Chapel Hill, North Carolina: Last week, the US Department of Energy announced 26 ‘science and technology challenges of national importance’ to advance the Genesis Mission, an initiative launched last November by the US to accelerate scientific research through AI. More than this being about using AI to speed up research, it’s about letting machines build how science is imagined, tested and advanced, reducing years of discovery into weeks. When the pace of science changes, the balance of global power changes with it.
What Washington announced last week was not another AI policy. It was a declaration that speed of scientific discovery has itself become a strategic asset. New Delhi should heed this. As it hosts AI Impact Summit 2026, it needs to confront a harder truth: when it comes to infrastructure that determines how discovery actually happens – how quickly ideas are tested, validated and scaled – India remains anchored to a 20th c. institutional model.
Genesis Mission’s most radical idea is also its simplest: science is a system that can be accelerated, not by individual brilliance alone, but by computation, automation and integration. AI systems will design experiments, optimise energy grids, digitise nuclear data, accelerate growth of materials discovery and reduce years of trial and error into weeks. The explicit goal is to make parts of scientific discovery 20x-100x faster. Historically, nations competed on who discovered more. Now, they will compete on who discovers faster. In such a world, countries that move slowly will not just lag, but will also become dependent.
India’s scientific apparatus is not designed for speed. Its research ecosystem is fragmented across ministries, councils, autonomous institutes, public sector labs and universities. Data standards are inconsistent. Collaboration depends more on personal networks than shared infrastructure. Funding cycles are slow, compliance-heavy and risk-averse.
In 2023-24, India’s total public R&D spending hovered around 0.65-0.7% of GDP. China spends about 2.4%, the US around 3.4%. More tellingly, a fraction of US R&D is concentrated in mission-oriented, high-performance computing. India’s is dispersed thinly across thousands of institutions, many of them digitally underpowered.
India speaks of AI in governance, startups, ethics, skilling, policy. But rarely does it treat AI as core national scientific infrastructure on par with power grids, highways, or space launch facilities.
The US Genesis Mission does exactly that. It integrates supercomputers, national labs, datasets, sensors, experimental facilities and AI models into a single discovery ecosystem. This is not about apps or chatbots. It is about putting intelligence into the physical sciences themselves.
When AI systems trained on decades of national data begin proposing new materials, reactor designs, or quantum algorithms, sovereignty changes its room. It moves from labs to models, computing and data governance. That’s why Genesis sits inside Department of Energy, not at the university consortium. Energy, defence, discovery and AI are treated as a single strategic continuum.
India collaborates extensively with global research networks. This openness is a strength. But collaboration without indigenous AI-science capacity risks a new asymmetry: India supplying talent and data while others control the discovery engines. One of the most disruptive elements of Genesis is the push toward autonomous labs – systems where experiments are run, adjusted and iterated by machines with minimal human intervention. This requires robotics, high-quality sensors, real-time data pipelines, reproducibility standards and massive computing power.
Across universities and public research institutions in India, data is still stored in incompatible formats, experimental protocols vary widely, and digitisation remains patchy. Many labs struggle with basic instrumentation uptime, let alone autonomy. Before debating whether autonomous labs threaten jobs or creativity, we must confront whether India’s scientific institutions are machine-legible.
There is a further irony in India’s AI ambitions. AI acceleration consumes enormous energy. Large-scale AI models, supercomputers and autonomous labs demand reliable, high-capacity power. The US anchors its AI-science strategy explicitly in energy planning because it understands this coupling. India does not.
India’s peak power demand crossed 250 GW in 2024, with shortages still routine in several states. Data centres already consume 3-4% of national electricity, a figure expected to rise sharply. Yet, AI strategies and energy planning are rarely discussed in the same breath. You can’t build an AI-driven scientific economy on an energy system designed for yesterday.
Genesis also forces a rethink of scientific education. If AI systems increasingly design experiments and analyse data, what does a scientist trained only in traditional methods look like in 2035? India produces vast numbers of science graduates. But curricula often lag frontier practice by a decade or more. Systems thinking, computation-first experimentation and AI-guided modelling remain peripheral in many institutions.
Without reform, India risks training excellent scientists for a world that no longer exists. India does not need to replicate the US Genesis Mission. Its priorities differ. Its constraints are real. But ignoring the shift it represents would be strategic negligence. At the least, India needs a national debate on three hard questions:
Should India build an AI-science platform connecting IISc, IITs, national labs, strategic agencies and industry into a shared computational and data backbone?How does India ensure scientific sovereignty in an era where discovery emerges from AI systems trained on national data? Is its funding, institutional design and education system prepared for machine-accelerated science?The US has decided that the future of science will be faster, and that speed itself will be weaponised. India can choose to respond. Or it can continue organising committees while discovery still accelerates elsewhere.