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 U.S. stock market. By February, the “AI disruption theory” took over market sentiment, triggering panic trading among U.S. stocks.

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 “resilient to AI shocks.” Is this sell-off merely emotional venting or a rational warning? How long will this adjustment last? These questions are closely watched by 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, U.S. legal software and data services 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 heavily concentrated in software, such as Ares and KKR, 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 decline in U.S. wealth management stocks; on the 11th, panic extended to the U.S. 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 sell-offs among U.S. investors.

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 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, noted that 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 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’s 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 narrative factors.

Market “Overreaction”

Regarding the recent panic selling in U.S. stocks driven by AI fears, most interviewed institutions agree that the market is “overreacting,” with confusion over 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 short-term impacts 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 optimization, pushing industries toward higher-end upgrades.

Wu Mingyuan, chief analyst at Chuangye Securities for computing, 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 warnings about “black swan” events are not unfounded. First, the 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 patterns. His judgment is based on two facts: real-world cases of agents (AI systems) being implemented, and the foundational shake-up of traditional business models.

Ping An Technology Innovation Hybrid Fund manager Zhai Sen also sees 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 U.S. stocks in February will continue. Many institutions believe that while the correction is not over, the extreme phase is passing, and the market will enter a period of digestion and validation.

He Bangyu, co-chief analyst of the Computer Sector at Zhongtai Securities, told reporters that the panic trading might 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 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 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 new quarterly reports test the fundamentals. He noted that sector differentiation will become clear with earnings disclosures: companies that demonstrate AI-driven cost optimization or improve service efficiency and ARPU (average revenue per user) through “human-machine collaboration” will recover valuations first; those slower to adapt will take longer. The true signal of stabilization will be when leading companies confirm that AI 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 round 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, panic will escalate. 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 emerging.

Some institutions are relatively optimistic. Yang Cheng believes that panic sentiment is gradually easing, and the market will move into a phase of “distinguishing true from false.” Liu Yang, vice general manager of Shenwan Hongyuan Research, and Huang Zhonghuang, chief analyst of the computer sector, stated 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.

(Article source: Securities Times)