For India, "leapfrogging" with AI means overcoming systemic resource shortages. AI acts as a horizontal productivity multiplier, enabling, for example, a limited number of doctors to deliver better healthcare outcomes through AI-powered diagnostics, thus enhancing sectoral capacity without massive infrastructure investment.
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Indians are more optimistic about AI than Westerners because AI is seen less as a threat to the workforce (which has proportionally fewer white-collar jobs) and more as a crucial national opportunity. AI is viewed as a "leapfrog" technology to accelerate development and close the economic gap.
Contrary to expectations, analysis shows that sectors with low profit per employee, such as healthcare and consumer staples, stand to gain the most from AI. High-tech firms already have very high profit per employee, so the relative impact of AI-driven efficiency is smaller.
Don't view AI through a cost-cutting lens. If AI makes a single software developer 10x more productive—generating $5M in value instead of $500k—the rational business decision is to hire more developers to scale that value creation, not fewer.
Instead of competing to build sovereign AI stacks from the chip up, India's strategic edge is in applying commoditized AI models to its unique, population-scale problems. This leverages the country's deep experience with real-world, large-scale implementation.
The most significant opportunity for AI in healthcare lies not in optimizing existing software, but in automating 'net new' areas that once required human judgment. Functions like patient engagement, scheduling, and symptom triage are seeing explosive growth as AI steps into roles previously held only by staff.
Indian startups are carving a competitive niche by focusing on the AI application layer. Instead of building foundational models, their strength lies in developing and deploying practical AI solutions that solve real-world problems, which is where they can effectively compete on a global scale.
Contrary to the global trend where consumer applications dominate AI usage (70%), India's adoption is heavily skewed towards productive enterprise use (60%). This business-first approach is driven by a large STEM workforce leveraging AI for efficiency gains in sectors like finance and healthcare.
The narrative of AI destroying jobs misses a key point: AI allows companies to 'hire software for a dollar' for tasks that were never economical to assign to humans. This will unlock new services and expand the economy, creating demand in areas that previously didn't exist.
Unlike prior technological inputs like energy, which required machinery to be useful, AI compute can be added directly to the economy to strengthen it. Simply increasing compute improves product quality and expands user access simultaneously, acting as a direct economic force multiplier without traditional bottlenecks.
Just as electricity's impact was muted until factory floors were redesigned, AI's productivity gains will be modest if we only use it to replace old tools (e.g., as a better Google). Significant economic impact will only occur when companies fundamentally restructure their operations and workflows to leverage AI's unique capabilities.
