Bernstein Warns: India Must Build Indigenous AI or Risk Geopolitical Lockout from Global Tech Race

Bernstein Warns: India Must Build Indigenous AI or Risk Geopolitical Lockout from Global Tech Race​

The race for foundational Artificial Intelligence (AI) is rapidly transforming from a commercial venture into a geopolitical battleground, according to a report by Bernstein. The brokerage firm warns that if India continues to rely on foreign-developed LLMs while focusing primarily on application layer development, the nation risks ceding control over critical future technology.

Bernstein argues that recent restrictions imposed by the United States on access to advanced frontier AI models mark a definitive turning point in global AI strategy. Cutting-edge large language models (LLMs) are increasingly being viewed not merely as software products but as strategic national assets.

AI Sovereignty: Why Foundational Models Are Strategic Assets​

The report likens foundational AI models to military hardware, stating that "AI is the next fighter jet." As global powers increase control over advanced technologies like semiconductors, GPUs, and frontier AI, governments are proactively restricting access.

Bernstein highlights instances such as restrictions on Anthropic's frontier models for non-US citizens, illustrating that access to advanced AI cannot be guaranteed. This trend mirrors successive US export controls on specialized semiconductor equipment and AI capabilities.

If these geo-political controls expand further, India could face a scenario where it is forced to operate using AI systems that are one or two generations behind those available in the US and China. Such dependence could place Indian technology companies at a significant structural disadvantage globally.

The Missing 'DeepSeek' Moment for Indian Tech Ecosystem​

According to Bernstein, India has yet to achieve its own "DeepSeek moment" because its existing technology ecosystem is heavily geared towards IT services rather than generating massive proprietary datasets required to train cutting-edge AI models.

The brokerage noted that the prevalent focus on developing applications atop foreign LLMs leaves companies exposed to geopolitical risks. This service-led model, Bernstein suggests, has historically rewarded businesses customizing global software rather than incentivizing domestic foundational capability building.

AI is now following a trajectory similar to nuclear energy and defence systems, where access is increasingly dictated by geopolitics over free market mechanisms.

Rethinking India's AI Policy: From Application Layer to Indigenous Control​

Bernstein advises that relying solely on overseas AI models presents an unsustainable path for national competitiveness. The country must simultaneously build foundational AI capabilities while developing specialized domain-specific LLMs using its proprietary data in critical sectors like healthcare, defence, and industry.

The brokerage questioned the sufficiency of India's current multi-pronged AI strategy. While the IndiaAI Mission covers computing infrastructure, applications, research, hardware, and foundational models, spreading limited resources across too many priorities risks hindering meaningful leadership development.

Bernstein concludes that developing an indigenous foundational AI model is no longer an optional luxury but a strategic necessity. To maintain control over next-generation technology and remain globally competitive, India must move decisively toward technological autonomy.