Why the White House Economist Had to Step In to Stop a Wall Street AI Meltdown

The usual buzz on the trading floor had given way to a tense quiet by mid-morning on Monday. Minutes before, screens had been green, but now they were glowing red. A dense, dystopian, and surprisingly viral research note was bouncing around hedge fund group threads and chat terminals. Leaning over desks, traders read passages that predicted a “global intelligence crisis” that would cause white-collar jobs to disappear and lead to a deflationary spiral. It read more like speculative fiction than market analysis. But as if it were a piece of scripture, prices were shifting.

James van Geelen, the founder of Citrini Research, published a report that envisioned a near-future economy in which artificial intelligence eliminates entire job categories while increasing productivity. According to the scenario, consumer demand plummets and unemployment rises above 10%, which lowers equity markets. Financial stocks had their worst day in months, software ETFs plummeted, and the S&P 500 had turned around by the opening bell, closing down more than 1 percent. Given tariff concerns and geopolitical commotion, the sell-off might have occurred anyhow, but traders continued to cite the memo as they pressed the sell button.

Experienced observers were surprised by the speed of belief as well as the decline. Investors appear to think AI will completely reorganize industries, but they aren’t sure if this will result in increased profits or widespread displacement. Companies like American Express, DoorDash, and ServiceNow were identified in the report as being at risk of an AI-driven reorganization, and as a result, their stock prices fell. The irony that van Geelen’s phone was constantly ringing with new subscription requests by the afternoon was not lost on anyone observing the chaos.

It didn’t take long for the White House Council of Economic Advisers to react. The scenario was rejected by acting chair Pierre Yared, who claimed that the model defied fundamental economic reasoning and was more akin to science fiction than accounting reality. His subtle but purposeful intervention indicated that the federal government did not believe that AI job displacement would cause an impending macroeconomic collapse. That was important in markets that were desperate for adult supervision. There’s a feeling that investors wanted assurance that a reliable person had done the math, not certainty.

One could sense echoes of past panics as they watched Washington’s response. Fear spread more quickly than balance sheets could be examined during the Silicon Valley Bank collapse in 2023, another incident that van Geelen had warned about months earlier. After all, narrative is just as important to markets as data. Furthermore, the prevailing narrative surrounding artificial intelligence is currently dividing into two incompatible narratives: one about systemic disruption and the other about productivity miracles.

The anxiety was heightened by the timing. After weeks of industry-wide drops in software, insurance brokerage, and cybersecurity companies, AI stocks had already begun to sway. Silicon Valley, meanwhile, is still investing enormous amounts of money in data centers and processing power, frequently with the help of intricate debt arrangements and special purpose vehicles. Critics caution that these arrangements may resemble previous overbuild cycles if demand does not materialize. Whether the infrastructure boom is an example of foresight or overreach is still up for debate.

Even leaders in the industry give conflicting signals. Jensen Huang of Nvidia maintains that the boom is genuine. Policymakers and venture capitalists define an investment super-cycle. However, economists like Daron Acemoglu of MIT warn that productivity increases might come later than the hype implies. The conflict between these points of view permeates every investor conference and earnings call, influencing sentiment in ways that spreadsheets are unable to measure.

Once back at trading desks, the panic dissipated as fast as it had arisen. Markets recovered by Tuesday, and some of the most severely impacted stocks gained ground. The “AI ghost story” that frightened Wall Street for a day was the subject of jokes among traders. Beneath the humor, however, the episode exposed something more delicate: trust in the AI economy is predicated on assumptions that haven’t been thoroughly tested.

The distinction between analysis and narrative contagion has become increasingly blurred. The market’s extreme sensitivity to concerns about AI disruption was revealed in a single report that was intended to spark discussion. Washington’s answer only served to level the playing field; it did not put an end to the discussion. Furthermore, the next shock may not come from a dystopian memo but rather from reality catching up to speculation as artificial intelligence continues to transform work, productivity, and corporate spending.

For the time being, the markets continue to trade, the servers continue to function, and the policymakers continue to count the data, possibly in the hopes that transparency and measurement will prevent belief from turning into panic. The durability of that hope is a different matter.