Whalesbook
India's AI Strategy: Apps First, Infrastructure Next
India is carving out a unique path in artificial intelligence by focusing on becoming a major production hub for AI applications rather than competing on foundational model development. This strategy plays to the country's strengths: immense scale and a highly digital population.
A Booming App Market
With over 1.4 billion people and more than 900 million internet users, India offers a massive market for AI applications. Its real-time digital payment system, UPI, processes a huge volume of transactions daily, generating valuable data for AI. Consumer adoption is high, with 62% using AI for shopping and 64% for product research. Critically, trust in AI is very strong, with nearly 90% of Indians approving AI and over 79% accepting AI-driven decisions, often seeing them as more objective. This high trust accelerates AI adoption, making India the second-largest market for ChatGPT with over 100 million weekly users.
Investment Focus on Applications
India's AI sector uses capital efficiently with an application-first approach. About 80% of AI funding targets application-layer companies, unlike regions focusing on expensive foundational models or infrastructure. This strategy has led to faster revenue generation, with nearly 60% of startups earning money early on. Global AI firms are investing to capture data from India's diverse user base and multilingual needs. AI deal volume and funding show this trend: 2025 saw 164 AI deals, up significantly from previous years, with total funding reaching $2.5 billion, up from $0.9 billion in 2024. Average deal sizes have also grown, reflecting increased investor confidence in India's AI app potential.
The Infrastructure Shortage
Despite strong growth in apps and startups, India faces a major shortage in core AI infrastructure, especially data storage. While the country generates about 20% of the world's data, its storage capacity is less than 3% of the global total. This imbalance is a significant hurdle for long-term AI development and global competitiveness. To fix this, over $200 billion in infrastructure commitments have been announced, signaling a major effort to build essential compute and storage capabilities. This marks a key shift towards developing domestic AI infrastructure beyond just deploying applications.
Global Context and Future Challenges
India's application-first strategy differs from the model-centric approaches of the United States and China, which invest heavily in foundational research and hardware. While India uses its size and cost-effectiveness for apps, the growing global demand for AI computing power highlights the need for India to strengthen its infrastructure. Analysts agree that significant infrastructure investment is an important step. However, staying relevant globally will require building robust backend capabilities.
The AI funding landscape shows growth, with total funding rising sharply to $2.5 billion in 2025 from $0.9 billion the previous year. Still, the ecosystem is dominated by early-stage funding rounds, with 71% of deals at this level, indicating a growing but still developing market.
Key Risks for India's AI Ambitions
While India's role as an AI application factory is strong, there are inherent risks. Relying heavily on app development without matching infrastructure investment is like using existing digital systems instead of building new ones. Unlike the US and China, which have advanced chip industries and large cloud networks, India starts its compute and data storage build-out from a much lower base. This dependence on foreign technology for core infrastructure could lead to supply chain issues and higher costs. Furthermore, the huge scale of the infrastructure challenge, with over $200 billion in commitments, means it is hard to execute. Spending this money well needs good project management, clear rules, and ongoing support from government and business. Delays or inefficiencies in filling this infrastructure gap could limit India's AI future, potentially leaving it as a high-volume user rather than a self-sufficient innovator.
India's AI future depends on advancing its application strength alongside the foundational infrastructure needed for sustained growth. The $200 billion infrastructure push shows ambition, but the market will watch how effectively these resources are used amid growing global demand for AI computing power.