number of employees in India is not public, the company said in a statement in 2024 that its workforce exceeds 3,500 employees here. Visa operates corporate, business and major technology hubs in India from Bengaluru and Mumbai, with additional corporate presence in Chennai and Hyderabad. Bengaluru is the company’s primary large-scale technology and software development centre.
Mint spoke to six former and current employees from India to piece together what happened last week. All of them spoke on condition of anonymity; Visa did not respond to queries. The cuts were deep enough to hollow out whole teams. On one India team of 28 people, 10 were let go, employees said. Seniority did not help; among those who lost their roles were several long-serving managers.
Severance packages varied widely and came with roughly 15 to 30 days of notice. “Some are getting a lot and some are getting less,” one employee said. Although they were asked to serve notice periods, many employees had to hand over their ID cards and laptops and their access to company email was removed by Friday.
The Bengaluru office emptied out within days. On Friday, people had been scuffling about to find places to sit; by Wednesday the place was dead silent. “Seeing your colleagues’ empty tables hurts a lot, and you can be the next,” said an employee who was told their jobs were safe. Several of those laid off turned down invitations from former teammates for a farewell. “When I reached out to all of them, most of them were not ready to come,” one employee said. They did not want anything to do with the company that had just let them go.
The Visa job cuts show how AI is slowing the pace of hiring and taking over or supplementing some roles in companies. Goldman Sachs, in a 28 July report, said 8% to 12% of India's non-agricultural employment is at risk of substitution from generative AI and 42% to 48% of jobs are more likely to be complemented by it. Total jobs in IT and related roles in India in June stood at 1.7 million, while global capability centres added 700,000 people in three years.
“For instance, in financial services, Gen-AI can complement analyst roles by automating some form of basic modelling, but may completely substitute routine back-office functions like basic compliance checks,” Goldman Sachs said. The advent of AI has also led companies to reduce hiring; total new hires at nine of the 30 Sensex companies fell 27% between FY24 and FY26.
The cuts at Visa did not come out of nowhere, employees said, even if the timing was a surprise. Over the preceding months, contractor hiring was pulled back and spending on outside software vendors was cut with the justification that AI could replace some of it. In July, caps appeared on AI tool usage where access had been open before. Developers in the US said they were expected to use large language models for their work, then handed a $1,500 monthly limit on tokens. “This is the fourth such cost-cutting measure within the last quarter,” a Bengaluru-based employee said.
The contradiction is not lost on the people in Visa. AI is simultaneously the reason costs have escalated and the justification offered for headcount reduction. “It's making us more efficient but as expected by the CXOs,” the person said. “But for the employee, the cost has gone out of hand”.
Based on the sources, here is the full text of the "Long Story" article from page 12 of the August 4, 2026, edition of Mint:
Why most AI pilots end up in the graveyard
Scaling AI isn’t a technical problem—it requires fixing messy data and redesigning legacy processes
By Mastufa Ahmed New Delhi
Tata Steel has spent eight years building artificial intelligence (AI) into the fabric of its business. Today, more than 680 AI applications run across the steel major’s operations in India. They monitor equipment for early signs of failure, process invoices, and guide engineers through troubleshooting before a breakdown occurs.
Soummo Bose, the company’s chief AI officer, does not call any of it ‘artificial intelligence’. “We call it augmenting intelligence,” he says, reflecting the company’s belief that AI should enhance human capability rather than replace it.
The distinction matters. That journey took a decade of investment in data infrastructure and specialized talent before a single model went into production. Most Indian enterprises have not made that investment. Getting AI to work was never the hard part. The harder part is everything that comes after—embedding it into legacy systems, redesigning how people work, and proving it is worth the cost.
Flirty business
There used to be a joke among Indian technology leaders: There were more AI pilots in Indian enterprises than airline pilots in Indian skies. Rajesh Nambiar, president of Nasscom, the IT industry’s lobby body, still uses the line, but with a different conclusion attached. “We’re now beginning to see many of those pilots move into production,” he says. “That’s the good news”.
But the headline tells only part of the story. Nearly half of Indian enterprises—47%, according to a 2026 EY-CII survey of 200 companies—now have multiple AI use cases running in live workflows. But running AI in one department is not the same as running it across an organization. Data from Nasscom and IBM’s Institute for Business Value independently found that only 15% of organizations have reached that harder milestone: scaling AI cross-functionally, with unified governance and measurable outcomes across the business. “Many organizations are flirting with AI,” says Nambiar. “Only 15% are actually scaling it”.
Prasanto Kumar Roy, a Delhi-based technology policy advisor and a former technology editor, has a sharper description for what the rest are left with. “Many businesses are now AI pilot graveyards,” he says. “Proof-of-concepts that may have been successful on their own, but created operational friction when forced to scale enterprise-wide”. Rishi Aurora, managing partner at IBM Consulting, sees another pattern. Some companies, he says, treat AI as a “tick-in-the-box exercise”, pursuing programmes largely to demonstrate progress to their boards.
Where it worked
The companies that have crossed from experimentation into operational AI share one characteristic that has nothing to do with the sophistication of their models. They started earlier, invested longer, and built the foundations that allowed AI to disappear into everyday operations.
At Tata Steel, the journey began eight years ago. Its internal platform, the Tata Steel Digital Assistant or TDA, has an unexpectedly mundane origin: when ChatGPT launched in 2023, the company blocked public generative AI platforms over data security concerns and built its own alternative. Today, TDA runs nearly 200 AI agents used by more than 12,000 officers across India and some UK group companies.
The more consequential work sits inside the plants. Predictive modelling applied to critical equipment has improved availability by between 5% and 20% depending on the asset. Invoice processing has reached approximately 95% automation. The employee who once validated every line item now reviews only what the AI flags as uncertain. “Data and talent have been our two strategic investment vectors for the good part of the last decade,” says Bose. “The results you see today are not something we turned around in a year”.
Apollo Hospitals has 20 certified AI algorithms—12 in live clinical use, having processed 5 million interactions (API calls) across its platforms over two and a half years. What distinguishes Apollo is its operational discipline. Each certified system carries a monthly tracker covering uptime, error rates, and change frequency. Value is assessed per 100,000 interactions. One disease-progression tool is projected to generate approximately $9 million in revenue for every 100,000 patient assessments it processes, based on what comparable healthcare systems in developed markets charge for similar diagnostics.
“The differentiator between organizations that scale and those that stall,” says Dr Sujoy Kar, Apollo’s chief medical information officer, “is whether AI is treated as a governed clinical capability or a procurement decision”.
The impact of AICVD, Apollo's cardiovascular risk prediction tool, is most visible in the patients it identifies before symptoms appear. Confident grew gradually as its predictions were repeatedly validated through clinical evaluations. “Rather than waiting for disease to become clinically apparent,” says Dr Kar, “the clinician can now intervene earlier with greater confidence, using AI as a trusted decision-support partner while retaining full responsibility for the final clinical decision”.
At Hindustan Unilever’s Haridwar factory, recognised by the World Economic Forum as a Global Lighthouse site in June 2026, an AI-powered ‘Supply Chain Nerve Centre’ coordinates production in real time. Response times have fallen 72%, inventory days are down 24%, and on-time in-full (OTIF) delivery has reached 99%.
At DBS Bank India, a generative AI content-capture tool used by 1,500 branch employees has cut data-entry time by around 50%. More than two-thirds of the bank’s India employees now use generative AI as part of their daily work.
The sandbox trap
Getting a pilot to work is one thing. Scaling it across the enterprise is another. “AI can look sexy when the ‘AI guy’ in a company picks up a problem or two and uses prompts to show how quickly he can get outputs,” says Roy. “But they can’t scale that”.
The reason is rarely the model. The hardest part begins after the pilot works, says Vic Gupta, executive vice president and head of product development at Coforge. “Technology is rarely the constraint. Change management, process redesign, ownership, and governance usually are”.
Four failure modes emerge consistently across the companies that have tried:
- Data: At Kirloskar, the journey of an AI-powered quality inspection tool from pilot to production became an education in what controlled environments hide. The pilot worked on curated datasets, but met a far wider array of defect combinations in the real-world factory environment. Ashok Jade, CIO of Kirloskar Brothers Ltd, calls this the ‘sandbox trap’—the gap between data tidy enough to prove a concept and data reflecting industrial reality.
- Portability: At Tata Steel, findings showed that models do not travel. A model built for one piece of equipment cannot be replicated on another because every asset operates under different conditions. Apollo encountered the same: its cardiovascular risk tool required full recalibration when deployed abroad.
- Process: “You cannot force-fit the process,” says IBM’s Aurora. “You put AI on top of a current process and expect magic to happen. That is not going to happen”. Saurabh Mittal of DBS Bank India echoes this, noting value comes from redesigning workflows around what AI makes possible.
- People: Deploying AI at scale is a change management challenge. Tata Steel runs a ‘Divisional AI Month’ to demystify the technology and build deployment roadmaps with business units.
The guardrails
As AI moves into daily operations, the question of responsibility arises. IBM’s Institute for Business Value found that 77% of executives say AI adoption is outpacing their oversight capabilities.
Apollo Hospitals uses its EASE framework to evaluate ethics, adoption, suitability, and explainability across 18 criteria. DBS Bank India uses the PURE framework to ensure data use is purposeful, unsurprising, respectable, and explainable. Tata Steel requires every AI system to clear cold, warm, and hot trials before going live. “The best performers bake compliance directly into the product lifecycle,” says Roy.
The destination
Most Indian enterprises still derive AI value from efficiency gains, but this is not the ultimate destination. “If you are deploying agentic AI effectively,” says Nambiar, “the objective should not simply be cost reduction. It should be about changing your business model, entering new markets, reaching new customer segments”.
Apollo Hospitals applies this to AI economics: a model must demonstrate a credible economic case to earn the investment needed to expand. Similarly, at Kirloskar, every AI initiative is tied directly to a performance indicator owned by the business unit.
Indian enterprises have realized only about 20% of AI’s overall potential. Closing that gap does not require a better model, but foundational investments in data and process.
KEY NUMBERS
- 15%: Organizations that successfully scaled AI cross-functionally with unified governance and measurable business outcomes.
- 200: AI agents run by Tata Steel’s digital assistant, used by over 12,000 officers.
- 3.5 million: Patient assessments that used Apollo Hospitals’ cardiovascular risk prediction tool, AICVD, over the last five years.
- 62%: Technology executives who expect to be scaling AI broadly across their organizations by 2030.
Based on the sources, here is the full text of the article from the August 4, 2026, edition of Mint:
Is Gift City the new Mauritius? It’s luring foreign F&O traders
It offers foreign portfolio investors looking to trade derivatives on the NSE an attractive avenue
By Amit Baid
For decades, the story of foreign capital entering India had a familiar opening line: it began somewhere else—usually in Mauritius. Between 2000 and 2024, Mauritius accounted for nearly one-fourth of India’s foreign direct investment—about $179 billion. It was India’s largest single-country source. The island nation was a legal address through which global capital reached India. An entire ecosystem grew around one idea: the right tax treaty could transform the returns on investing in India.
That idea is fading. As treaties narrowed and scrutiny intensified, Mauritius lost its shine. Another island nation, Singapore, has overtaken it in recent quarters. But the more interesting development is that smart capital is no longer looking for overseas islands.
The successor is a stretch of reclaimed land on the banks of the Sabarmati: the Gujarat International Finance Tec-City (Gift City) and the International Financial Services Centre (IFSC) within it. And what it offers is fundamentally different from the model it is replacing. The old structures depended on borrowed advantages—a treaty, a residence certificate and the tax relief they promised. Gift City offers something that need not be borrowed at all: a tax outcome written directly into Indian law.
The Gift City proposition is particularly compelling for foreign investors trading listed Indian derivatives. A non-resident can establish a Category III Alternative Investment Fund (AIF) in Gift City, obtain foreign portfolio investor (FPI) registration and trade futures and options (F&O) on the NSE and BSE. Profits from such trading are exempt under India’s own domestic tax law, rather than a treaty or any concession granted by another jurisdiction.
For derivative trading strategies, this is transformative. F&O trading is high-volume and margin-driven; it often invites tax disputes over whether gains are capital or business income and whether an offshore vehicle genuinely qualifies for treaty relief. The Category III IFSC fund sidesteps all of it. Indian law itself treats the fund’s securities as capital assets and exempts trading income, so the two questions that haunted the old structures fall away.
Since such a fund takes no recourse to any treaty, an entire layer of controversy disappears—no treaty shopping, no principal purpose test, no limitation of benefits clause and no debate over treaty substance. India’s General Anti-Avoidance Rule (GAAR) framework goes further by specifically carving out FPIs that do not resort to any treaty benefit, placing them beyond the reach of GAAR itself. The structure rests entirely on Indian law, instead of a bargain struck with another country.
Gift’s substance requirements are deliberately light: a small office and two or three professionals are generally enough to run a fund. And since 2025, even that can be outsourced—an overseas manager can simply plug into an independent, locally licensed platform.
In practice, the local Gift entity provides the regulated presence, while the offshore investment team drives investment decisions using sophisticated tools that enable those calls to be attributed to the Gift platform. In that sense, it resembles Mauritius—arguably with even lighter substance, but within India’s own legal perimeter.
Capital is responding. By March 2026, cumulative commitments to Gift funds had crossed $39 billion, according to the International Financial Services Centres Authority. Even India’s benchmark Nifty derivatives, long traded on Singapore’s exchange, have since come home to Gift City.
As capital pours into Gift City, substance matters more than ever. The framework may not demand a heavy on-ground presence, but that is not the same as substance being optional. Courts can still apply substance-over-form principles even where statutory GAAR does not apply (often described as ‘judicial GAAR’). The Supreme Court’s reasoning in the case of Tiger Global is a good example. Today, judicial GAAR poses little threat to funds in Gift City because the platform is a stated national priority, and is promoted, backed and actively encouraged by the government.
But such priorities are not permanent. Should the policy mood shift, the same substance-over-form reasoning that unsettled treaty structures could, in principle, be turned towards even a government-favoured platform. The exemption is statutory but the goodwill around it is political. Wise investors should invest on the basis of genuine substance rather than relying on the political disposition.
The lesson is simple. Gift City rewards those who bring real activity onshore—real managers, real decisions and real risk. It punishes the letterbox.
So, is Gift City the new Mauritius? The question understates it. Mauritius was a clever fix for an era when India taxed foreign capital heavily. Gift City reflects India’s decision that global capital should no longer need another jurisdiction to invest tax-efficiently in India. It reflects an India that has chosen to compete.
Mauritius’s biggest competitor may no longer be another island. It may simply be India itself.
The author is head of tax, BTG Advaya.
Based on the sources, here is the article titled "Why your body never forgets exercises" from the August 4, 2026, edition of Mint:
Why your body never forgets exercises
The brain stores movement patterns that make returning to exercise easier
By Pulasta Dhar
When starting a fitness activity, consistency matters most in the beginner phase. This is because, for the muscles, it is the first phase or the cognitive phase of learning new moves and patterns—just like when you typed on a keyboard for the first time, or learnt how to catch a ball or tie your shoelaces. The more you do this task, the more the body starts understanding other factors like how much weight is too little or too much.
Despite its name, muscle memory is less about the muscles alone and more about the brain and nervous system remembering how to perform a movement. “As your muscles don’t have the capacity to retain memories like your brain does, they increase the amount of muscle fiber nuclei (myonuclei) within the trained muscle cells,” says a medically reviewed article on Cleveland Clinic’s website from 2025. “Think of these as crew members on a boat. The more members rowing the boat, the better it will perform in a race. As myonuclei increase, so does your muscle mass.”
The same principle also helps explain why returning to a sport after a long break is often easier than expected. It could be getting on a bicycle ten years after you last rode one, or returning to the football pitch after a long-term injury derailed you.
“Neural memory is what your brain and spinal cord remember: movement patterns like hitting a badminton smash, riding a bicycle, or kicking a football. Your strength and fitness decline with inactivity, but the blueprint for the motor movement often remains. You may be slower or weaker initially, but the nervous system relearns much faster than it learned the first time,” says Udgam Baxi, a neurosurgeon in Vadodara with a FIFA-accredited diploma in football medicine.
The National Academy of Sports Medicine (NASM) put out a YouTube video on this topic a year ago, on their Peak Fitness Podcast. This also helped explain “newbie gains”—the rapid uptick in muscle size and strength when one starts regularly lifting weights for the first time—and their links with creating new neural pathways.
“People who just start lifting are creating different pathways and will see a sudden rise in the neuromuscular control and strength output. These are especially evident in the first 6-12 months of training and an athlete might gain almost twice the muscle in the same period as a more experienced lifter,” says NASM trainer Andre Adams in the video.
All of which means that maintenance work to stay fit is not just for size and strength, but to make sure the movement patterns you learnt in your fittest days continue to be used. Aside from that, learning entirely new movements offers other benefits too and help develop neuroplasticity: the more frequently and correctly you practice a movement, the stronger the neural pathways become.
The more often you practice a movement, the stronger the neural pathways become.
