{"id":40137,"date":"2026-02-27T17:57:39","date_gmt":"2026-02-27T12:27:39","guid":{"rendered":"https:\/\/kuvera.in\/blog\/?p=40137"},"modified":"2026-02-27T18:01:46","modified_gmt":"2026-02-27T12:31:46","slug":"rise-of-the-robots","status":"publish","type":"post","link":"https:\/\/kuvera.in\/blog\/rise-of-the-robots\/","title":{"rendered":"Rise of the Robots"},"content":{"rendered":"

Artificial intelligence has captivated worldwide attention over the past few years. Tech giants and AI startups have cashed in on the euphoria. Investors have poured billions of dollars. And policymakers have laid out the red carpet.<\/span><\/p>\n

Behind all this excitement is a growing assumption embedded in markets today: AI will lift productivity, expand profit margins, and reward the companies that deploy it fastest.<\/span><\/p>\n

So, capital expenditure into data centres and compute capacity continues. Demand for chips stays high and supply remains a constraint. The working premise is that more intelligence, applied at scale, is unambiguously positive.<\/span><\/p>\n

But consider an alternative scenario.\u00a0<\/span><\/p>\n

It is June 2028. AI systems are performing exactly as designed. But the unemployment rate in the US has jumped to 10.2%. The S&P 500 has slumped 40% from its highs. Loan defaults have soared. And the broader economy has stalled.<\/span><\/p>\n

That, in a nutshell, is the fictional frame of a report released this week by Citrini Research.<\/span><\/p>\n

The 2028 Global Intelligence Crisis report asks a simple question \u2013 what if AI succeeds and that success creates strain?<\/span><\/p>\n

The report is written as a memo from June 2028 \u2013 a point in time where the AI systems are simply doing more of the work once performed by well-paid employees.<\/span><\/p>\n

The mechanism is straightforward. If AI materially improves white-collar productivity, companies reduce headcount. Cost savings are reinvested into further automation. Productivity rises again. Labour demand falls again.\u00a0<\/span><\/p>\n

What begins as margin expansion in software, consulting or professional services leads to job and salary cuts. Consumption weakens. Credit assumptions written during more stable income periods begin to look optimistic.<\/span><\/p>\n

Markets today appear to be pricing the first-order effects of AI adoption: higher productivity, stronger margins, durable competitive moats. Less clear is whether they are pricing second-order effects: distributional changes in income, shifts in labour\u2019s share and knock-on consequences for consumption and credit.<\/span><\/p>\n

The report was hypothetical but still shocked the markets. Shares of software companies in the US tanked, with IBM sinking the most in 25 years. The repercussions were felt in India, too. The Nifty IT index has dropped over 20% in February, the most since 2003. The 10 companies in the index lost a combined $68 billion in market value.<\/span><\/p>\n

To be sure, this is not an argument that a crisis is imminent. It is rather a question about transmission.<\/span><\/p>\n

The scenario assumes that substitution happens quickly and broadly across white-collar work. But history suggests technological change rarely unfolds so cleanly. New tools displace specific tasks, but they also generate complementary roles and new forms of demand. AI may substitute in some areas while augmenting labour in others.<\/span><\/p>\n

It also assumes that policy remains inert. In practice, institutions respond once stress becomes visible. Fiscal adjustments, labour-market interventions, and regulatory recalibration are not implausible if income displacement accelerates.<\/span><\/p>\n

Yet the distribution question lingers. In consumer-driven economies, higher-income cohorts account for a disproportionate share of discretionary spending. Even modest income impairment at the top can have outsized macro effects. Productivity can rise while wage growth slows. GDP can look stable while household balance sheets adjust unevenly. Equity markets can rally even as labour-market outcomes diverge.<\/span><\/p>\n

For long-term investors, the more constructive question is whether current asset prices implicitly assume that productivity gains will be broadly shared and that income stability at the top remains intact. If those assumptions prove optimistic, repricing need not be dramatic to be meaningful. It can emerge gradually through lower consumption growth, tighter credit conditions or reduced margin expansion.<\/span><\/p>\n

The value of the Citrini Research scenario lies less in its dystopian framing than in its reframing of the debate. Instead of asking how large the AI opportunity might be, it asks how the gains are distributed and what markets reprice if that distribution narrows.<\/span><\/p>\n

So far, markets appear confident in the AI productivity story. The distribution story remains less certain. That uncertainty does not invalidate the opportunity but broadens the lens through which it should be viewed.<\/span><\/p>\n

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\"SIP_Kuvera\"<\/b><\/strong><\/span><\/p>\n

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Cloudy Outlook<\/b><\/h3>\n

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AI isn\u2019t the only topic that is creating uncertainty the world over. Another big issue is the ever-changing US tariffs.\u00a0<\/span><\/p>\n

Late last week, the US Supreme Court scrapped most of the tariffs President Donald Trump has imposed since last year and said that he overstepped his authority under the 1977 International Emergency Economic Powers Act.<\/span><\/p>\n

The court didn\u2019t say whether the US government must refund the nearly $175 billion collected from these tariffs. But the ruling means that the tariffs that various countries had negotiated with the US under bilateral trade deals are no longer applicable. India, for instance, had negotiated an 18% rate under an interim agreement.<\/span><\/p>\n

As soon as the court blocked his tariffs, Trump found another way. He signed an order to impose a 10% tariff on all countries under a different law. These tariffs can last no more than 150 days, creating another layer of confusion.<\/span><\/p>\n

As if this wasn\u2019t enough, the US Commerce Department this week imposed preliminary countervailing duties on solar cells and panels imported from India, Indonesia and Laos, citing subsidies that disadvantage American producers. The general subsidy rate for Indian imports stands at 125.87%, with higher company-specific rates. A separate anti-dumping decision is due next month, with a final countervailing determination expected in July.<\/span><\/p>\n

The immediate market reaction was sharp. Shares of Indian solar manufacturers such as Waaree Energies and Vikram Solar fell as investors reassessed earnings exposure to the US market. Even Premier Energies was caught in the whirlwind, despite the fact that exports to the US account for less than 1% of its revenue.<\/span><\/p>\n

For Indian manufacturers, the concern is margin mix. Overseas shipments, particularly to the US, typically command higher realisations than domestic sales. Analysts estimate a meaningful share of order books remains linked to US demand for some players, while others have already reduced export reliance. Hence, the exposure is uneven.<\/span><\/p>\n

Yet this development was not entirely unexpected. The US had initiated investigations in August 2025 into whether manufacturers in India and other countries benefited from subsidies that distorted competition. Since then, companies have been recalibrating \u2013 expanding US manufacturing footprints, diversifying sourcing strategies or pivoting toward domestic and alternative export markets.<\/span><\/p>\n

The uncertainty now is structural rather than episodic. US solar manufacturing capacity has been ramping up under industrial policy incentives, even as project approvals and subsidy frameworks face periodic revision. Imports have already declined in value terms. Trade policy, in this segment, appears less cyclical and more embedded.<\/span><\/p>\n

What remains unclear is the final duty level and how durable enforcement will be. Preliminary determinations often evolve. Anti-dumping findings could compound or moderate the current rates. Legal challenges are possible. Supply chains, as before, may adapt faster than policy architects anticipate.<\/span><\/p>\n

For investors, the key question is not whether exports fall. It is how resilient operating models are when market access becomes conditional and pricing power narrows.<\/span><\/p>\n

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Clear the Clutter<\/b><\/h3>\n

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Moving on to news related to our core interest area, the Securities and Exchange Board of India this week overhauled mutual fund rules. It removed some categories and added new ones, tightened portfolio boundaries, and allowed limited exposure to gold and silver across more schemes.\u00a0<\/span><\/p>\n

SEBI also directed mutual funds to use spot prices on domestic stock exchanges to value their physical gold and silver holdings from April 1, 2026, instead of using London Bullion Market Association prices to arrive at the valuation of gold and silver held by exchange traded funds.<\/span><\/p>\n

The changes affect an industry that now manages about $900 billion of assets, which have steadied markets when foreign flows turned volatile.<\/span><\/p>\n

Overall, SEBI has expanded the number of fund categories to 40 from 36. While it discontinued solution-oriented schemes such as retirement and children\u2019s plans, it introduced life-cycle funds and sectoral debt funds.<\/span><\/p>\n

The regulator also asked fund houses to merge schemes where allocations overlap, and imposed time-bound compliance \u2013 six months for most schemes, three years for thematic funds.<\/span><\/p>\n

At one level, this is administrative housekeeping. But the underlying shift is conceptual. The regulator is moving from labels to demarcation. Schemes must remain \u201ctrue to label\u201d, it said.<\/span><\/p>\n

Portfolio overlaps within the same asset management company are capped \u2013 50% between value and contra funds, and similar limits for thematic strategies. Monthly disclosure of category-wise overlap will now be mandatory.<\/span><\/p>\n

In parallel, equity and hybrid schemes can allocate a residual portion to gold and silver instruments, and life-cycle funds can invest up to 10% in gold and silver ETFs, derivatives, and InvITs. The metals are being formalised as diversification tools, not as core strategy shifts.<\/span><\/p>\n

The industry\u2019s rapid growth has created a proliferation of choices. SEBI\u2019s message is that choice must not become duplicated.<\/span><\/p>\n

For investors, the practical effect is unlikely to be immediate. But over time, clearer boundaries may reduce style drift and make fund selection less about marketing language and more about actual portfolio construction.<\/span><\/p>\n

Markets often move first and explain later. Regulation, when it works well, does the opposite.<\/span><\/p>\n

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Restore the Trust<\/b><\/h3>\n
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In key corporate developments this week, India\u2019s banking sector took a small hit to its reputation when IDFC First Bank disclosed a Rs 590-crore fraud in accounts linked to the Haryana government.<\/span><\/p>\n

The state quickly removed the bank \u2013 along with AU Small Finance Bank \u2013 from handling government business. A forensic audit by KPMG is under way, and four employees have been suspended.<\/span><\/p>\n

But markets do not wait for forensic audits. Shares of IDFC First Bank fell 20% on Monday, hitting the lower circuit.\u00a0<\/span><\/p>\n

The bank has said it has paid back a net amount of Rs 583 crore, including about Rs 22 crore in interest, to the state. Haryana Chief Minister Nayab Singh Saini told the state assembly that discrepancies were first detected in January and that instructions to close and transfer the accounts were issued before \u201cmore serious\u201d inconsistencies emerged in February. The matter has been referred to the State Vigilance & Anti-Corruption Bureau.<\/span><\/p>\n

Separately, Yes Bank said it detected unauthorised transactions in its multi-currency prepaid forex cards. It said unauthorised transactions worth $280,000 were approved on behalf of 5,000 customers. The payments were routed through 15 merchants in a Latin American country, it said, adding that it blocked some of those transactions.<\/span><\/p>\n

Based on disclosures so far, this does not appear to raise systemic capital or liquidity concerns. The financial quantum is small relative to the balance sheet of the private-sector lenders.<\/span><\/p>\n

The reputational impact, at least for IDFC First Bank, is harder to quantify.<\/span><\/p>\n

Government accounts are sticky, low-cost deposits. They signal institutional trust. Losing that business affects not just fee income but funding mix. More importantly, questions around internal controls \u2013 especially in public-sector linked accounts \u2013 introduce uncertainty about oversight standards.<\/span><\/p>\n

The market reaction reflects that uncertainty. When the issue is governance rather than credit demand, repricing tends to be swift. Investors attempt to estimate not only the financial hit but the secondary effects: potential regulatory scrutiny, tighter compliance costs, management bandwidth diverted to investigations.<\/span><\/p>\n

It is also a reminder of how operational risk surfaces. Banking risks are often framed in terms of loan books and asset quality. Yet control failures, if substantiated, can be equally disruptive. They do not always threaten solvency, but they can impair confidence. What will determine the trajectory now are the findings of the forensic audit, regulatory response, any widening of investigation scope, and whether similar discrepancies emerge elsewhere.<\/span><\/p>\n<\/div>\n<\/div>\n

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Market Wrap<\/b><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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India\u2019s stock market benchmarks fell this week and recorded their third consecutive month of decline, dragged down primarily by tech stocks. The BSE Sensex slipped about 1.8% for the week while the NSE Nifty 50 lost 1.5%. For the month, the Sensex declined 1.2% and the Nifty shed 0.6%.<\/span><\/p>\n

The Nifty IT index sank 19.5% in February on AI-related fears after US firms such as Anthropic unveiled advanced AI automation tools. This is its worst monthly performance since the global financial crisis erupted in September 2008.<\/span><\/p>\n

Almost two-thirds of the Sensex and Nifty stocks ended in the red for the week. Zomato and Blinkit parent Eternal was the top loser, falling over 8.5%. Among IT stocks, Tech Mahindra lost 6.8% while Wipro, Infosys and HCL Tech slipped 3-4% each. TCS did a tad better, falling less than 2%.<\/span><\/p>\n

Bharti Airtel skid almost 5% after it announced plans to spend Rs 20,000 crore on its digital lending business. Trent, ITC, Bajaj Finance, Bajaj Finserv, HDFC Bank, Larsen & Tourbo, and Asian Paints were the other prominent losers.<\/span><\/p>\n

Apollo Hospitals was the biggest gainer this week, rising 2.7%. NTPC, JSW Steel, Titan, Tata Steel, Shriram Finance, Bajaj Auto and Coal India were among the other winners.<\/span><\/p>\n<\/div>\n

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\"FD_Kuvera\"<\/p>\n

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Other Headlines<\/b><\/h3>\n

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