Washington’s new bet on AI and what it means for India

Last week, the United States gently crossed a line that will define again how power is built in the modern world. Through a new initiative called the Genesis Mission, the US Department of Energy announced 26 science and technology challenges that place artificial intelligence at the core of  scientific discovery itself.

This is not about using AI to speed up research. It is 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. That is why  I’m writing on this for an Indian Newspaper, but yes it needs to be written, because it’s not only valuable for the US, But for India too.

What Washington announced last week was not another AI policy. It was a declaration that the speed of scientific discovery has itself become a strategic asset. New Delhi should read it as a warning.

For years, India has spoken of becoming a knowledge superpower — enshrined most clearly in the National Education Policy (NEP) 2020. The country produces more than 1.6 million STEM graduates every year, ranks among the world’s top three in research output, and has launched ambitious missions in quantum technologies, semiconductors, space, and green energy.

We’re even hosting the world’s first major AI summit in the Global South in 2026. Yet beneath this confidence lies a harder truth: when it comes to the infrastructure that determines how discovery actually happens — how quickly ideas are tested, validated, and scaled — India remains anchored to a 20th-century institutional model, in a world that is rapidly moving beyond it.

The 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.Under Genesis, AI systems will design experiments, optimise energy grids, digitise nuclear data, accelerate the growth of materials discovery, and reduce years of trial-and-error into weeks. The explicit goal is to make parts of scientific discovery 20 to 100 times faster.

This changes everything. 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 — they will become dependent.India’s scientific apparatus is not designed for speed. Our 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 per cent of GDP. China spends roughly 2.4 per cent, the US about 3.4 per cent. 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’s AI conversation remains oddly misplaced. We speak of AI in governance, in startups, in ethics, in skilling, in policy & in summit. Rarely do we 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.

We’ve nothing comparable. We have high-performance computing facilities, yes — but access is limited, fragmented, and often bureaucratic. Of Course We’ve world-class labs — but many still lack interoperable data pipelines. We’ve ambitious missions—but no unified computational backbone linking them.

The result is predictable: duplication, delay, and diminished impact. There is a big question India has not begun to confront: who owns AI-generated science? 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 laboratories to models, computing, and data governance.

The US understands this. That is why Genesis sits inside the Department of Energy, not at the university consortium. Energy, defence, discovery, and AI are treated as a single strategic continuum.

Though we collaborate extensively with global research networks. That openness is a strength. But collaboration without indigenous AI-science capacity risks a new asymmetry: India supplies talent and data, while others control the discovery engines.

Autonomous labs and an uncomfortable reality

One of the most disruptive elements of the Genesis Mission is the push toward autonomous laboratories —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.

Now ask an uncomfortable question: How many Indian labs are even digitally ready for this?

Across universities and public research institutions, 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 its scientific institutions are machine-legible at all.

That gap will provoke resistance. It should. Disruption always does. The Energy Constraint No One Wants to Discuss. 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 an estimated 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 cannot 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. What India Should Be Arguing About—Now. India does not need to replicate the US Genesis Mission. Our priorities differ. Our constraints are real. But ignoring the shift it represents would be strategic negligence.

At minimum, India needs a national debate on three hard questions:First, should India build an AI-science platform connecting IISc, IITs, national labs, strategic agencies, and industry into a shared computational and data backbone? Second, how does India ensure scientific sovereignty in an era where discovery emerges from AI systems trained on national data?

Third, is our funding, institutional design, and education system prepared for machine-accelerated science, or are we optimised for a slower past?

These are not academic issues. They determine industrial competitiveness, energy security, defence capability, and long-term economic power. The US has decided that the future of science will be faster—and that speed itself will be weaponized. India can choose to respond. Or it can continue organising committees while discovery still accelerates elsewhere. History is rarely kind to nations that mistake deliberation for strategy.

Nishant Sahdev is a theoretical physicist at the University of North Carolina at Chapel Hill, US, and the author of the forthcoming book The Last Equation Before Silence.; views are personal