Anthropic’s abrupt decision to halt access to its latest AI models, following a directive from the U.S. government, has sparked new discussions across the global tech sector. In India, this move has revived an ongoing debate about whether the country, one of the world’s largest AI markets, should continue to depend on technology developed and managed abroad.
The announcement was made on Friday evening when Anthropic disclosed that it had received instructions from the U.S. government to suspend access to its newly released Fable 5 and Mythos 5 models for all foreign nationals, including its own international employees. This decision followed the company’s announcement of a collaboration with India’s Tata Consultancy Services to promote enterprise AI adoption in India, emphasizing the extent of India’s reliance on U.S.-developed technology.
While the full implications remain uncertain, some reports indicated that Amazon CEO Andy Jassy was among the first to alert the government about initial security concerns. According to The Information, the White House is unlikely to impose similar restrictions on other AI firms and attributes the issue to Anthropic’s handling of alleged vulnerabilities. Anthropic has contested the government’s portrayal and maintains that the measures were unwarranted.
This development has sparked a debate among Indian entrepreneurs, investors, and policy analysts about whether the nation should expedite efforts to establish domestic AI capabilities, invest more in open-source alternatives, or continue depending on a limited number of U.S. frontier model providers. For some, the situation underscores the risks of technological dependence, while others see it as a reminder that access to vital AI systems can be influenced by geopolitical decisions beyond India’s control.
India has emerged as a crucial market for leading AI companies. Both Anthropic and OpenAI have identified the South Asian nation as their second-largest market after the U.S., highlighting its increasing significance in the global AI competition. These companies have recently established offices in India, expanded local hiring, and formed partnerships, leveraging India’s vast pool of developers, startups, and businesses to boost the adoption of their cutting-edge technologies.
For many in India’s tech industry, Anthropic’s announcement was more than just about one AI company; it raised questions about the country’s long-term AI strategy and whether it can afford to remain reliant on a select few foreign frontier AI providers.
“It completely changes things,” said Aakrit Vaish, founder of the Indian AI venture platform Activate, referring to Anthropic’s decision. “I think this materially changes the way all of us should be thinking about sovereign AI in India.”
Vaish expressed to JS his surprise and confusion upon hearing the news on Saturday morning, stating that it reinforced the need to develop homegrown AI capabilities. He anticipates that startups will increasingly lean towards open-source models and plans to advise companies in his portfolio to lessen their reliance on a limited number of frontier AI providers.
For some entrepreneurs, the primary concern was how restrictions on frontier AI access could impact competitiveness. Vijay Rayapati, co-founder and CEO of Atomicwork, told JS that the incident underscored the risks for startups with teams spread across multiple countries if access to advanced AI systems becomes increasingly subject to geopolitical constraints.
Atomicwork employs about 25 individuals in the U.S., with a significant portion of its product engineering team located in Bengaluru, India.
“If your AI team is not made up entirely of U.S. citizens, you are at a competitive disadvantage,” Rayapati stated, pointing out that uneven access to frontier AI models could offer some companies a significant advantage over competitors.
This issue arises as segments of India’s tech sector are already dealing with questions about how AI might transform the economics of global talent. Recently, U.S. real estate tech company Opendoor closed its India office less than two years after expanding there, with CEO Kaz Nejatian citing a move to bring operational work closer to U.S. customers and a shift towards smaller AI-native teams.
While Opendoor did not clarify to what extent this decision was driven by AI-related efficiencies, the move has contributed to a broader debate about how AI advancements could influence the future of global technology work and what that might mean for India’s role as a hub for engineering talent.
Beyond Anthropic
Besides startups and AI developers, the Anthropic situation has also sparked a wider discussion among India’s tech leaders about reliance on foreign AI infrastructure.
Sridhar Vembu, founder of Indian SaaS company Zoho, remarked that the situation demonstrated how “technology is the ultimate weapon,” and he encouraged Indian organizations to adopt smaller and open-source models.
“What can our government do right now? Ensure that orgs in India embrace smaller models, both Indian and Chinese open source ones,” Vembu wrote on X.
Investor and former Infosys executive Mohandas Pai responded to Vembu on X, arguing that the situation underscores the necessity for a much more ambitious national AI strategy and urged the government to significantly boost investments in AI, computing infrastructure, and deep technology.
“We are way behind and need a national mission to get going quickly,” Pai wrote, recommending the establishment of an annual ₹500 billion (about $5 billion) fund for AI and deep tech, along with a ₹2 trillion (around $21 billion) credit guarantee program to support cloud infrastructure, hardware, and semiconductor development.
Pai’s proposal would greatly surpass India’s current AI initiatives. In 2024, New Delhi approved the IndiaAI Mission with an allocation of ₹103.72 billion (about $1.2 billion) over five years, aimed at expanding computing infrastructure, supporting startups, and fostering indigenous AI capabilities.
Despite growing interest in AI and New Delhi’s efforts to cultivate domestic capabilities, India remains a relatively minor player in the development of frontier models. Only a few startups are pursuing foundational AI models, such as Sarvam, which released open-source models earlier this year. However, another prominent AI startup, Krutrim, shifted its focus to cloud and AI infrastructure services after initially being centered on foundational model development.
Much of India’s AI ecosystem has instead focused on applications and specialized models built upon existing foundational models. Recent examples include Avataar AI, which recently launched a video-generation model aimed at providing a cost-effective alternative to offerings from competitors like Google’s Veo, Kling, Luma, and Runway.
Not everyone concurs that the lack of capital is the primary issue. Responding to Pai’s remarks, Lightspeed partner Hemant Mohapatra argued that the main constraints to creating globally competitive AI companies are talent, access to computing resources, and execution, rather than merely the size of investment commitments.
Mohapatra estimated that training a frontier AI model could cost from hundreds of millions to several billion dollars, depending on the strategy, but noted that successful AI companies have historically scaled their capital needs over time as adoption increased.
However, for some policy observers, the implications reach well beyond AI startups or model providers.
Prasanto Roy, a New Delhi-based technology policy expert who advises multinational companies, suggested that the situation would likely reinforce concerns within the Indian government regarding strategic autonomy, drawing parallels to the lesson many nations learned from Russia’s exclusion from SWIFT and other elements of the global financial system following its invasion of Ukraine.
He conveyed to JS that the move could provoke a significant nationalist response in India and described it as a poorly considered decision by Washington, with repercussions extending far beyond Anthropic itself.
“Even if this is corrected or reversed, the Anthropic episode shows there’s no such thing as a geopolitically neutral foreign LLM,” Roy said. “American AI models are bound to American geopolitics.”
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