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With each passing day without an AI labor revolution, the tech industry’s pricing scheme for AI is becoming more and more disconnected from reality — so much so that even its biggest clients are starting to revolt.
Speaking during an interview on CNBC‘s “Squawk on the Street” segment earlier this week, CEO of cybersecurity giant Palo Alto Networks Nikesh Arora implored the tech industry to lower the cost of AI.
During the segment, the chief executive argued that the cost to use large language models (LLMs) has to drop by 20 percent by 2027 — and 90 percent by 2028 — for the tech to be useful to enterprises.
“We need to see the pricing for AI come down,” Arora said.
Zooming out, Arora’s pleas for cheaper AI are instructive. For your average CEO, the ostensible value of any AI tool is in its ability to automate human workers and either slash payroll costs or keep them low — hence the trillions of dollars capitalists have poured into the industry.
There’s just one problem: AI, or more specifically, LLMs, can’t seem to make automation happen in an effective way, and some argue they never will. Instead, AI has largely become a tool to discipline labor, to squeeze more work out of every worker and keep margins high.
Unfortunately for the CEOs of the world, the rising cost of AI threatens to disrupt even this less-than-optimal arrangement.
Approaching the issue from the opposite end — though without the drama of a CEO experiencing buyer’s remorse — is tech critic Ed Zitron. In a separate interview with the same CNBC panel, Zitron argued that the AI industry is a “$10 to $30 billion [total addressable market] industry pretending to be a $1 trillion one.”
The critic’s diagnosis is essentially the same: the tech industry’s pricing assumes a level of AI demand and value creation that doesn’t exist. The difference between the two is that Arora needs that to change in order to justify his outrageous AI bill, forcing a confession in line with one of the tech industry’s fiercest critics.
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