Anthropic’s sudden move to suspend access to its latest AI models at the direction of the US government has raised new questions across the global technology industry. In India, the decision reignites a long-standing debate over whether the country, one of the world’s largest AI markets, can afford to rely on technology built and managed in other countries.
The announcement was made late Friday, when Anthropic said it had received a directive from the U.S. government to suspend access to its recently launched Fable 5 and Mythos 5 models for all foreign nationals, including its own foreign employees. The move comes on the heels of the company announcing a partnership with Indian IT services giant Tata Consultancy Services to expand enterprise AI adoption in India, highlighting how the country’s AI ambitions are closely tied to technology developed and managed in the United States.
The broader impact remains unclear, but some reports say Amazon CEO Andy Jassy first brought the security concerns to the government’s attention. And The Information said the White House is unlikely to extend similar restrictions to other AI companies and has privately criticized Anthropic’s response to the alleged jailbreak vulnerability. Antropic disputed the government’s characterization and argued that the action should not have been taken.
Either way, this development has sparked a debate among Indian founders, investors, and policy experts about whether to accelerate efforts to build domestic AI capacity, deepen investment in open source alternatives, or continue to rely on a small number of US frontier model providers. For some, this episode is a wake-up call against our dependence on technology. For others, it is a reminder that access to increasingly important AI systems can be shaped by geopolitical decisions beyond India’s control.
India has become one of the most important markets for frontier AI companies. Both Anthropic and OpenAI say the South Asian country is their second-largest market after the United States, reflecting its growing importance in the global AI race. The companies have already set up offices in India and have expanded local hiring, partnerships and corporate initiatives in recent months, betting on India’s vast base of developers, startups and enterprises to accelerate adoption of the latest technology.
For many in India’s technology industry, Anthropic’s Friday announcement was about more than just one AI company. This has once again raised questions about the country’s long-term AI strategy and whether India can afford to continue relying on a small number of foreign frontier AI providers.
“This completely changes the game,” Aakrit Vaish, founder of Indian AI venture platform Activate, said of Anthropic’s decision. “I think this is a big change in the way we all think about sovereign AI in India.”
Vaish told TechCrunch that he woke up Saturday morning “shocked and confused” by the announcement, which he said strengthened the case for developing domestic AI capabilities. He expects startups to increasingly rely on open source models, and plans to encourage companies in his portfolio to reduce their reliance on a small number of frontier AI providers.
For some founders, a bigger concern was how restrictions on access to frontier AI would impact competitiveness. Atomicwork co-founder and CEO Vijay Rayapati told TechCrunch that the episode highlighted the risks faced by startups whose teams span multiple countries when access to advanced AI systems is increasingly subject to geopolitical restrictions.
Atomicwork has approximately 25 employees in the United States, but much of its product engineering team is based in Bangalore, India.
“If your AI team is not made up entirely of U.S. citizens, you are at a competitive disadvantage,” Rayapati said, arguing that unequal access to frontier AI models could give some companies a significant advantage over their competitors.
The concerns come as some in India’s technology industry are already grappling with how AI will reshape the global talent economy. This week, U.S. real estate technology company Opendoor closed its India office less than two years after entering the country, with CEO Kaz Nejatian citing efforts to move operations closer to U.S. customers and a shift to a smaller, AI-native team.
Although Open Door did not say how much of this decision was driven by AI-related efficiency improvements, the move added to a broader discussion about how advances in AI could impact the future of global technology jobs and what that means for India’s position as an engineering talent hub.
beyond humans
The Anthropic episode sparked a broader discussion about dependence on foreign AI infrastructure among startups and AI builders, as well as among Indian technology leaders.
Sridhar Vembu, founder of Indian SaaS company Zoho, said the move shows that “technology is the ultimate weapon” and urged Indian organizations to adopt smaller, open-source models.
“What can our government do now? Ensure that Indian organizations adopt smaller versions of both Indian and Chinese open source models,” Vembu wrote in X.
Speaking to Vembu on X, investor and former Infosys executive Mohandas Pai argued that the development highlights the need for a more ambitious national AI strategy and called on the government to significantly increase investment in AI, computing infrastructure and deep technology.
“We are far behind and we need a national mission to start urgently,” Pai wrote, calling on the government to create a 500 billion rupee (about $5 billion) annual fund for AI and deep technology, alongside a 2 trillion rupee (about $21 billion) credit guarantee program to support cloud infrastructure, hardware and semiconductor development.
Pai’s proposal would dwarf India’s existing AI efforts. In 2024, New Delhi approved the IndiaAI Mission to spend Rs 103.72 billion (approximately $1.2 billion) over five years to expand computing infrastructure, support startups, and develop indigenous AI capabilities.
Despite growing interest in AI and New Delhi’s push to develop domestic capabilities, India remains a relatively small player in frontier model development. Only a handful of startups are pursuing basic AI models, including Sarvam, which released an open source model earlier this year. But Krutrim, another high-profile AI startup, initially focused on basic model development before pivoting to cloud and AI infrastructure services.
Much of India’s AI ecosystem is instead focused on applications and specialized models built on top of existing foundational models. A recent example is Avatar AI, which launched a video generation model earlier this week with the aim of providing a lower-cost alternative to products from competitors such as Google’s Veo, Kling, Luma, and Runway.
Not everyone agrees that the main challenge is lack of capital. In response to Pai’s comments, Lightspeed partner Hemant Mohapatra argued that the biggest constraint to building a globally competitive AI company is not just the size of the investment commitment, but talent, access to computing resources, and execution.
Mohapatra estimated that training a frontier AI model can cost anywhere from hundreds of millions of dollars to billions of dollars, depending on the approach, but said successful AI companies have historically scaled up their capital requirements over time as adoption increases.
But for some policy observers, the impact extends far beyond AI startups and model providers.
Prasant Roy, a New Delhi-based technology policy expert who advises multinational companies, said the episode is likely to heighten concerns within the Indian government over strategic autonomy, comparing it to the lessons many countries learned from Russia’s loss of access to SWIFT and other parts of the global financial system after its invasion of Ukraine.
He told TechCrunch that the move would likely spark a significant nationalist backlash in India, saying it was a poorly thought-out decision by Washington and that its implications go far beyond Anthropic itself.
“Even if this is modified or reversed, the human episode shows that there is no such thing as a geopolitically neutral foreign LLM,” Roy said. “The American AI model is bound by American geopolitics.”
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