Anthropic’s sudden move towards suspend access to its latest AI models following a directive from the US government has raised new questions in the global technology industry. In India, the move reignited a long-running debate over whether one of the world’s largest AI markets can afford to rely on technologies built and controlled elsewhere.
THE announcement came Friday evening, when Anthropic said it had received the directive from the US government requiring it to suspend access to its recently launched Fable 5 and Mythos 5 models for all foreign nationals, including its own foreign employees. The move came shortly after the company announced a partnership with Indian IT services giant Tata Consultancy Services expanding enterprise AI adoption in India, highlighting how the country’s AI ambitions are now tied to technologies developed and governed in the United States.
Although the broader implications remain unclear, some reports indicate that initial security concerns were first reported to the government by Amazon CEO Andy Jassy. And the information said The White House is unlikely to extend similar restrictions to other AI companies and privately blame Anthropic’s handling of alleged jailbreak vulnerabilities. Anthropic disputed the government’s characterization and argued that this action should not have been taken.
Regardless, the development has sparked a debate among Indian founders, investors, and policy experts over whether the country should accelerate efforts to build domestic AI capabilities, deepen investments in open source alternatives, or continue to rely on a handful of U.S. model providers. For some, this episode is a wake-up call about technological dependence. For others, it is a reminder that access to increasingly critical AI systems can be shaped by geopolitical decisions beyond India’s control.
India has become one of the most important markets for pioneering AI companies. Both Anthropic and OpenAI have described the South Asian nation as their second largest market after the United States, reflecting its growing importance in the global AI race. Companies have already set up their offices in India, expanded local hiring, partnershipsAnd corporate initiatives in recent months, betting on India’s vast base of developers, startups and enterprises to accelerate the adoption of their latest technologies.
For many in the Indian tech sector, Friday’s Anthropic announcement wasn’t just about one AI company. This has reopened questions about the country’s long-term AI strategy and whether India can afford to remain dependent on a small number of foreign AI providers.
“This is a complete game-changer,” said Aakrit Vaish, founder of India’s AI venture capital platform. Enablereferring to Anthropic’s decision. “I think this significantly changes the way we should all think about sovereign AI in India.”
Vaish told TechCrunch he woke up Saturday morning “shocked and confused” by the announcement and said it strengthens the case for developing domestic AI capabilities. He expects startups to increasingly turn to open source models and plans to encourage his portfolio companies to reduce their reliance on a small number of pioneering AI providers.
For some founders, the biggest concern was what consequences restrictions on border access to AI might have on competitiveness. Vijay Rayapati, co-founder and CEO of Atomic worktold TechCrunch that the episode highlights the risks startups whose teams span multiple countries face if access to advanced AI systems becomes increasingly subject to geopolitical restrictions.
Atomicwork has about 25 employees in the United States, although 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 cutting-edge AI models could give some companies a significant advantage over competitors.
The concern comes as parts of India’s tech sector are already grappling with questions about how AI could reshape the global talent economy. This week, American real estate technology company Opendoor close its office in India less than two years after expanding into the country, with CEO Kaz Nejatian citing a desire to bring operational work closer to customers in the United States and a move toward smaller AI-native teams.
Although Opendoor did not specify the extent to which the decision was driven by AI-related efficiencies, the move added to a broader debate about how advances in AI could affect the future of global tech work and what that could mean for India’s position as an engineering talent hub.
Beyond anthropism
Besides startups and AI builders, the Anthropic episode has also sparked a broader debate among Indian tech leaders about dependence on foreign AI infrastructure.
Sridhar Vembu, founder of Indian SaaS company Zoho, said the move showed that “technology is the ultimate weapon” and urged Indian organizations to increasingly adopt smaller, open source models.
“What can our government do now? Ensure that organizations in India adopt smaller models, both Indian and Chinese, open source,” Vembu wrote on X.
Mohandas Pai, investor and former Infosys executive replied to Vembu on
“We are way behind schedule and need a national mission to hit the ground running,” Pai wrote, urging the government to create an annual fund of ₹500 billion (about $5 billion) for AI and deep technology, as well as a ₹2 trillion (about $21 billion) credit guarantee program to support the development of cloud infrastructure, hardware and semiconductors.
Pai’s proposal would dwarf India’s current AI efforts. In 2024, New Delhi approved the IndiaAI Mission with an outlay of ₹103.72 billion (around $1.2 billion) over five years, aimed at expanding compute infrastructure, supporting startups and developing indigenous AI capabilities.
Despite growing interest in AI and New Delhi’s efforts to develop domestic capabilities, India remains a relatively small player in developing pioneering models. Only a handful of startups are pursuing fundamental AI models, including Sarvamwhich published open source models earlier this year. However, another high profile AI startup, Krutrim, pivoted to cloud infrastructure and AI services after initially positioning itself around the development of fundamental models.
Much of the Indian AI ecosystem has instead focused on specialized applications and models built on top of existing core models. Recent examples include Avataar AI, which launched a video generation model earlier this week, aimed to provide a lower-cost alternative to offerings from competitors including Google’s Veo, Kling, Luma and Runway.
Not everyone agrees that the main challenge is a lack of capital. In response to Pai’s comments, Lightspeed partner Hemant Mohapatra argued that the biggest constraints to building globally competitive AI companies are talent, access to computing resources and execution, rather than simply the size of investment commitments.
Mohapatra estimates that training a cutting-edge AI model could cost anywhere from hundreds of millions to several billion dollars, depending on the approach, but said successful AI companies have historically increased their capital requirements over time as adoption has grown.
Yet for some policy observers, the implications extend far beyond AI startups or model providers.
Prasanto Roy, a New Delhi-based technology policy expert who advises multinational companies, said the episode would likely reinforce concerns within the Indian government about strategic autonomy, comparing it to the lesson 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 was likely to provoke a significant nationalist backlash in India and described it as a poorly considered decision by Washington, the consequences of which would extend far beyond Anthropic itself.
“Even if this is corrected or reversed, the anthropogenic episode shows that there is no such thing as a geopolitically neutral foreign LLM,” Roy said. “American AI models are linked to American geopolitics. »
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