JPMorgan Vice Chair Daniel Pinto Says ‘Correction’ Coming for AI Valuations
JPMorgan Chase Vice Chairman Daniel Pinto said Tuesday (Nov. 18) that artificial intelligence valuations need re-examination.
He also warned that a downturn among AI companies would have a broader impact on the larger stock market, Bloomberg reported Tuesday.
“There is probably a correction there,” said Pinto at the Bloomberg Africa Business Summit in Johannesburg, per the report. “That correction will also create a correction in the rest of the segment, the S&P and in the industry.”
Pinto is one of several Wall Street figures worried about the possibility of an AI bubble forming amid gargantuan investments in the sector, according to the report.
The five largest tech companies could spend an estimated $371 billion this year to develop the data centers required to train and run complex AI models. By the decade’s end, that infrastructure will need $5.2 trillion to keep up with demand, the report said, citing projections from McKinsey & Co.
“In order to justify these valuations, you are considering a level of productivity that, it will happen, but it may not happen as fast as the market is pricing now,” Pinto said, per the report.
Pinto downplayed the likelihood of a recession in the United States, while also painting a less-than-rosy picture of the stock market, according to the report.
“We do see some deceleration,” Pinto said, per the report. “I think that the economy may grow less next year, but most likely it will avoid recession.”
While the stock market may be concerned about AI valuations, finance teams are increasingly focused on the technology’s deployment.
“The evolution of AI in payments started across existing use cases, with models embedded in fraud detection, invoice matching and risk scoring,” PYMNTS reported Nov. 7.
Now, gains are beginning to materialize as AI crosses over into proactive and predictive territory.
For chief financial officers, AI’s capacity to improve financial outcomes falls into three categories: operational, strategic and relational. Operational return on investment (ROI) comes from reducing manual effort, strategic ROI emerges when AI helps finance leaders shape the company’s liquidity horizon, and relational ROI enhances trust between buyers and suppliers.
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