Mishik Sharma

Introduction: From Layers to Sphere Much of today’s discourse on artificial intelligence is framed in terms of a technological “stack”—chips at the base, models in the middle, and applications at the top. This layered view, while useful, is increasingly inadequate. Artificial intelligence is no longer confined to digital workflows. It is moving into factories, mines, refineries,  energy grids,  logistics corridors, and transport systems. In doing so, it is not merely advancing within a fixed stack—it is expanding outward into the real economy. This shift calls for a new conceptual framework: an expanding AI application sphere, where technological layers continuously push one another deeper into real-world deployment, enlarging the domain of application. For India, recognising this shift is critical. The Four Layers and Their Convergence At the core of this transformation are four interlinked layers: Chips: the raw compute substrate Compute Infrastructure (Data Centres): scaled...

Design is often understood in narrow terms—form, engineering precision, or product features. In physical industries, it is typically treated as the stage where a product is shaped, optimised, and readied for production. Once built, the product is expected to find its place in the market, and the company’s responsibility largely ends at the point of sale. But in several fast-scaling sectors in India, this understanding is quietly becoming inadequate. The real shift is not in how products look or function. It is in how they are deployed, used, and sustained over time. Design, as a result, is moving beyond the product—towards the system in which the product operates. This is not a theoretical shift. It is already visible in India's green energy linked sectors. What is emerging is a new logic: design is no longer about creating products; it is about delivering real-world outcomes. Signals from the Market: The E-Bus Turn According to a recent report by Marqstats (released on 25 March), ...

India’s startup story is undergoing a quiet but consequential shift. For over a decade, the country’s startup energy has been synonymous with a handful of megapolitan hubs—Bengaluru, Hyderabad, Mumbai, NCR, etc. Today, that geography is changing. According to a recent report by Tracxn Technologies (released on 30 March), more than 68,000 startups are now headquartered outside India’s primary startup hubs, as of December 2025. Startups are increasingly emerging from tier-two cities (especially Jaipur, Indore, Kochi, Surat, Coimbatore, and Lucknow), driven by lower costs, expanding digital infrastructure, and locally rooted demand. Yet, beneath this diffusion lies a structural imbalance: the report says that tier-two cities' startups account for just 8.6% of total funding rounds and only 2.1% of total capital deployed, over the last ten years. This reveals that while entrepreneurship is decentralising, capital, scale, and institutional support remain concentrated. The result is a fra...

Like every year, the placement season of the Indian Institutes of Technology (IITs) and the Indian Institutes of Management (IIMs) is unfolding right now. And like every year, the same metrics are dominating media attention: placement percentages, salary packages, recruiting companies, and what all these mean for the economy.  These institutions have, without doubt, become some of India’s most successful post-Independence creations—efficient engines that identify, train, and distribute talent into the economy. But beneath this success lies a quieter question:  India has built powerful talent pipelines. But has it built enough institutions that develop and sustain strategic capabilities over long horizons? The Quiet Outlier One institution sits somewhat outside this narrative: the Indian Institute of Science (IISc).  Unlike the IITs or IIMs, IISc does not dominate headlines during placement seasons. Its visibility comes instead from research breakthroughs, long-term projec...

India’s e-commerce sector is sending out a subtle but powerful signal. A recent CIEL HR report (released on 26 March) notes that hiring in the sector has grown by roughly 35% over the past two years, with demand for engineering roles—software developers, DevOps professionals, AI/ML specialists—rising sharply. At first glance, this looks like a routine expansion story. It is not. What we are witnessing is a capability reorientation . India’s e-commerce companies are no longer scaling primarily through warehouses, delivery fleets, and geographic reach. They are quietly rebuilding themselves as technology-intensive systems, investing in the infrastructure needed to handle a far more complex operating model. The question is: why now? The Limits of the First Wave For much of the past decade, the dominant playbook was straightforward—expand into new cities, add sellers and dark stores, subsidise deliveries, and chase Gross Merchandise Value (GMV). This model delivered scale, visibility, and ...

For decades, India's law-makers and policy-makers have treated coal primarily as a resource to be mined, transported, and burned. India has done this at scale. It sits on nearly 400 billion tonnes of proven reserves — among the largest in the world — and has built an extensive extraction and distribution system around them. But the question is no longer whether India can extract coal efficiently. It is whether it can transform coal into the foundation of a broader industrial economy. At this moment of acute energy vulnerability, the answer remains: not yet. The ongoing disruption in West Asia, including Qatar’s suspension of natural gas exports, has exposed a structural fault-line in India’s industrial system. India imports about 85% of its crude oil, about 50% of its natural gas, and about 90% of its methanol and fertilisers. These are not merely energy statistics. They are the molecular inputs of industrial production — the feedstocks for chemicals, fertilisers, fuels, and synthe...

The recent buzz in India around NVIDIA’s announcements at the GPU Technology Conference 2026 (16-19 March) has largely focused on downstream effects—data-centres, AI infrastructure, and IT services. What is striking is not what is being discussed, but what is not. There is little serious conversation about building semiconductor capability itself. This gap matters. Because for India, the semiconductor question is not just about access to compute—it is about whether the country can build the engineering, industrial, and institutional capabilities that underpin it. Moving Beyond Prestige and Towards Purpose The global semiconductor race is often framed through extremes—2nm nodes, AI accelerators, technological supremacy. But frontier manufacturing is defined by: extreme capital intensity entrenched supply chains decades of accumulated know-how Competing head-on with companies like TSMC, Samsung Electronics, and Intel is neither immediately feasible nor necessarily optimal. A prestige-dri...

Announcements at NVIDIA's GPU Technology Conference 2026 (March 16–19) made one thing clear: artificial intelligence is no longer content to sit as a digital overlay. The spotlight on edge platforms—most notably the general availability of NVIDIA IGX Thor for industrial physical AI, with its sensor fusion, functional safety, and real-time reliability—alongside Jetson Thor-powered systems from Advantech, AI-RAN integrations by T-Mobile and Nokia, and adoptions by Caterpillar and Hitachi Rail—signals that intelligence is moving directly into factories, machines, and devices. These are not incremental tools; they enable decisions at the point of action, where latency, bandwidth, and privacy make cloud impractical. In my earlier piece, I argued that India must move AI beyond the 'topping'—the surface-level copilots, chatbots, and workflow enhancers that dominate current adoption—and embed it in the 'cake' itself: the structural core of how industries operate, produce, e...

Announcements from global technology leaders at NVIDIA's annual GPU Technology Conference (March 16-19, 2026) point towards a decisive shift in the trajectory of semiconductors and artificial intelligence. Advances in energy-efficient, specialised chips are making it possible to run powerful AI models directly on machines, devices, and industrial systems. At the same time, partnerships between AI companies and industrial software companies are embedding AI across the entire lifecycle of design, engineering, and manufacturing. These developments signal something fundamental: AI is moving beyond its role as a digital productivity layer and entering the core of industrial systems. Yet, much of today's policy thinking continues to treat AI as a "topping"—an add-on to existing digital workflows, governance tools, and enterprise software. This approach delivers incremental gains, but it misses the deeper opportunity. India's real strategic advantage lies in using AI not...