In a recent opinion piece published on Moneycontrol, veteran investor Punita Kumar-Sinha paints a rosy picture of India’s detachment from the global AI-driven market rally.
She argues that India’s lag—rooted in its domestically focused sectors like banking, industrials, and consumer goods—serves as a “natural hedge” against a potential AI bust.
With global markets propelled by semiconductor giants like NVIDIA (+38% YTD in 2025) and Taiwan’s Nanya Technology (+388%), India’s modest performers, such as Force Motors (+157%), are hailed for providing stability amid foreign institutional investor outflows of nearly ₹2 lakh crore this year.
Kumar-Sinha posits that this insulation from the “crowded AI trade” offers diversification, allowing India to weather corrections driven by overhyping, regulatory hurdles, or unmet earnings in AI infrastructure.
But let’s pierce this veil of complacency. Far from a strategic advantage, India’s exclusion from the AI race is a symptom of profound structural failure—a technological chasm so wide that catching up seems illusory without revolutionary overhaul.
The contrarian truth is stark: India cannot join this race. It trails by what amounts to six generations in core technologies like semiconductors and AI, produces barely 50,000 truly capable young entrants into the high-tech workforce annually despite its vaunted demographic bulge, and remains mired in underinvestment in human capital.
Until India commits to massive, sustained spending on education, R&D, and skilling—far beyond current token efforts—it is doomed to perpetual band-aid solutions: outsourcing low-value services, importing critical tech, and watching global powers like the US and China pull further ahead.
This isn’t diversification; it’s delusion, and it risks turning the world’s largest youth population into a ticking socioeconomic bomb.
Consider the technological lag first. Kumar-Sinha acknowledges India’s marginal exposure to semiconductors and hyperscalers but frames it as a buffer. In reality, this “absence” is a generational deficit that locks India out of the innovation loop.
Global AI leadership hinges on advanced chip design and fabrication, where process nodes measure progress in nanometers—each shrink representing a “generation” of efficiency, speed, and power. The US and Taiwan dominate at 3nm and below, enabling breakthroughs in AI training models that require exaflop-scale computing.
China, despite US export curbs on chips like NVIDIA’s A100 series, has surged ahead with domestic alternatives like Huawei’s Ascend processors, capturing 30% of global manufacturing while investing $143 billion in semiconductors since 2014. 
India? It’s stuck at 28nm nodes in nascent facilities like Tata’s Gujarat plant, roughly six generations behind (from 28nm to 22nm, 14nm, 10nm, 7nm, 5nm, 3nm).  This isn’t mere lag; it’s obsolescence. India’s overall critical tech score is a dismal 15.2 on global indices, far below the US (over 80) and China (around 70), encompassing not just semis but AI algorithms, quantum computing, and biotech. 
Why does this matter? AI isn’t a spectator sport. The rally Kumar-Sinha describes—fueled by Micron’s +166% gains or Palantir’s +114%—stems from ecosystems where hardware and software co-evolve.
India’s reliance on imports for 95% of its chips exposes it to geopolitical vulnerabilities, as seen in US curbs aimed at China but rippling to allies.  Initiatives like Semicon India, with its $10 billion incentives, are drops in the ocean compared to China’s $100 billion Big Fund or the US’s $52 billion CHIPS Act.
Without closing this gap, India’s “domestic stability” is illusory: its banks and industrials increasingly depend on AI for fraud detection, supply chain optimization, and consumer analytics. Lagging here means higher costs, reduced competitiveness, and eternal dependence.
Kumar-Sinha’s hedge? It’s more like hiding under a leaky umbrella while the storm rages.
Exacerbating this is India’s human capital crisis, where a massive demographic dividend morphs into a disaster. With over 600 million people under 25—more youth than the entire population of Europe—India should be flooding the tech market with innovators. Instead, it churns out barely 50,000 net new high-tech jobs annually from FY2026-28, as AI automation slashes entry-level hiring by 70% at IT giants like TCS and Infosys, which once absorbed 600,000 fresh graduates yearly.  
Sure, India boasts 1.4 million STEM graduates entering the workforce each year, and it holds 16% of global AI talent, projected to hit 1.25 million by 2027.   But quality trumps quantity. Employability in AI and ML roles hovers at 56%, with companies decrying a lack of “production-ready” skills—candidates who can deploy models, not just code basics.  
Over 40% of IT workers use AI tools, but this masks a deeper rot: 63% of the workforce needs reskilling by 2030, yet only 12% are deemed trainable in emerging tech. 
This failure isn’t accidental; it’s engineered by chronic underinvestment. India’s R&D spend languishes at 0.64% of GDP, versus China’s 2.4%, the US’s 3.5%, and Israel’s 5.4%.   Private sector involvement is negligible, with fragmented ecosystems and poor industry-academia ties stifling innovation.   Education fares worse: at 2.9% of GDP, it’s half the UNESCO benchmark of 6%, leaving higher education underfunded and outdated.  The Human Capital Index ranks India poorly, with underinvestment in health and skills squandering potential: a child born today will achieve only 56% of their productivity potential. 
Compare this to China’s pivot: post-2000, it poured trillions into STEM education, producing 4.7 million engineering grads annually with high employability, fueling its AI surge despite sanctions. 
Kumar-Sinha’s narrative ignores this rot. Her “resilient flows” from domestic investors prop up valuations, but they mask unemployment at 8-10% among youth, with 175 million idle or underemployed—a dividend turned disaster.   Without investment, India resorts to band-aids: gig economy platforms where AI displaces rather than empowers, or “Digital India” schemes that spawn volatile startups but no global champions. 
This perpetuates a vicious cycle: low skills beget low-value jobs, eroding the middle class and fueling inequality. As economists warn, business-as-usual will waste this window, turning youth into a liability amid automation.  
The stirring imperative? India must act now or forfeit its future. Triple R&D to 2% of GDP, channeling funds into AI labs and vocational training for 100 million youth. Forge public-private partnerships to upskill 63% of workers, prioritizing AI ethics, chip design, and data sovereignty. Emulate China’s talent repatriation or the US’s moonshot investments.
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