AI as infrastructure: India must develop the right tech

These reactions are understandable but short-sighted. AI is not just a product or tool. It is an enabling layer, much like electricity, the internet or aviation, that can permeate and power every aspect of life. 

Electricity offers a useful parallel. In the 19th century, Edison and Tesla fought bitterly over the future of current, with Edison backing direct current (DC) and Tesla championing alternating current (AC).

Edison went so far as to electrocute animals to discredit AC. But common sense and scalability prevailed, and AC became the standard. Today, no one argues about what kind of current powers their device. We simply expect it to work. 

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AI is taking a similar path. For most people, their introduction to AI has been through conversational tools like ChatGPT or voice assistants like Siri. But that's merely the tip of the iceberg. The real power of AI lies in systemic transformation. 

Last year, AI kind of won a Nobel prize in Chemistry! It was awarded to Demis Hassabis and John Jumper from Google DeepMind for protein structure prediction, a puzzle humanity has been attempting to solve for over five decades.

It was made possible through an AI called AlphaFold2. This is the kind of systemic AI transformation that we need, and fortunately, there are inroads being made. 

Take Niramai, a women-led Indian startup that's revolutionizing breast cancer screening with non-invasive, radiation-free AI diagnostics. Or Wysa, a mental health startup using AI to deliver affordable Cognitive Behavioural Therapy to over 6 million users across 60 countries.

Or Tapestry, incubated at Google X, which is making electrical grids more resilient by improving visibility and reducing complexity. 

These are not vanity projects. They're mission-driven innovations designed to solve problems that truly matter. But to scale the impact of AI, we need systemic thinking. 

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Systemic change needs systemic thinking: Some of India's core challenges such as air pollution, water scarcity, fragmented supply chains and rural health gaps are not ‘market opportunities’ in the traditional sense. 

They cannot be solved by building a prettier app or running a slick marketing campaign. These issues demand long-term thinking, policy alignment, patient capital and public-private partnerships.

AI can bring transformative changes, and fortunately, help is at hand. First, let’s look at the state-sponsored initiatives. The IndiaAI Mission is one such coordinated effort driving foundational capabilities across the ecosystem.

Over 10,000 graphics processing units (GPUs) are being deployed through public-private partnerships, giving startups and researchers access to large-scale computing power.

Indigenous AI models like BharatGen focus on developing context-specific datasets and models in areas like agriculture, healthcare and urban planning. Further, there's exemplary work being done in developing IndiaAI Datasets and skill-building programmes like YuvaAI. 

While the public sector is helping with core infrastructure and favourable policies, global investors, family offices and academia are investing in AI startups. 

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Incubation centres are also supporting hundreds of early-stage deep-tech ventures.

That said, startups in this space don't just need funding or a pathway from campus labs to capital markets. They need frameworks. How do you design AI for scale? How do you ensure safety is built-in and not bolted on later?

How do you unlock value while keeping costs grounded in reality? How does it treat linguistic minorities? Who are left out, who are counted and who are privileged? These aren't coding problems; they're systems design challenges. 

Across the board, large technology companies and innovation hubs are stepping up to help founders in their AI journey. This is where horizontal mentorship from technologists, product leaders and ethicists becomes a force multiplier. 

For me, the top-of-mind recall is Google for Startups, which I've mentored for over a decade. The accelerator has nurtured 17 cohorts, helping 237 startups raise over $4.5 billion and create 8,500 jobs.

Today, the focus is sharper than ever, helping AI-first startups solve real problems through access to tools, mentorship, cloud infrastructure and, most importantly, guided thinking. 

Also Read: India must forge its own AI path amid a foundational tug of war

Go for the right kind of AI growth: India doesn't need an AI ecosystem built purely on monetization and hype. It needs one built on resilience, inclusion and public good. This means investing in those already solving hard problems, often quietly and resourcefully.

It means shifting our narrative from fear to responsibility, from siloed innovation to systemic collaboration. 

We are not just users of AI. We are—and must be—its co-creators. If we get this right, India won't just keep pace in the global AI race. It will set the benchmark for what responsible, equitable and high-impact AI-led growth should look like.

The author is CEO of Agrahyah Technologies and adjunct professor of digital transformation at IIM Trichy.