A wave of selling hit AI-related names on Monday after Anthropic's Dario Amodei argued in an essay that "We must slow the pace at which we improve the capabilities of AI models." That message, amplified by high profile voices, landed just as debate over AI risks flared online following a researcher's public resignation.
Asia led off with declines: SK Hynix finished down more than 6% and Samsung Electronics slipped more than 4%. In Japan, SoftBank - among the largest backers of OpenAI - fell 10%.
Europe followed with sharp losses in semis and AI-adjacent plays. Across Europe, ASML declined by over 5%, Nokia slipped roughly 8%, and Infineon shed more than 7%. Companies tied to data center infrastructure, including Siemens Energy and Schneider Electric, also traded lower.
The weakness reached the U.S. as well. Micron was down around 7%, Intel slid 6%, and Nvidia fell more than 3%, with several other chip stocks under pressure. Big cloud platforms such as Amazon dipped slightly. Around 10:33 AM EDT, Nvidia last traded at 210.69 dollars, down 7.60 dollars or 3.48%.
The selling arrived after a burst of online posts about AI safety. Jacob Coxon - an Anthropic researcher and former OpenAI employee - stated that he quit because he fears the two companies are "gambling with our lives." Anthropic safety researcher Evan Hubinger also said he thinks the odds exceed 10% that AI will "kill all humans" within the next decade. The uproar drew swift responses from industry leaders.
Amodei's Saturday essay pressed for a slower push on frontier capabilities, not a freeze. He wrote that "progress will still seem fast." That same day, OpenAI CEO Sam Altman said he concurs with Amodei that AI companies ought to "pace the frontier," and on Monday he clarified on X that "pacing" does "not mean 'stopping'." Altman added, "Progress has been rapid and will continue to be. But it should be slower than it otherwise could be; interventions like safety cases and monitoring have significant costs." Elon Musk weighed in too, posting, "Dario is right."
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There is concern that any broad deceleration could affect everything from chip purchases to demand for computing power, for which hundreds of billions of dollars in capital outlays are slated. On CNBC's "Squawk Box Europe," RBC Brewin Dolphin's senior director Zoe Gillespie remarked, "The kind of equity market rally has been based on AI growth and productivity gains … so if we do see that start to derail, then it could have an impact on equity performance going forward." She added that expectations for future earnings are embedded in today's prices, and if those are threatened, "we may see this destabilize."
Analysts emphasized that a moderated rollout would not necessarily slam the brakes on revenue. In an interview with CNBC, Quilter Cheviot's global head of technology research, Ben Barringer, stated that "while things may slow somewhat, the pace of change is still going to be vast." He noted that even if training and deployment cool, the bottleneck is in inference - the running of AI systems - where demand still far exceeds available supply. In his view, that imbalance suggests company revenues are unlikely to be hit, even if development eases.
Markets just signaled that AI isn't a one way bet. If companies collectively move more cautiously, spending on chips and compute could land later or lower than expected, and that matters to stock prices built on aggressive growth. At the same time, the core message from industry voices is not stop, but slow - and if inference remains supply constrained, demand may keep flowing even with a gentler pace on frontier models. For regular investors, it is a reminder to look under the hood of any AI exposure and know whether it leans on training firepower, inference capacity, or the data center ecosystem around both.
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