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

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 center stage, triggering panic selling among US equities.

Within just a month, panic spread from the software industry to finance, legal, consulting, commercial real estate, logistics, media, and other sectors, with investors shifting their focus to sectors perceived as “resistant 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 themes have been seen as threats 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 the 10th, Altruist introduced AI tax planning tools, leading to a collective drop in US wealth management stocks; on the 11th, panic extended to the US real estate services sector; and on the 12th, AI logistics company Algorhythm released a white paper claiming AI algorithms could triple productivity, prompting a sell-off in trucking and logistics.

On February 23, Citrini Research published a report titled “Global AI Crisis 2028,” projecting potential chain reactions of economic crises triggered by rapid AI development, reigniting US stock market sell-offs.

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

According to Zhang Jiqiang, head of the Huatai Securities Research Institute, since 2026, the global AI narrative has shifted at least three times: first, the traditional “bigger models, more data, stronger compute power equals better performance” rule has shown 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’s disruptive potential have grown.

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 fragile transaction 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 narrative factors.

Market “Overreaction”

Regarding the recent AI panic in the US stock market, all interviewed institutions agree that the market is “overreacting,” with confusion about “which industries will be disrupted” and “how fast” the disruption will occur. 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 gain competitive advantages.” He also cautioned that current AI architectures still face issues like hallucinations, response delays, and insufficient computing resources, which prevent meeting high-reliability requirements for enterprises. This means new technologies need long-term adaptation from emergence to mature application.

Jiang Jialin, assistant director at the Industrial and Financial Research Institute of Industrial Bank, 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 does not mean destruction. Historical experience shows that initial panic during technological revolutions is often accompanied by opportunities. AI’s impact on industries is gradual, not a sudden wave of bankruptcies; most sectors will adapt and improve efficiency through AI.

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 upgrades, pushing industries toward higher-end development.

Wu Mingyuan, chief analyst of Huachuang Securities’ Computer Sector, offered a different view. He said the current sell-off is a combination of “structural undervaluation” and “excessive emotional reaction,” but the disruptive risk AI poses to traditional industries is indeed underestimated.

Wu believes that Nassim Nicholas Taleb’s warning about “black swan” events is not unfounded. First, tail risks in various industries are structurally underestimated; these risks are not minor corrections but significant retracements. Second, the sustainability of leading AI companies is overestimated; early pioneers are often replaced, based on historical lessons. His judgment is based on two facts: real-world cases of AI agents have emerged, and the foundations of traditional business models are shaking.

Ping An Technology Innovation Hybrid Fund manager Zhai Sen also thinks 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 Will Enter a Phase of Assimilation and Validation

The market’s focus is on whether the AI panic selling in US stocks in February will continue. Many institutions believe that 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 the Computer Sector at Zhongtai Securities, told reporters that panic trading may last about one quarter. He explained that it takes at least one quarter for the initial panic to be validated by financial data; if the latest quarterly reports show no deterioration, panic sentiment will significantly weaken. 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 analyst 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 next earnings season provides a fundamental test. He noted that sector differentiation will become clear as earnings reports are released: 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 reset cycle. 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, volatility will intensify over the next 1–3 months, with indiscriminate selling and rebounds intertwined. Any breakthroughs in AI technology or downward revisions in earnings guidance could trigger another wave of sell-offs. In the medium term, 3–12 months, fundamentals will be tested, and sector differentiation will intensify. The second half of 2026 will be a critical point—if layoffs in the software industry occur earlier than expected, panic will deepen. Long-term, 1–3 years, a new order will be established, with SaaS subscription models shifting toward a “usage-based + results-based” hybrid, and platform companies with native AI capabilities will emerge.

Some institutions remain relatively optimistic. Yang Cheng believes that panic sentiment is gradually easing, and the market is entering a phase of “distinguishing true from false.” Liu Yang, deputy general manager of Shenwan Hongyuan Research, and Huang Zhonghuang, chief analyst of the Computer Sector, stated that based on the change in global risk appetite in February, the market correction has entered its latter stages, and we are now in a phase of calming pessimism.

(Article source: Securities Times)