"Gartner has signaled that the supply of "agentic AI" in terms of models, platforms, and products far outstrips demand, creating a situation that will lead to consolidation and market correction. The analyst company expects the agentic AI market - based on LLM-powered models that perform tasks for humans - to consolidate in the short term as the last couple of years' hype and "fear of missing out" (FOMO) give way to fundamental economics."
"Gartner's position follows the Bank of England's warning that there is a danger of a sudden correction in the financial markets, owing to the value of tech and AI stocks, citing some financial metrics that are comparable to the dotcom bubble of the late 1990s that led to a crash in early 2000. Equity markets might be "particularly exposed should expectations around the impact of AI become less optimistic," the Financial Policy Committee said."
"Gartner said that in a correction, the losers of consolidation would be undifferentiated AI companies and their investors, while the winners would be capital-rich incumbents with the resources to acquire promising technologies and talent. "While we see early signs of market correction and consolidation, product leaders should recognize this as a regular part of the product life cycle, not a sign of inevitable economic crisis," said Will Sommer, senior director analyst at Gartner."
Supply of agentic AI models, platforms, and products far outstrips demand, creating conditions for consolidation and market correction. The agentic AI market, based on LLM-powered systems that perform tasks for humans, is expected to consolidate as recent hype and FOMO yield to fundamentals. The Bank of England warned of a sudden financial-market correction owing to tech and AI valuations comparable to the late 1990s dotcom bubble. Equity markets could be particularly exposed if expectations around AI impact weaken. The IMF warned that market shocks could threaten global growth. Leading vendors formed complex financial interdependencies to build infrastructure; Bain estimates $500 billion per year is needed through 2030. In a correction, undifferentiated AI companies and their investors would likely lose, while capital-rich incumbents could acquire technologies and talent.
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