Mishik Sharma

Introduction In its Integrated Annual Report 2025-26, Reliance Industries Ltd (RIL) highlighted the launch of Reliance Intelligence, a dedicated initiative aimed at democratising artificial intelligence across India. The company committed ₹10 lakh crore over the next seven years to build gigawatt-scale AI-ready data-centres, described as “patient, disciplined, nation-building capital” for creating sovereign AI infrastructure. Powered by in-house green energy and starting with it's first gigawatt-scale data-centre in Jamnagar, this infrastructure will serve as a sustainable, high-performance compute backbone. Jio, with its extensive network and customer reach, is positioned to play a central role in achieving RIL's aim of developing multilingual, voice-first AI platforms that make intelligence affordable and accessible to individuals, MSMEs, enterprises, and institutions across India.  This is a potentially paradigm-changing initiative. Around the world, AI discussions remain do...

Indian e-commerce has reached a critical inflection point. With projections placing the sector at $280-300 billion GMV by 2030, quick commerce is not merely reshaping urban consumption — it is emerging as a structural force in the broader economy. Yet public and policy discourse continues to reduce it to two narrow narratives: a competitive battle between large platforms and small retailers, or a gig economy story centred on the precarity of delivery workers. Both framings are real. Neither is sufficient. Indian e-commerce has catalysed far more than either story captures: an explosive rise of direct-to-consumer (D2C) startups, from a few hundred in 2018 to around 10,000 by 2025; the quiet modernisation of millions of kiranas; the formalisation of industrial value chains that once operated through kinship networks and informal trust; and the reshaping of cultural identities and consumption rituals across Tier II and III India. To reduce this transformation to platform rivalry or gig wo...

Introduction A recent Economic Times report, published on 26 May, said that a crop of Indian startups are deploying workers to record home-service chores and industrial tasks for global robotics and AI laboratories. These companies are increasingly deploying workers to generate physical-world data — washing dishes, folding clothes, assembling components, operating machinery — that will ultimately train the next generation of embodied AI systems. This news has brought into focus both the promise and the peril of India’s emerging position in the global Artificial Intelligence ecosystem.  At one level, this creates employment opportunities and inserts India into one of the fastest-growing segments of the digital economy. At another, it raises a deeper strategic question: Is India once again becoming a supplier of raw material—this time digital—within value chains controlled elsewhere? The question is particularly relevant because the AI economy is entering a new phase. The first gener...

Introduction: India’s “100 Products” Moment On 12 May, DPIIT Secretary Amardeep Singh Bhatia said, at the CII Annual Business Summit 2026, that the central government is identifying around 100 products that the country still cannot manufacture in sufficient quantity despite possessing both domestic demand and a large industrial base. The list reportedly spans a wide range of industrial categories — from axles and bearings to electronic systems, industrial intermediates, machinery, and rare-earth-linked products. At first glance, such reports may appear to be another routine addition to India’s long-running manufacturing discourse. But the significance of this development lies elsewhere. For decades, much of India’s manufacturing conversation revolved around increasing production volumes, attracting investment, improving ease of doing business, or raising exports. What this latest policy thinking appears to recognise, however, is that the deeper challenge is not merely manufacturing out...

Introduction: The AI Supercycle and the Missing Layers Beneath It The world is in the middle of an AI supercycle. AI chip companies—especially those in East Asia and the United States—have witnessed enormous investor enthusiasm. Many of these companies have seen their market-valuations surge to trillions of dollars — which in turn have sharply increased the total valuations of national stock markets of those countries. The dominant global narrative of the AI era has therefore become deeply chip-centric. Artificial Intelligence is increasingly interpreted through the lens of GPUs, semiconductor manufacturing, frontier AI labs, and stock-market valuations. Countries lacking globally dominant AI-chip companies are casually described as "missing" the AI boom. India, in particular, has been described as a "loser" (by Bloomberg) in the AI supercycle because it lacks major listed AI-chip champions comparable to those in Taiwan, South Korea, or the United States. Such narr...