US Stock AI Trading Panic Spreads as Market Enters Fundamental Validation Period

Wu Qi and Liu Yiwen

The narrative around artificial intelligence (AI) markets has undergone a dramatic shift. As we enter 2026, the once-booming “AI gold rush” has suddenly cooled.

In January, the dominant view was that “AI is burning money without returns,” and concerns grew over the long investment cycle for AI in the US stock market. In February, the “AI disruption theory” took over market sentiment, triggering panic trading in US stocks.

Within just a month, panic spread from the software industry to finance, law, consulting, commercial real estate, logistics, media, and other sectors. Investors shifted their focus to sectors perceived as “resilient to AI shocks.” Is this sell-off merely emotional venting or a rational warning? How long will this adjustment last? These questions are highly关注 to investors.

Dissecting the AI Sell-off

If in 2025, international investors still believed in AI, then in the first two months of 2026, AI has been viewed as a threat by the market.

After Anthropic launched legal AI tools, US legal software and data service companies plummeted on February 3. The next day, the sell-off spread to software, semiconductors, and AI infrastructure sectors. That week, private credit markets also felt the impact, with firms like Ares and KKR, heavily concentrated in software holdings, experiencing sharp declines.

On February 9, online insurance platform Insurify launched a new AI tool, causing the S&P 500 Insurance Index to fall 3.9% that day. On February 10, Altruist introduced AI tax planning tools, leading to a collective drop in US wealth management stocks. On February 11, panic extended to the US real estate services sector. On February 12, AI logistics company Algorhythm released a white paper claiming AI algorithms could triple productivity, prompting a sell-off in trucking and logistics sectors.

On February 23, Citrini Research published a report titled “Global AI Crisis 2028,” projecting that rapid AI development could trigger a chain reaction of economic crises, reigniting sell-offs among US investors.

A fund manager from a public mutual fund company told Securities Times that since February, the adjustment in some AI sectors is due to two reasons: first, concerns about business models driven by AI technological iterations; second, increased market discussion about AI technological routes. “But it’s important to clarify that technological evolution is normal for industry development. Discussions about new tech routes actually indicate rapid industry progress.”

Zhang Jiqiang, head of the Huatai Securities Research Institute, stated that since 2026, the global AI narrative has shifted at least three times: first, the traditional “bigger models, more data, stronger computing power equals better performance” rule is showing cracks, such as diminishing marginal returns and data bottlenecks; second, the market has shifted from rewarding “capital expenditure” to worrying about “slow monetization”; third, concerns about AI disruptive potential.

Zhang believes these three narratives point to real issues, but the timing and ultimate boundaries of these changes are hard to predict in advance. Currently, the market is making linear extrapolations under panic, pricing in the worst-case scenarios. One key reason may be the overvaluation and fragility of trading structures, which amplify panic. Before this correction, AI-related sectors were valued at historic highs, and even the commercial software sector was not undervalued, leading to concentrated sell-offs triggered by narratives.

Market “Overreaction”

Regarding the panic-driven trading in US stocks caused by AI fears, all interviewed institutions agree that the market is “overreacting.” There is confusion about which industries will be disrupted and how quickly. However, opinions differ on the extent of AI’s impact on traditional industries.

Yang Cheng, deputy head of the Information Science and Technology Industry Chain Group at China Merchants Fund, said this is a short-term overreaction. Historically, capital markets tend to overestimate the short-term impact of an event and underestimate long-term changes.

“We are mid-way through the intelligent era. AI remains an effective tool to boost productivity. While AI will reshape many industries, it won’t eliminate them. industries or companies that effectively utilize AI will have a competitive advantage.” He also warned that current AI architectures, hallucination issues, response delays, and insufficient computing resources still can’t meet high-reliability enterprise needs, meaning new technologies require long-term adaptation from emergence to mature application.

Jiang Jialin, assistant director at Industrial Securities’ Institute of Economics and Finance, also noted that the sell-off is driven by herd mentality and emotional factors. He explained that panic trading mainly stems from anxiety over future uncertainties, but uncertainty doesn’t mean destruction. Historical experience shows that initial panic during technological revolutions is often accompanied by chance, and AI’s industry reshaping is gradual, not a sudden “bankruptcy wave.” Most industries will adapt AI to improve efficiency.

He believes that while AI’s impact on traditional industries is intense, it is less destructive than the internet revolution. The core benefit is the release of technological dividends, not industry destruction. Although AI may disrupt some basic jobs, in the long run, it will promote economic growth and structural optimization, pushing industries toward higher-end upgrades.

Wu Mingyuan, chief analyst at Chuang Securities for computer technology, offered a different view. He said the current sell-off is a combination of “structural undervaluation” and “excessive emotional reaction,” but the disruptive impact of AI on traditional industries is indeed underestimated.

Wu believes that Nassim Nicholas Taleb’s warning about “black swans” is not unfounded: first, tail risks in various industries are structurally underestimated, with risks not just minor corrections but significant retracements; second, the sustainability of leading AI companies is overestimated, as early pioneers are often replaced. His judgment is based on two facts: real cases of AI agents being implemented, and the foundational shake-up of traditional business models.

Ping An Technology Innovation Hybrid Fund manager Zhai Sen also believes that from a long-term perspective, AI’s impact on traditional industries is not overestimated—in some niche areas, it may even be underestimated.

Market Entering a Phase of Assimilation and Validation

The market’s concern remains whether the AI panic in US stocks in February will continue. Many institutions believe the correction is not over but that the extreme phase is passing, and the market will enter a period of digestion and validation.

Hé Bingyu, co-chief analyst of China Securities (600918), told reporters that the panic trading will likely last about one quarter. He explained that it takes at least one quarter for the panic at the start of the year to be validated by financial data. If the latest quarterly reports show no deterioration, panic sentiment will weaken significantly. After a quarter of adjustment, most panic positions will have been cleared, reducing the likelihood of large-scale sell-offs. However, he warned that if operational or financial data turn negative, the adjustment period could extend.

Zhang Lin, chief of the Communications Industry at Industrial Securities’ Institute of Economics and Finance, shared a similar view, expecting the correction to last 1–2 quarters until the new quarterly reports provide a basic test of fundamentals. He noted that sector differentiation will become clear with the release of earnings: companies that demonstrate AI-driven cost optimization or improve service efficiency and ARPU (average revenue per user) through “human-machine collaboration” will lead the valuation recovery; those slower to adapt will see a longer valuation restructuring process. The true sign of stabilization will be when leading companies confirm that AI technology does not erode core profit margins but instead becomes a new growth engine.

Wu Mingyuan provided a more detailed timeline: in the short term, the next 1–3 months will see increased volatility, with indiscriminate selling and rebounds intertwined. Any breakthrough in AI technology or downward revisions in earnings guidance could trigger a new round of sell-offs. In the medium term, 3–12 months, fundamentals will be tested, and differentiation will intensify. The second half of 2026 will be a critical point—if layoffs in the software industry occur earlier, panic will intensify. Long-term, 1–3 years, a new order will be established, with SaaS (Software as a Service) shifting toward a “usage + results” hybrid model, and platform companies with native AI capabilities will emerge.

Some institutions are relatively optimistic. Yang Cheng believes panic is gradually easing, and the market will enter a phase of “seeking truth from facts.” Liu Yang, deputy general manager of Shenwan Hongyuan Research, and Huang Zhonghuang, chief analyst of computers, said that based on the global risk appetite changes in February, the market correction has entered its latter stage, and we are currently in a phase of calming pessimism.