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AI stocks fell globally after Anthropic CEO Dario Amodei urged a slower pace for frontier AI development, backed by OpenAI’s Sam Altman and Elon Musk. The warnings have raised fresh investor concerns about AI spending, chips and data-centre demand.
AI stocks fell sharply across global markets on Monday after Anthropic CEO Dario Amodei called for a slower pace of frontier AI development. The warning was backed by OpenAI CEO Sam Altman and Elon Musk, creating an unusual show of agreement among major AI leaders.
Investors are now questioning what a slowdown could mean for the massive spending on chips, data centres and computing power that has fuelled the AI boom.
In Asia, SoftBank shares fell about 12% in Tokyo. The company is one of the biggest investors in OpenAI, with a roughly $64.6 billion commitment. South Korea’s AI-linked giants also came under pressure. SK Hynix and Samsung Electronics fell sharply as investors reassessed the outlook for memory chips used in AI infrastructure.
The selling spread to Europe. ASML, Infineon and Nokia were among the companies hit, while data-centre suppliers such as Siemens Energy and Schneider Electric also declined. US-listed AI and semiconductor stocks were lower in premarket trading, with Micron, Intel and Nvidia among the major names under pressure.
The debate intensified after Anthropic researcher Jacob Coxon resigned, saying AI companies were moving too quickly and “gambling with our lives”. Anthropic researcher Evan Hubinger then said he personally estimated there was a greater than 10% chance that AI could “kill all humans” within the next decade. Those are individual risk assessments, not established predictions.
Amodei’s response was more focused on controlling the pace of development. In his essay, “We Must Pace the Frontier,” he argued that AI capabilities are advancing quickly enough to create serious risks, including loss of control, cyberattacks and bioterrorism.
OpenAI’s Sam Altman backed Amodei, saying AI companies need to “pace the frontier”. But Altman stressed that pacing does not mean stopping AI development. He said progress will continue, although it should be slower than it otherwise might be because safety testing and monitoring add costs and time.
That distinction matters for investors. A slower development cycle could reduce demand for some new chips and computing capacity. But analysts argue that AI infrastructure demand remains extremely strong, particularly for inference the computing needed to actually run AI models for users. “The pace of change is still going to be vast,” Quilter Cheviot technology researcher Ben Barringer told CNBC, arguing that demand for inference remains greater than available supply. For markets, the immediate question is therefore not whether the AI boom is ending. It is whether the enormous expectations already priced into AI companies can survive a world where the industry deliberately chooses to move more carefully.