India debates AI future as Anthropic suspends access to new models

Anthropic’s abrupt suspension of access to its latest AI models, following a directive from the U.S. government, has sparked renewed scrutiny across the global technology sector. In India, this decision has rekindled a longstanding debate regarding whether one of the world’s largest AI markets can sustain its growth while relying on technologies developed and controlled abroad.

The announcement was made late Friday, with Anthropic stating it received a U.S. government order to restrict access to its newly released Fable 5 and Mythos 5 models for all foreign nationals, including its own international staff. This move occurred shortly after the company announced a strategic partnership with Tata Consultancy Services, India’s IT giant, to expand enterprise AI adoption, highlighting the intricate ties between India’s AI ambitions and U.S.-governed technologies.

While the broader consequences remain uncertain, reports suggest that Amazon CEO Andy Jassy initially flagged security concerns to the government. Additionally, The Information reported that the White House is unlikely to impose similar restrictions on other AI firms and is privately criticizing Anthropic’s management of alleged jailbreak vulnerabilities. Anthropic has contested the government’s stance, arguing that the suspension was unwarranted.

Regardless of the specifics, this development has ignited discussions among Indian founders, investors, and policy experts about whether the country should accelerate domestic AI development, invest more heavily in open-source alternatives, or continue depending on a select group of U.S. frontier model providers. For some, this incident serves as a stark warning about technological dependency; for others, it underscores how access to critical AI systems can be influenced by geopolitical factors beyond India’s control.

India has emerged as a crucial market for frontier AI companies. Both Anthropic and OpenAI have identified South Asia as their second-largest market after the U.S., reflecting its rising significance in the global AI landscape. These companies have established local offices, expanded hiring, and launched partnerships and enterprise initiatives in recent months, betting on India’s extensive pool of developers, startups, and businesses to drive the adoption of their latest technologies.

For many in India’s tech sector, Anthropic’s Friday announcement extended beyond a single company’s actions. It reopened critical questions about the nation’s long-term AI strategy and whether India can afford to remain dependent on a limited number of foreign frontier AI providers.

“It completely changes things,” said Aakrit Vaish, founder of 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 told TechCrunch that he woke up on Saturday morning “shocked and confused” by the announcement, stating that it strengthened the case for developing domestic AI capabilities. He anticipates that startups will increasingly turn to open-source models and plans to encourage companies in his portfolio to reduce their reliance on a few frontier AI providers.

For some founders, the primary concern lies in what restrictions on frontier AI access might mean for competitiveness. Vijay Rayapati, co-founder and CEO of Atomicwork, told TechCrunch that this episode highlighted the risks facing startups with multinational teams if access to advanced AI systems becomes increasingly subject to geopolitical constraints.

Atomicwork employs around 25 people in the U.S., although much of its product engineering team is based in Bengaluru, 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 provide some companies with a significant edge over their rivals.

These concerns arise as parts of India’s tech sector are already grappling with questions about how AI might reshape the economics of global talent. Earlier this week, U.S. real estate technology company Opendoor closed its India office less than two years after expanding in the country. CEO Kaz Nejatian cited a strategy to bring operational work closer to U.S. customers and a shift toward smaller, AI-native teams.

While Opendoor did not specify the extent to which AI-related efficiencies drove this decision, the move added to a broader debate about how AI advancements could impact the future of global technology work and what this might mean for India’s position as an engineering talent hub.

Beyond Anthropic

In addition to startups and AI builders, the Anthropic incident prompted a wider discussion among India’s technology leaders regarding dependence on foreign AI infrastructure.

Sridhar Vembu, founder of Indian SaaS company Zoho, stated that the move demonstrated that “technology is the ultimate weapon” and urged Indian organizations to increasingly 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 this development highlighted the need for a more ambitious national AI strategy. He called on the government to substantially increase investments in AI, computing infrastructure, and deep technology.

“We are way behind and need a national mission to get going quickly,” Pai wrote, urging the government to establish an annual ₹500 billion (approximately $5 billion) fund for AI and deep tech, alongside a ₹2 trillion (around $21 billion) credit guarantee program to support cloud infrastructure, hardware, and semiconductor development.

Pai’s proposal would significantly exceed India’s current AI initiatives. In 2024, New Delhi approved the IndiaAI Mission with a budget of ₹103.72 billion (about $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 push to develop domestic capabilities, India remains a relatively minor player in frontier model development. Only a handful of startups are pursuing foundational AI models, including Sarvam, which released open-source models earlier this year. However, another high-profile AI startup, Krutrim, pivoted toward cloud and AI infrastructure services after initially focusing on foundational model development.

Most of India’s AI ecosystem has instead focused on applications and specialized models built on top of existing foundation models. Recent examples include Avataar AI, which launched a video-generation model earlier this week, aiming to provide a lower-cost alternative to offerings from competitors such as Google’s Veo, Kling, Luma, and Runway.

Not everyone agrees that the primary challenge is a lack of capital. Responding 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 merely 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 noted that successful AI companies have historically scaled their capital requirements over time as adoption grew.

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 this incident would likely reinforce concerns within the Indian government about strategic autonomy. He compared it to the lessons many countries drew from Russia’s loss of access to SWIFT and other parts of the global financial system following 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, with consequences 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.”