Why China's AI model export rethink may force India to revisit AI strategy

China is considering limiting overseas access to its frontier AI models after a similar US move, signalling that advanced AI is increasingly being treated as a strategic national asset

China is reportedly considering limiting overseas access to its own frontier artificial intelligence (AI) models, weeks after the US temporarily restricted access to Anthropic's most advanced AI models. The shift indicates that governments are beginning to view AI models not merely as commercial software, but as strategic assets whose access can be controlled.

 

If the trajectory continues, the implications extend far beyond Washington and Beijing. Countries such as India, which currently rely on a mix of US and Chinese AI models while building their own capabilities, may eventually have to rethink what technological dependence means in the AI era.

 

Why the shift matters for India

For India, the immediate concern is not whether the US or China is justified in restricting access to frontier AI models. It is whether such access can still be taken for granted.

 

Over the past two years, Indian startups and enterprises have built products using models from both ecosystems — OpenAI, Anthropic, Google and Meta alongside China's Qwen and DeepSeek — selecting whichever offered the best balance of capability, cost and performance.

 

That flexibility could become harder to preserve if governments increasingly decide who can access their most advanced AI systems on national security grounds.

Thomas J Vallianeth, partner at Trilegal, told Business Standard: "The lesson of the past month is that model access is now a supply-chain risk. Boards will begin to treat AI dependency accordingly and diversify the regions from where foundational models are procured."

 

His comments reflect a broader shift in how businesses may need to approach AI. Until now, discussions largely focused on capability, pricing and performance. Increasingly, resilience and control are becoming equally important.

 

The challenge is therefore no longer simply adopting AI. It is ensuring reliable access to it.

 

Ashish Tandon, founder and chief executive officer of Indusface, made a similar point in an earlier interaction with Business Standard, arguing that recent developments have fundamentally changed the conversation around sovereign AI.

 

"Sovereign capability has been an India ambition for the long term; this reframes it as near-term resilience policy," he said, adding that the objective is to ensure critical sectors are "never run on borrowed technology with no indigenous fallback".

 

Vallianeth also argued that businesses may have to rethink how AI systems are built.

 

"A frontier model was switched off overnight by a foreign government — with no warning and no transition time," he said. India, he added, may need to diversify sources of foundation models, invest more seriously in Small Language Models (SLMs) and self-hosted open-weight deployments, and negotiate contracts that account for geopolitical disruption rather than assuming uninterrupted access.

Sovereign AI gains urgency

These developments also strengthen the case for India's sovereign AI ambitions.  Mozammil Ahmad, advocate at the Delhi High Court and former strategy lead at White & Brief Law Offices, believes India's relative neutrality could become a strategic advantage if AI ecosystems continue to fragment.

 

"The next AI moat isn't intelligence, it's jurisdiction and that may be India's opening. As Washington and Beijing increasingly ring-fence their most advanced AI capabilities, the market may begin to value trusted access as much as frontier performance," he told Business Standard.

 

According to Ahmad, although India still trails global leaders in frontier model development, it has an opportunity to position itself as a preferred jurisdiction for building and deploying AI through credible regulation, sovereign compute and an open innovation ecosystem.

 

"The next phase of AI competition may not be won solely by those with the smartest models, but by those being most reliable to let others use them," he said.

China may be following a path opened by the US

According to a Reuters report citing three people familiar with the discussions, Chinese authorities have spent the past month consulting Alibaba, ByteDance and startup Z.ai on whether overseas access to China's most advanced AI models should be restricted. The discussions reportedly cover future frontier models that have not yet been released, although no decision has been taken and there is no fixed timeline for any restrictions.

 

If Beijing proceeds, it would reverse a strategy that has helped Chinese AI companies rapidly expand their global footprint. Alibaba's Qwen, ByteDance's Doubao and Z.ai's GLM series have become popular among developers worldwide by making weights of their capable models widely available. As TIME noted, that openness has been one of China's biggest competitive advantages, helping its AI ecosystem narrow the gap with leading US models despite still trailing them on many frontier benchmarks.

 

Restricting access would therefore signal that strategic considerations are beginning to outweigh the benefits of global adoption. China, however, would not be the first country to move in that direction.

How the US set the precedent for AI model controls

In June, the US Commerce Department's Bureau of Industry and Security ordered Anthropic to suspend access to its two most advanced models — Claude Fable 5 and Claude Mythos 5 — for certain foreign nationals after officials raised concerns about a possible technique that could bypass the models' cybersecurity safeguards.

 

The restrictions were later lifted after Anthropic addressed the government's concerns, restoring global access on July 1. Although short-lived, the episode established an important precedent.

 

As legal publication Lawfare observed, it marked the first known instance of the US applying export controls to an AI model itself rather than to the semiconductors or computing infrastructure used to build it.

 

Until recently, governments sought to influence AI development by controlling the inputs required to create it — advanced chips, chipmaking equipment and high-end compute. The Anthropic episode suggested something different: Governments were now willing to control the finished capability itself.

 

If Beijing eventually imposes similar restrictions, the world's two largest AI powers would both have demonstrated a willingness to treat frontier models as strategic exports.

Why AI models are becoming strategic assets

The progression of US restrictions over recent years shows how governments' thinking around AI has evolved. Semiconductors were the first choke point because only a handful of companies manufacture the advanced chips needed to train frontier AI systems. Compute came next because access to powerful cloud infrastructure can be monitored, measured and, if necessary, switched off. Frontier AI models now represent the next layer.

 

The Anthropic episode demonstrated that governments are willing to intervene not only in how frontier AI is built but also in who gets access to the finished model. That reflects growing recognition that frontier AI systems are dual-use technologies capable of generating enormous commercial value while also creating national security risks if misused.

 

AI companies increasingly acknowledge these risks. Anthropic, OpenAI and Google DeepMind have each published frontier safety frameworks covering advanced cyber capabilities and, in the case of Anthropic and OpenAI, certain biological and chemical risks as models become more capable.

 

Beyond security, frontier models are also emerging as sources of economic, scientific and technological advantage. AI companies argue that advanced systems can accelerate software engineering, scientific discovery, healthcare, materials science and drug research by helping researchers analyse information, generate hypotheses and automate parts of the research process.

 

The question is therefore no longer only who can build the best AI model. Increasingly, it is who gets to use it.