India is positioning itself as a third force in the global AI race, building indigenous semiconductors, sovereign computing infrastructure, and localized AI models to break free from technological dependence on the United States and China. The move reflects a broader shift among emerging economies that fear being locked into a two-nation AI hegemony, where technological superiority translates into geopolitical control and economic inequality.

What Exactly Is AI Hegemony, and Why Should You Care?

AI hegemony sounds abstract, but it has real consequences for countries and citizens. It refers to the concentration of power over artificial intelligence, semiconductors, computing infrastructure, and the foundational models that power everything from chatbots to medical diagnostics, in the hands of a few wealthy nations and corporations. When one or two countries dominate this technology, they don't just lead in innovation; they shape the economic opportunities, security choices, and even the political autonomy of other societies.

Think of it as a new form of power that operates through algorithms and technological dependence rather than traditional territorial control. A country that controls the chips, the computing power, and the AI models can effectively gatekeep who gets access to cutting-edge technology and on what terms. For developing nations like India, this creates a precarious situation: either depend on foreign technology or risk falling further behind.

How Are the US and China Currently Dominating the AI Race?

The United States maintains a commanding lead in private investment and frontier AI development. According to the Stanford AI Index 2026, private AI investment in the United States reached approximately 285 billion dollars in 2025, with 1,953 newly funded AI companies that year. That's more than ten times the number of newly funded AI companies in the next-ranked country. The US also dominates through major technology corporations like Amazon Web Services, Microsoft Azure, and Google Cloud, which control much of the computing infrastructure used to train and distribute AI models globally.

China, meanwhile, is narrowing the performance gap through a different strategy. Rather than competing head-to-head on frontier models, China is leveraging open-source AI adoption and building alliances with developing nations through its newly created World Artificial Intelligence Cooperation Organization (WAICO). This approach allows China to court the Global South while the US focuses on maintaining its technological edge.

Both nations benefit from control over the semiconductor supply chain. Companies like NVIDIA (USA) dominate advanced AI accelerators, while cutting-edge chip manufacturing relies heavily on foundries like TSMC in Taiwan. Advanced lithography equipment is supplied predominantly by ASML in the Netherlands. This concentration gives technologically powerful states the ability to use export controls and supply restrictions as instruments of geopolitical influence.

What Are the Key Barriers Preventing Other Countries from Competing?

Several structural factors lock developing nations out of meaningful AI competition. Understanding these barriers reveals why India's push for sovereignty is so significant:

• Financial Resources: Developing frontier AI models requires billions of dollars for chips, data centers, electricity, research, and skilled personnel. Only wealthy governments and major technology corporations can sustain investment at this scale, creating an enormous barrier to entry for emerging economies.
• Computing Infrastructure: Frontier AI depends on massive clusters of specialized processors. Global AI computing capacity has increased roughly 30-fold since 2021, illustrating the enormous scale of the ongoing infrastructure race. Countries without affordable access to such computational power cannot train competitive foundation models and must depend on foreign cloud platforms.
• Intellectual Property Concentration: Patents, trade secrets, proprietary datasets, and closed model weights prevent technological diffusion and force less-developed economies to pay licensing fees or accept external dependence. UNCTAD's Technology and Innovation Report 2025 noted that just 100 companies account for approximately 40 percent of global business-funded research and development.
• Vertical Integration by Tech Giants: Leading technology corporations increasingly control multiple stages of the AI ecosystem simultaneously, from chips to cloud infrastructure to foundation models to consumer applications. This vertical integration makes it difficult for independent firms to compete and allows incumbents to favor their own products.

How Is India Building Its Own AI Sovereignty?

India's strategy centers on three pillars: indigenous semiconductors, sovereign compute infrastructure, and localized foundation models. Rather than trying to outspend the US or match China's scale, India is focusing on building technology that serves its own population and economic needs.

The country has launched several initiatives to support this vision. The Semiconductor Mission 2.0 aims to develop domestic chip manufacturing capacity. The IndiaAI Mission focuses on building indigenous AI capabilities, while AI4Bharat works on creating AI models trained on Indian languages and data. Sarvam AI and BharatGen represent private sector efforts to develop Indian-language AI models. These initiatives are supported by government backing and private investment, though the scale remains modest compared to US and Chinese efforts.

The World Bank identifies computing capacity as one of four foundations required to participate meaningfully in the AI economy, alongside connectivity, data, and skills. India's approach recognizes that building these foundations domestically is essential to avoiding permanent technological dependence.

Steps to Understanding India's AI Independence Strategy

• Indigenous Semiconductor Development: India is investing in domestic chip design and manufacturing to reduce reliance on NVIDIA, TSMC, and other foreign suppliers that control access to AI accelerators and computing hardware.
• Sovereign Compute Infrastructure: Building national data centers and computing clusters ensures India can train and deploy AI models without depending on Amazon Web Services, Microsoft Azure, or Google Cloud for critical infrastructure.
• Localized Foundation Models: Creating AI models trained on Indian languages, cultural contexts, and local data ensures that AI systems serve Indian citizens and businesses rather than forcing them to use models optimized for English-speaking Western markets.
• Talent Development: The IndiaAI FutureSkills initiative aims to build a workforce capable of developing and maintaining sovereign AI systems, reducing dependence on foreign expertise and brain drain.
• Ecosystem Support for Deep-Tech Startups: Government backing for Indian AI startups and deep-tech companies helps create a competitive domestic ecosystem rather than relying on foreign corporations to provide AI solutions.

Why Does India's Path Matter Beyond India?

India's push for AI sovereignty signals a broader trend among emerging economies that refuse to accept permanent technological subordination. If India succeeds in building competitive indigenous capabilities, it could demonstrate a viable third path between US and Chinese dominance. This matters because the current trajectory concentrates AI power in ways that reinforce global inequality.

The stakes extend beyond economics. AI hegemony has military, surveillance, and governance dimensions. Countries possessing superior AI systems can gain asymmetric military advantages in cyberwarfare and autonomous weapons. When surveillance systems lack accountability, technological capacity can translate into authoritarian control. And when a handful of corporations and countries set AI governance standards, they effectively shape how other societies produce knowledge, make decisions, and imagine their future.

India's challenge is balancing strategic pragmatism against upstream foreign dependencies. The country cannot isolate itself from global AI development, nor can it afford to ignore the technological advances happening in the US and China. But by building sovereign capabilities in semiconductors, computing infrastructure, and localized models, India can negotiate from a position of greater strength and ensure that AI development serves Indian interests rather than external powers.