Kris Gopalakrishnan: The age of AI needs a new growth model—green innovation and entrepreneurship

Training and running large AI models demands significant energy, compute infrastructure and water for cooling. Scaling AI without rethinking efficiency and energy sources risks building tomorrow’s digital economy on yesterday’s carbon curve. The opportunity—and responsibility—of this moment is clear: the next phase of economic growth must be powered by green innovation and AI must become part of the climate solution, not an accelerant of the problem.

That is why ‘green innovation and entrepreneurship’ is vital. The most competitive economies will be those that combine four must-dos: build and deploy AI; reduce the energy and resource intensity of digital systems; use AI to decarbonize the economy, including agriculture, industry, mobility and power; and build EcoAI literacy at scale.

AI’s energy challenge can become an innovation engine: The energy intensity of AI is not just a constraint; it can be a catalyst for innovation. It pushes entrepreneurs towards ‘efficient-by-design’ systems: smaller models where possible, smarter inference, better chips, better cooling, better scheduling of workloads and deeper integration with renewables. For instance, the Indian Institute of Science’s work on GaN 2D materials such as graphene and memristors is enabling low-power chips and memory that can run AI far more efficiently.

Similarly, brain research at IIT Madras is enabling neuromorphic chips that deliver intelligence with a much smaller energy footprint. It pushes us towards new business models where performance is measured not only by accuracy, but by ‘outcomes per watt per rupee.’

More importantly, AI can help us solve the very problem it creates. AI can improve grid forecasting and balancing, reduce industrial wastage, optimize logistics, accelerate materials discovery and make agriculture more climate-resilient.

Consider IIT Ropar’s iHub, AWaDH, its agriculture and water development hub supported by the National Mission on Interdisciplinary Cyber-Physical Systems. Insofar as research is concerned, AWaDH has built solutions such as a ‘Digital Entomologist’ (with global research institutes), which is a solar-powered AI biodiversity sensor that uses motion-sensing cameras to detect and count insect species. The data it generates feeds into a Biodiversity Index of Farms, which helps measure on-farm biodiversity over time.

The opportunities are equally compelling. A recent report by The Council on Energy, Environment and Water (CEEW) estimated that by 2047, India’s ‘green economy’—which includes our energy transition, circular economy and bio-economy—could generate $1.1 trillion in market value and 48 million jobs.

Support sustainability startups and inclusive green entrepreneurship: Strong innovation ecosystems are crucial for green entrepreneurship to grow. Today, incubators are increasingly backing early-stage sustainability and climate-tech startups that build infrastructure to make clean energy adoption and resource-efficiency easier to deploy at scale.

At the same time, green innovation is not only about high-tech labs and large balance sheets. Some of the most powerful climate solutions emerge when sustainability is tied to livelihoods and inclusion.

Industree Foundation, for example, helps rural women build stable livelihoods by creating women-owned collectives. It also leverages digital platforms to expand markets for climate-positive products by linking these producer collectives to global buyers, so sustainable products can scale beyond local markets.

Similarly, the Office of the Principal Scientific Adviser to the Government of India has developed a Village Readiness Level framework, building on the traditional technology readiness level (TRL) metric, to evaluate innovations suited for deployment in rural India.

EcoAI literacy: Finally, none of this scales without education. There is increasing emphasis on AI literacy today, but that alone is insufficient. What we need is EcoAI literacy. It would allow students to see how AI changes the choices people face, read AI outputs with a questioning mind (not blindly accept recommendations) and understand real trade-offs across nature, society, technology and the economy.

It also means they can take part in shared decision-making, such as community stewardship of water, energy or public services, and reflect on the ethical and ecological consequences of what a group decides to do.

Schools and colleges can weave this into the curriculum across subjects: use real local cases in projects (water use, waste, air quality, energy bills), teach students to critique AI tools and dashboards in assignments, run simulations and debates on policy trade-offs, and assess students on reasoning, impact and responsible action—not just tool usage.

If India gets this right by mobilizing entrepreneurs, investors, researchers and educators, we can drive the next phase of growth in a way that is globally competitive and climate-positive. The age of AI can also be the age of green innovation.

N. Dayasindhu and Krishnan Narayanan, co-founders of Itihaasa Research and Digital, contributed to this article.

The authors are, respectively, co-founder, Infosys, and co-founder, itihaasa Research and Digital.