AI token prices must fall up to 90%



TL;DR

Palo Alto Networks CEO Nikesh Arora told CNBC that AI token prices need to fall by as much as 90% for large-scale enterprise adoption, calling OpenAI’s 54% GPT-5.6 efficiency gain “a good start” but not enough. He argued demand is “infinite” and costs will “rationalize over time.” His plea reflects a real paradox: per-token prices have collapsed while total enterprise AI bills keep rising, driven by agentic usage.

Palo Alto Networks chief executive Nikesh Arora says the cost of running AI needs to plunge before businesses can deploy it at scale. He told CNBC on Thursday that token prices may need to fall by as much as 90%, according to CNBC.

Arora was reacting to OpenAI’s claim that its new GPT-5.6 model is 54% more token-efficient on agentic coding. “I think 54% is a good start,” he said, making clear it is nowhere near enough.

He wants the trend to continue, with efficiency improving further over the next year and dramatically more the year after. Only then, in his telling, does mass enterprise adoption become affordable.

Despite the sticker shock, Arora is not bearish on demand. “The demand continues to be infinite,” he said, arguing that with an infinite demand curve, costs “will rationalize over time”.

His logic is that the market will either grow into the spending or force prices down. Budgets should ease, he suggested, as the underlying technology becomes more efficient.

The paradox behind the plea

Arora’s complaint captures a genuine puzzle in enterprise AI. Per-token prices have collapsed, yet total bills keep climbing, so much so that prices fell 98% while enterprise AI bills tripled.

The culprit is agentic AI, which calls a model over and over to complete a task. A single ambitious project can burn through a fortune, as one developer’s agents ran up a $1.3m token bill in a month.

That is why cheaper headline prices do not automatically translate into lower costs. Usage grows faster than prices fall, and the bill goes up anyway.

Squeezed buyers and a price war

The strain is already changing behaviour, with some firms capping how much AI staff can use as costs bite. Arora is voicing, from the buyer’s seat, a frustration many enterprises share.

The good news for him is that a price war is under way, with DeepSeek making a 75% discount permanent and rivals racing to match. A wave of startups is also chasing cheaper inference to squeeze more output from every chip.

Whether that adds up to Arora’s 90% is another matter, since efficiency gains can be swallowed by ever-heavier usage. His bet is that scale eventually wins, and the economics settle.

For now, the man running a cybersecurity giant is effectively telling AI vendors their product is still too expensive to use everywhere he wants to use it. Coming from a customer of that size, it is a message the model makers will hear.



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TL;DR

India debates sovereign AI after the US forced Anthropic to kill Fable 5, with proposals for a $5B fund and calls to embrace open-source models.

When the US government ordered Anthropic to shut down Fable 5 and Mythos 5 on 12 June, the export control directive was aimed at restricting foreign nationals from accessing America’s most capable AI. In India, Anthropic’s second-largest market, it landed as a warning shot about what happens when your AI infrastructure runs on someone else’s politics.

The suspension cut off Indian developers and enterprises from Claude’s most advanced models overnight. India’s Claude run-rate revenue had doubled since October 2025, and Tata Consultancy Services had announced a partnership just one day earlier, on 11 June, to train 50,000 employees on Claude and build a dedicated Anthropic business unit. That deal is now in limbo.

The timing has turned what was already a simmering debate about AI sovereignty into a full strategic reckoning. Proposals that sounded ambitious a week ago now sound urgent.

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Mohandas Pai, former Infosys CFO and one of India’s most prominent tech investors, has called for a ₹50,000 crore (roughly $5 billion) annual sovereign AI fund. He has also proposed a ₹2 lakh crore (approximately $21 billion) credit guarantee to finance cloud infrastructure, hardware procurement, and semiconductor development. The figures dwarf the government’s existing commitment.

India approved its IndiaAI Mission in March 2024 with a budget of ₹10,372 crore, approximately $1.25 billion. The programme has deployed around 38,000 GPUs so far. Pai’s proposal would quadruple annual spending and add a credit backstop an order of magnitude larger.

Sridhar Vembu, the founder of Zoho, has gone further. He argued that India should embrace smaller and open-source models, including Chinese ones, rather than depend on American frontier systems that can be switched off by executive order. “Technology is the ultimate weapon,” Vembu said. “Globalization is dead and Bharat must find her own way ahead.

The argument has teeth because the suspension demonstrated exactly the vulnerability Vembu is describing. Amazon’s CEO reportedly triggered the government crackdown by telling Treasury Secretary Scott Bessent that researchers had used Fable 5 to obtain information that could be used in cyberattacks. Anthropic called the action disproportionate, but compliance was immediate and global.

Policy expert Prasanto Roy put it bluntly: “American AI models are bound to American geopolitics.” For Indian enterprises that had built workflows around Claude, the lesson was that access to frontier AI is a privilege that can be revoked without notice, without consultation, and without regard for the commercial relationships it disrupts.

The Indian startup ecosystem is already adapting. Sarvam, a Bengaluru-based AI company, released 30-billion and 105-billion parameter open-source models at the India AI Impact Summit in 2026. Krutrim, founded by Ola’s Bhavish Aggarwal, has pivoted from building foundational models to providing cloud and AI infrastructure services, reporting ₹3 billion in revenue for fiscal year 2026.

Neither company is close to matching the capabilities of Fable 5 or Mythos 5. But the argument for sovereign AI was never about matching frontier performance immediately. It is about ensuring that the floor does not fall out when Washington makes a unilateral decision about who gets to use which models.

Aakrit Vaish, founder of the AI startup Activate, said the suspension “completely changes things” for the sovereign AI debate. Vijay Rayapati, CEO of Atomicwork, raised concerns about what the precedent means for Indian companies with multi-country teams that depend on American AI providers. If the US can shut off model access to enforce export controls, any country that relies on American AI is one policy decision away from disruption.

Not everyone agrees that India needs to build its own frontier models. Hemant Mohapatra, a partner at Lightspeed Venture Partners, argued that talent and compute access matter more than capital for building competitive AI. India has the engineering workforce, but the compute gap is significant, and closing it requires either massive domestic investment or continued access to foreign cloud infrastructure.

Anthropic opened a Bengaluru office as part of its India expansion, and the TCS partnership was designed to be a cornerstone of its enterprise strategy in the country. Whether those plans survive the suspension intact depends on how quickly Anthropic can restore access and whether Indian enterprises still trust a provider whose most capable models can vanish overnight.

The broader pattern is unmistakable. The US has spent four years tightening controls on AI technology, from chip export restrictions to model-level interventions. Each escalation pushes more countries toward the conclusion that dependence on American AI infrastructure carries political risk. India, with its 1.4 billion people and rapidly growing technology sector, is now asking whether it can afford that risk, and what it would cost to eliminate it.

The Opendoor layoffs in June 2026, which shut the company’s India office and affected roughly 250 employees, added another dimension. CEO Kaz Nejatian cited AI-native teams as the reason, suggesting that some US companies are using AI to reduce their reliance on Indian engineering talent at the same time that India is debating its reliance on American AI. The relationship is becoming less complementary and more competitive.

For now, the sovereign AI proposals remain proposals. Pai’s fund has no legislative vehicle, Vembu’s call for open-source adoption has no coordinated policy framework, and the IndiaAI Mission’s GPU deployment is still in early stages.

But the Anthropic suspension has done something that years of policy papers and conference speeches could not: it has given the sovereign AI movement a concrete, recent, and viscerally felt example of why dependence on foreign AI is a strategic liability. The debate is no longer theoretical.



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