Is an AI Bubble Inevitable?
Remember the dot-com boom and collapse? Experts warn that history may repeat itself.
May 13, 2024
Is the AI industry headed toward "irrational exuberance?" That's the phrase then-Federal Reserve Board chairman Alan Greenspan used in a speech given at the American Enterprise Institute during the dot-com bubble of the 1990s.
Like the hype cycles of just about every technology preceding it, there's a significant chance – about 30% – of a major drawback in the AI market predicts Scott Zoldi, chief analytics officer at credit scoring services firm FICO, in an email interview.
Inspired by the hype surrounding GenAI, many organizations are exploring potential AI uses. This often occurs without understanding its core limitations, "or by trying to apply Band-Aids to not-ready-for-prime-time applications of AI," Zoldi says. He estimates that less than 10% of organizations can actually operationalize AI to enable meaningful execution.
Adding further pressure, Zoldi notes, is increasing AI regulation. "These AI regulations specify strong responsibility and transparency requirements for AI applications, which GenAI is unable to meet," he says. "AI regulation will exert further pressure on companies to pull back."
Pedro Amorim, an assistant professor of industrial engineering at Portugal's University of Porto, specializing in AI, data and analytics, says he's almost certain that a drawback will, at some point, be inevitable. "Factors such as the astronomical valuation of companies like NVIDIA, and the prevalence of decisions made by boards in every corner of world on investments in AI without any comprehensive understanding or rationality, suggest that the AI market is clearly hyped," he notes via email.
Jen Clark, director of advisory services at Eisner Advisory Group, is somewhat less pessimistic. "We’re more likely to witness a dampening in excitement and investment," she says, in an email interview. Clark agrees that the biggest threat to the AI market is hype. "Some of the excitement is greater than the current capabilities and ability to produce quality results."
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