From IT Superpower to AI Spectator: How India Missed the Moment

India, once recognised globally as an IT superpower driven by its vast pool of engineers, outsourcing hubs, and software service giants, now faces the risk of becoming a secondary player in the artificial intelligence (AI) revolution. While Indian engineers contributed significantly to building the world’s digital infrastructure, leadership in AI is increasingly dominated by the United States and China.

Artificial intelligence is emerging as the foundational infrastructure of the future global economy, reshaping sectors such as defence, healthcare, finance, manufacturing, education, and energy. Despite its historic strength in IT services, India has not produced a globally significant foundational AI model. The country’s position reflects measurable structural gaps in computing infrastructure, patents, research investment, and industrial scale.

The shift has become evident over the past decade, particularly between 2014 and 2024, as global investments in AI surged and the technological race intensified. The disparity is visible in compute capacity, patent filings, and research output, marking a decisive moment in the global technological hierarchy.

The global AI leadership contest is centred in the United States and China, where massive investments in compute infrastructure, semiconductor ecosystems, and research institutions have created powerful innovation ecosystems. India, despite its global IT footprint anchored in cities such as Bengaluru, Hyderabad, and Pune, remains structurally underpowered in core AI infrastructure.

The primary reasons behind India’s lag are systemic and measurable:

Modern AI development requires enormous computing power. Industry estimates place U.S. AI compute capacity at approximately 5,200 petaflops and China’s at over 3,500 petaflops. India’s capacity stands near 148 petaflops, making it more than 20 times smaller than China and 35 times smaller than the United States. Without sufficient compute, India cannot train competitive frontier models or sustain large-scale experimentation.

Between 2014 and 2023, India produced roughly 1,350 generative AI patents. In contrast, China produced over 38,000 and the United States around 6,200. Globally, India accounts for just 0.37% of AI patents, compared to China’s 70% and the United States’ 14%. This gap highlights India’s continued role as an implementer rather than an owner of intellectual property.

India spends approximately 0.7% of its GDP on research and development. China spends between 2.4% and 2.7%, while the United States invests between 3.4% and 3.5%. Additionally, private sector participation in India’s R&D ecosystem remains limited at about 36%, compared to 70–75% in advanced economies. This results in fewer world-class laboratories, weaker industry-academic collaboration, and limited frontier innovation.

India produces fewer than 500 AI-related PhDs annually, and many of its top researchers migrate abroad due to better funding, infrastructure, and institutional support. While India exports talent, other nations convert that talent into technological leadership.

AI leadership depends on semiconductor and GPU manufacturing. The United States and China have established strong domestic semiconductor ecosystems, while India remains dependent on foreign supply chains for advanced chips, limiting technological sovereignty.

India’s IT success was built on services and outsourcing. However, the AI era rewards nations and firms that build foundational products and platforms. While Indian startups are active, they remain smaller in scale and global influence compared to their American and Chinese counterparts, which dominate foundational AI model development.

India’s current position is the result of long-term structural choices prioritising services over product innovation, limited investment in research infrastructure, insufficient compute capacity, and dependence on external hardware ecosystems. These factors collectively prevent India from establishing leadership in foundational AI technologies.

However, India retains structural advantages, including a vast domestic digital market, strong engineering talent, and rapid technology adoption. Artificial intelligence has the potential to contribute hundreds of billions of dollars to India’s GDP by 2035 through productivity gains.

To avoid technological dependence, India must significantly increase R&D spending toward 2% of GDP, invest in national compute infrastructure, expand doctoral-level research, strengthen semiconductor capabilities, and transition from services to deep-tech product development.

India’s rise in the previous technological era was defined by its role as the world’s back office. The emerging AI era will be defined by those who build foundational intelligence systems.

The strategic choice before India is clear: remain a consumer of artificial intelligence—or become its creator.