A potential AI slowdown has injected uncertainty into tech stocks, but some analysts believe the fears are overblown

Demand for chips, data centers and other infrastructure is likely to continue accelerating even if the pace of the AI build-out slows, one analyst said.

Calls from Anthropic CEO Dario Amodei, OpenAI's Sam Altman and Elon Musk to slow the rate of artificial-intelligence development are the latest overhang on fast-growing tech stocks.

But the market might be overreacting to the implications of an AI slowdown, leading tech stocks to trade at their cheapest levels since the launch of ChatGPT, according to Truist analyst Sam Grelck. Demand for chips, data centers and other infrastructure is likely to continue accelerating even if the pace of the AI build-out slows, Grelck wrote in a Tuesday note. "Slower model development injects uncertainty, but we are skeptical it reduces total demand over time," he said.

"It's too early to know, but markets don't wait for certainty, and the risk is that investors re-price the most expensive AI stocks on the uncertainty alone," Grelck added.

Valuations of tech stocks have compressed significantly in recent months. The tech sector, as measured by S&P Global's industry classifications, now trades at a multiple of 21x forward earnings estimates, down from an October level of 32x, according to Truist. This puts tech valuations back to late 2022 levels, when ChatGPT first kicked off the AI boom.

"As a result, investors are paying no more for technology stocks than they were before the AI era began. In our view, much of today's uncertainty is already reflected in valuations," Grelck said.

Meanwhile, the earnings strength of the tech sector continues to grow. Grelck noted that forward earnings estimates for tech stocks have increased 19% over the past three months, almost double the 10% growth for the second-strongest sector.

AI leaders like Anthropic's Amodei are pushing to slow the speed of model development to allow for safety and oversight to catch up. In an essay published last Saturday, Amodei proposed limitations on the computing power used to train models.

While Grelck acknowledged the uncertainties surrounding a potential pullback from the AI labs, he believes AI demand will "shift, not shrink" as more computing power is allocated to the inference workloads that power real-time AI tasks instead. More inference-heavy workloads would have the added benefit of improving profitability for the AI labs, as they can charge customers for inference, whereas model training is a pure cost.

"A higher mix of usage generates higher revenue and cash flow from existing infrastructure, a helpful offset to the financing and credit worries weighing on the group," Grelck said.

Bank of America analyst Vivek Arya echoed this sentiment, writing in a Tuesday note that despite concerns about a potential AI investment slowdown, "we see no signs of slowing in customer orders, [long-term agreements], capacity commitments or semis pricing."

The iShares Semiconductor exchange-traded fund SOXX has fallen nearly 25% since its peak in June. Current valuation levels are "compelling," according to Arya.

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-Christine Ji