'We need AI prices to come down': Palo Alto Networks CEO Nikesh Arora says AI is too expensive and needs to drop 90% to be affordable

Palo Alto Networks CEO Nikesh Arora says a 90% reduction in AI prices is needed to drive widespread adoption, with a 20% reduction by next year.
OpenAI’s latest GPT-5.6 Sol model is 54% more efficient in agent coding tasks
The shift toward consumption-based models is making high costs even more pronounced

Nikesh Arora, CEO of Palo Alto Networks, warned that the price of AI is still too high for widespread enterprise adoption, arguing that it should be drastically cheaper.

Although the efficiency and performance of the models have come a long way in recent years, he believes cost remains one of the biggest barriers to widespread adoption.

In a recent interview with C.NBCArora explained that he believes token prices need to fall by up to 90%, however, he acknowledges that the change is unlikely to happen immediately and instead welcomes a 20% price reduction over the next year.

Are AI prices preventing companies from widespread adoption?

Arora’s comments come in response to OpenAI’s latest announcement, which reveals that its latest GPT-5.6 Sol model now has 54% mode token efficiency in agent encoding tasks, a major improvement.

Although the CEO of Palo Alto Networks admitted that this in itself is a good start, it is not enough of an improvement to dramatically change the prices of large companies at this time.

“It is important to understand that the demand is still infinite,” he added, implying that the cost remains prohibitive. The issue of cost is also becoming increasingly concerning as AI companies evolve their pricing strategies, and customers move toward consumption-based models rather than fixed monthly fees per user.

Importantly, Arora’s vision of cheaper AI is not unfounded. Virtually all previous technological revolutions have already followed a similar pattern. In the case of AI, computing would become cheaper, models would become more efficient, and competition could keep prices low, all of which would benefit enterprise customers.

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