Anthropic’s sudden move to suspend access to its newest AI models following a US government directive has raised new questions across the global tech industry. In India, the decision has reignited a long-running debate over whether one of the world’s biggest AI markets can afford to rely on technologies made and controlled elsewhere.
The announcement came late Friday, when Anthropic said it had received the US government’s directive requiring it to suspend access to the recently released Fable 5 and Mythos 5 models for all foreign nationals, including its own foreign national employees. The move came shortly after the company announced a partnership with Indian IT giant Tata Consultancy Services to expand the adoption of business AI in India, underscoring how closely the country’s AI ambitions have been tied to technologies developed and governed in the US.
While the broader implications remain unclear, some reports said initial security concerns were first raised with the government by Amazon CEO Andy Jassy. And the Information he said the White House is unlikely to extend similar restrictions to other AI companies, and has privately blamed Anthropic’s handling of alleged jailbreak vulnerabilities. Anthropic disputed the government’s characterization and argued that the action should not have been taken.
Regardless, the development has sparked debate among Indian founders, investors and policy experts about whether the country should accelerate efforts to build domestic AI capabilities, deepen investment in open-source alternatives, or continue to rely on a handful of U.S. frontier model providers. For some, the episode is a wake-up call about technological dependency. 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 frontier AI companies. Anthropic and OpenAI have both described the South Asian nation as theirs second largest market after the US, reflecting its growing importance in the global AI race. Companies have already set up offices in India, expanded local hiring, partnerships and business initiatives in recent months, betting on India’s huge base of developers, startups and enterprises to accelerate adoption of their latest technologies.
For many in India’s tech sector, Anthropic’s announcement on Friday was about more than just one AI company. It reopened questions about the country’s long-term AI strategy and whether India could afford to remain dependent on a small number of foreign border AI providers.
“It completely changes things,” said Aakrit Vaish, founder of the Indian business AI platform Activatereferring to the Anthropic decision. “I think this fundamentally changes the way all of us should be thinking about mainstream AI in India.”
Vaish told TechCrunch that he woke up Saturday morning “shocked and confused” by the announcement, and said it strengthened 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 AI providers.
For some founders, the bigger concern was what restrictions on cross-border access to AI could mean for competitiveness. Vijay Rayapati, its co-founder and CEO Individual worktold TechCrunch that the episode highlighted the risks facing startups whose teams span multiple countries if access to advanced AI systems is increasingly subject to geopolitical restrictions.
Atomicwork has about 25 employees in the US, although much of its engineering product team is based in Bangalore, India.
“If your AI team isn’t made up entirely of US citizens, you’re at a competitive disadvantage,” Rayapati said, arguing that unequal access to border 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 artificial intelligence could reshape global talent economics. US real estate technology firm Opendoor this week closed its India offices less than two years after expanding into the country, with CEO Kaz Nejatian citing a push to bring operational work closer to US clients and a shift to smaller native AI teams.
While Opendoor did not specify how much of the decision was due to AI-related efficiencies, the move added to a broader discussion about how advances in artificial intelligence could affect the future of global tech work and what that might mean for India’s position as a hub for engineering talent.
Beyond Anthropic
Apart from AI startups and manufacturers, the Anthropic episode also sparked a broader conversation among India’s tech leaders about reliance on foreign AI infrastructure.
Sridhar Vembu, founder of Indian SaaS company Zoho, said the move shows that “technology is the ultimate weapon” and urged Indian organizations to increasingly embrace smaller and open-source models.
“What can our government do right now? Make sure organizations in India embrace smaller open source models, both Indian and Chinese,” Vembu he wrote in X.
Investor and former Infosys executive Mohandas Pai he responded in Vembu on X, arguing that the development underscored the need for a much more ambitious national AI strategy and calling on the government to significantly increase investment in AI, computing infrastructure and deep technology.
“We are far behind and need a national mission to move forward quickly,” Pai wrote, urging the government to create a ₹500 billion (about $5 billion) annual fund for artificial intelligence and deep technology, along with a ₹2 trillion (about $21 billion) credit guarantee program to support cloud infrastructure, hardware and semiconductor development.
Pai’s proposal would overshadow India’s existing AI efforts. In 2024, New Delhi was approved the IndiaAI mission with an outlay of ₹103.72 billion (about $1.2 billion) over five years, aimed at expanding computing infrastructure, supporting start-ups and developing indigenous AI capabilities.
Despite growing interest in artificial intelligence and New Delhi’s push to develop domestic capabilities, India remains a relatively small player in developing cutting-edge models. Only a handful of startups are pursuing basic AI models, including Sarvam, which released open source models earlier this year. However, another high-profile startup, Krutrim, turned to cloud infrastructure services and AI after initially positioning itself around developing fundamental models.
Much of India’s AI ecosystem has focused on applications and specialized models that build on existing foundational models. Recent examples include Avataar AI, which launched a video production model earlier this week aimed at providing a lower-cost alternative to offerings from competitors including Google’s Veo, Kling, Luma and Runway.
Not everyone agrees that the primary challenge is a lack of funds. Responding to Pai’s comments, Lightspeed partner Hemant Mohapatra argued that the biggest constraints to building competitive AI companies globally are talent, access to computing resources and execution, not just the size of investment commitments.
Mohapatra estimated that training a frontier AI model could cost anywhere from hundreds of millions to several billion dollars, depending on the approach, but said successful AI companies have historically scaled their capital requirements over time as adoption increased.
But for some policy watchers, 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 the Indian government’s concerns 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 thought-out decision by Washington, with consequences that extend far beyond Anthropic itself.
“Even if this is corrected or reversed, the Anthropic episode shows that there is no such thing as a geopolitically neutral foreign LLM,” Roy said. “US AI models linked to US geopolitics”.
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