The torrent of billion-dollar investment announcements related to artificial intelligence has raised fears that the economy is sitting on a bubble that, if popped, could send it into a tailspin.
Some on Wall Street aren’t buying it.
In a note to clients published Thursday titled “AI Spending Is Not Too Big,” Goldman Sachs economist Joseph Briggs made the case that the billions being spent on building out data centers — known as capital expenditures, or “capex” — remains sustainable.
In short: Briggs believes AI applications are leading to real productivity gains that will help boost companies’ bottom lines. Meanwhile, the cost of the computing processing needed to power those applications justifies the billions in spending, assuming the sophistication of the applications continues to improve.
In total, Briggs expects U.S. companies to generate as much as $8 trillion in new revenue thanks to AI.
“The key takeaway from our analysis is that the enormous economic value promised by generative AI justifies the current investment in AI infrastructure and that overall levels of AI investment appear sustainable as long as companies expect that investment today will generate outsized returns over the long run,” Briggs wrote.
Other key Wall Street players have echoed his assessment. This week, JPMorgan Chase CEO Jamie Dimon compared AI to the internet, which led to its own “dot com” bubble but ultimately created real economic and societal impact.
“You can’t look at AI as a bubble, though some of these things may be in the bubble. In total, it’ll probably pay off,” Dimon said at a conference hosted by Fortune.
Predictions about the economic impact of AI continue to run the gamut, from only a modest bump in productivity to the end of all jobs as we know them. Evidence of current effects so far is mixed, though the roster of companies citing AI or automation as a reason for job cuts — whether they actually intend to meaningfully increase its use — continues to grow.
Amid all those variables, AI’s biggest impact has arguably been on stock returns. Despite some recent drawdowns, major U.S. stock indexes continue to sit near all-time highs, thanks largely to gains from tech companies participating in the AI boom.
On Thursday, tech stocks got another lift when chip manufacturer Taiwan Semiconductor Manufacturing Co. (TSMC) reported record profits and soaring revenues. TSMC is the main supplier of semiconductors for Nvidia — the most valuable publicly traded company in the world — and it also counts Apple, Qualcomm and AMD as clients.
“Our conviction in the megatrend is strengthening, and we believe the demand for semiconductors will continue to be very fundamental as a key enabler of AI applications,” TSMC Chief Executive C.C. Wei told analysts on an earnings call.
Briggs of Goldman didn’t offer a direct comment about whether his analysis means AI-related stocks themselves have room to run. And there are growing signs that many investors now believe that whatever AI’s broader economic payoff is, stock valuations have become stretched. In its latest weekly investor sentiment survey, the American Association of Individual Investors found bullish sentiment had dipped below its historical average of 37.5% for the first time in five weeks, with 55% of respondents agreeing “stocks in general are overvalued.”
Briggs did warn that some of the companies whose shares have had the greatest run-ups so far won’t necessarily be the ones who end up reaping the greatest overall returns from the AI revolution.
“The ultimate winners from infrastructure builds are determined by a complex set of factors including timing, regulation, and market competition,” he wrote.
Eventually, Briggs said, computing costs will decrease, meaning some proportion of the current AI spending boom will look overdone in hindsight. But given a 15% boost to productivity, a slower adoption timeline and other factors, current spending levels on AI investment are sound, he added.
“While investment should eventually moderate as the AI investment cycle moves beyond the build phase and declining hardware costs dominate, the technological backdrop still looks supportive for continued AI investment,” he wrote.
Jim Cramer, host of CNBC’s “Mad Money,” had a similar assessment this week, comparing the current AI moment to the dawn of the railroad age.
“I am telling you, this is just the beginning,” he said. While not every company riding the wave will survive, the build-out itself changed the economy forever, he said, and “once the losers got wiped out, the winners won big.”
This article was originally published on NBCNews.com
The torrent of billion-dollar investment announcements related to artificial intelligence has raised fears that the economy is sitting on a bubble that, if popped, could send it into a tailspin.
Some on Wall Street aren’t buying it.
In a note to clients published Thursday titled “AI Spending Is Not Too Big,” Goldman Sachs economist Joseph Briggs made the case that the billions being spent on building out data centers — known as capital expenditures, or “capex” — remains sustainable.
In short: Briggs believes AI applications are leading to real productivity gains that will help boost companies’ bottom lines. Meanwhile, the cost of the computing processing needed to power those applications justifies the billions in spending, assuming the sophistication of the applications continues to improve.
In total, Briggs expects U.S. companies to generate as much as $8 trillion in new revenue thanks to AI.
“The key takeaway from our analysis is that the enormous economic value promised by generative AI justifies the current investment in AI infrastructure and that overall levels of AI investment appear sustainable as long as companies expect that investment today will generate outsized returns over the long run,” Briggs wrote.
Other key Wall Street players have echoed his assessment. This week, JPMorgan Chase CEO Jamie Dimon compared AI to the internet, which led to its own “dot com” bubble but ultimately created real economic and societal impact.
“You can’t look at AI as a bubble, though some of these things may be in the bubble. In total, it’ll probably pay off,” Dimon said at a conference hosted by Fortune.
Predictions about the economic impact of AI continue to run the gamut, from only a modest bump in productivity to the end of all jobs as we know them. Evidence of current effects so far is mixed, though the roster of companies citing AI or automation as a reason for job cuts — whether they actually intend to meaningfully increase its use — continues to grow.
Amid all those variables, AI’s biggest impact has arguably been on stock returns. Despite some recent drawdowns, major U.S. stock indexes continue to sit near all-time highs, thanks largely to gains from tech companies participating in the AI boom.
On Thursday, tech stocks got another lift when chip manufacturer Taiwan Semiconductor Manufacturing Co. (TSMC) reported record profits and soaring revenues. TSMC is the main supplier of semiconductors for Nvidia — the most valuable publicly traded company in the world — and it also counts Apple, Qualcomm and AMD as clients.
“Our conviction in the megatrend is strengthening, and we believe the demand for semiconductors will continue to be very fundamental as a key enabler of AI applications,” TSMC Chief Executive C.C. Wei told analysts on an earnings call.
Briggs of Goldman didn’t offer a direct comment about whether his analysis means AI-related stocks themselves have room to run. And there are growing signs that many investors now believe that whatever AI’s broader economic payoff is, stock valuations have become stretched. In its latest weekly investor sentiment survey, the American Association of Individual Investors found bullish sentiment had dipped below its historical average of 37.5% for the first time in five weeks, with 55% of respondents agreeing “stocks in general are overvalued.”
Briggs did warn that some of the companies whose shares have had the greatest run-ups so far won’t necessarily be the ones who end up reaping the greatest overall returns from the AI revolution.
“The ultimate winners from infrastructure builds are determined by a complex set of factors including timing, regulation, and market competition,” he wrote.
Eventually, Briggs said, computing costs will decrease, meaning some proportion of the current AI spending boom will look overdone in hindsight. But given a 15% boost to productivity, a slower adoption timeline and other factors, current spending levels on AI investment are sound, he added.
“While investment should eventually moderate as the AI investment cycle moves beyond the build phase and declining hardware costs dominate, the technological backdrop still looks supportive for continued AI investment,” he wrote.
Jim Cramer, host of CNBC’s “Mad Money,” had a similar assessment this week, comparing the current AI moment to the dawn of the railroad age.
“I am telling you, this is just the beginning,” he said. While not every company riding the wave will survive, the build-out itself changed the economy forever, he said, and “once the losers got wiped out, the winners won big.”
This article was originally published on NBCNews.com
