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The economics of artificial intelligence deployment are outpacing what most enterprise budgets can absorb.
Against that backdrop, Palo Alto Networks chief executive Nikesh Arora made a pointed call: AI pricing needs to fall 90 percent before commercial adoption can move from early experiments to anything resembling scale across corporate infrastructure.
The cost barrier Arora named Arora's argument centers on token costs, which he described as skyrocketing at a pace that prices out the broad business market.
Costs that rise steeply on the supply side get passed to enterprises through token-based pricing, and at current rates the math does not work for most use cases outside of narrow, high-value applications.
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