AI adoption is rising rapidly across the world. By 2025, nearly 88% of global organisations were using AI in at least one business function. However, while usage is widespread, control over AI’s core building blocks—compute, models, data, and standards—remains concentrated in a handful of firms and countries.
Training large foundational models requires enormous capital, advanced chips, massive energy, and water resources. Export restrictions on high-end processors and rising geopolitical tensions make access even more uncertain. For India, attempting to replicate this model would mean diverting scarce public resources into a race it is structurally disadvantaged to win.
Credits: EBNW Story
The report is blunt: scale for scale’s sake is a trap.
The Real Risk: Jobs, Productivity, and a Quiet Shift
One of the biggest anxieties around AI is job loss—and early evidence is more nuanced than the headlines suggest. Studies from the US and Europe show no immediate collapse in employment, even in AI-exposed sectors. Instead, what is emerging is a subtler shift: each unit of economic growth is now generating fewer jobs than before.
In simple terms, AI is not yet destroying jobs—but it is quietly changing how labour and output interact. For a labour-abundant economy like India, this is a warning signal. Uncalibrated AI adoption could boost productivity while weakening employment absorption, especially in low-value service jobs.
That’s why the policy challenge is not whether to adopt AI, but how fast and in what form.
Why India Needs Its Own AI Path
The report strongly argues that India must not become merely a consumer of foreign AI systems. Dependence on proprietary, opaque models carries economic, strategic, and even cultural risks. As AI spreads into governance, healthcare, defence, and education, technological dependence becomes a national vulnerability.
At the same time, total self-sufficiency is unrealistic. The answer lies in balance: staying open to global innovation while building domestic capability where it matters most.
This is where India’s strengths come in—human capital, data diversity, and institutional coordination. India already ranks among the top global contributors to AI research and has one of the most AI-literate workforces in the world. What it lacks in capital and compute, it can compensate for with scale of problems, ingenuity, and frugal innovation.
The Case for Bottom-Up, Frugal AI
Rather than chasing frontier models, the report proposes a bottom-up approach: small, application-specific AI systems tailored to real sectoral needs. These models are cheaper, faster to deploy, and can run on local devices like smartphones or low-cost servers—making them ideal for India’s infrastructure realities.
Across the country, this approach is already taking root. AI tools are being used for early cancer detection in low-resource hospitals, real-time water management in cities, landslide alerts in Himalayan regions, and improved learning outcomes in classrooms. Language platforms like Bhashini and AI4Bharat are bringing digital services to millions in their native languages, breaking barriers created by text-heavy systems.
This is AI designed for inclusion, not just efficiency.
Governance That Enables, Not Chokes, Innovation
The report also makes a strong case for regulatory sequencing. India should enable experimentation first, scale next, and regulate where risks are highest. Heavy, upfront regulation could stifle startups and local innovation, while no regulation could erode trust. The middle path is smart, phased governance—especially around data, where India must ensure that the value created from domestic data benefits its own people.
Credits: Business Standard
AI as a Strategic Choice
The central message of the report is clear: AI is not just a technology—it is a strategic choice. India’s advantage does not lie in building the biggest models or the largest data centres. It lies in building the most relevant ones.
By focusing on bottom-up innovation, open systems, and frugal deployment, India can turn AI into a source of dignified employment, resilient growth, and technological sovereignty—without falling into the costly traps of the global AI arms race.
