The hype surrounding AI is currently unavoidable. Promises of new developments such as personal Robot assistants And Miraculous cures for cancer are omnipresent as leaders use every opportunity to emphasize their AI capabilities excited investors – and somewhat less enthusiastic Consumer.
However, not everyone is enamored by the AI fanfare. James Ferguson, founding partner of British macroeconomic research firm MacroStrategy Partnership, fears that investors’ enthusiasm for AI has created a concentrated market bubble reminiscent of the dot-com era.
“Historically, these cases end badly,” Ferguson told Bloomberg’s Merryn Somerset Webb in the latest episode of Merryn talks about money Podcast. “Anyone who is a little older and has experienced something like this is tempted to believe that it will end badly.”
The experienced analyst argued that hallucinations – the tendency of large language models to invent facts, sources, etc. – may prove to be a more persistent problem than initially thought, resulting in far fewer viable applications for AI.
“AI is still completely unproven in my opinion. And in Silicon Valley, it might work to pretend until it works, but for the rest of us, AI is probably more of a ‘burnt child dreads the fire,'” he said. “If you can’t trust AI… then I think AI is basically useless.”
Ferguson also noted that AI may end up being too “energy hungry” to be a cost-effective tool for many companies. To his point, a recent Study at the Amsterdam School of Business and Economics concluded that AI applications alone could consume as much electricity as the Netherlands by 2027.
“Forget NVIDIA “If you keep charging more for your chips, you have to pay more and more to run those chips on the servers. And so you end up with something that is very expensive and hasn’t been proven to be worthwhile anywhere except for a few very limited applications,” he said.
Ferguson warned investors, especially those passionate about AI, that the over-hyped tech hype based on questionable promises is very similar to the era leading up to the dot-com crash. He noted that market returns in both periods were concentrated in tech stocks trading on Wall Street’s sky-high earnings growth forecasts.
But despite these lofty predictions, the dominant hardware giants of the dotcom era, Cisco and Intelhave largely disappointed investors since then. Ferguson argued that today’s AI hardware hero Nvidia could face a similar fate, especially given its lofty valuation.
“At what multiple of revenue is Nvidia a good deal, considering that no matter how stratospheric the growth rate is right now, the company is unlikely to be a major player in a decade?” he asked, suggesting that Nvidia may not be worth the current price of nearly 40 times revenue that investors are paying.
Despite arguing that AI-related technology stocks like Nvidia are highly overvalued, Ferguson acknowledged that no one can predict when a bubble will burst. This dynamic causes many bearish investors to “feel compelled to get in on the markets” even when the stocks seem expensive, the analyst said – and that’s a good way to get hurt.
“I mean, that’s certainly what happened in the dot-com era. [bubble]where, for example, almost everyone who wasn’t a retail bettor looked at these things and said, ‘This can’t go on like this, but on the other hand, if this goes on for another quarter and I don’t play, I’m going to lose my job,’ he explained.
The good news, according to Ferguson, is that there is still value potential because the current stock market bubble is so focused on AI-related stocks.
Of course, it will be painful for investors when the AI bubble bursts. But after that, says Ferguson, it’s worth looking at currently unpopular U.S. small-cap stocks that could benefit from rate cuts and aren’t highly valued.
“There is a lot of value to be found in the U.S. The problem is that that value has to be found the good old way, by sifting through small caps and looking for companies that are growing the good old steady way,” he said.