More pessimistic than Citrini: the more advanced AI efficiency becomes in the US, the more the allocation system breaks down.

On February 23, Citrini Research published “The Global Intelligent Crisis of 2028,” a thought experiment projecting an AI-driven surplus of intelligence between 2026 and 2028. The report does not provide direct predictions but instead uses structured scenario analysis to depict a possible negative feedback loop: AI capabilities continue to improve → white-collar jobs are replaced → labor income declines → consumption contracts → corporate profits come under pressure → companies further increase AI investments → larger-scale replacements and layoffs, ultimately affecting private credit, insurance funds, and the high-quality mortgage system.

After the report was released, it triggered a new wave of AI panic trading in the market. U.S. stocks continued to decline, with sectors highlighted in the Citrini report—including food delivery, software, payments, and private credit—dropping sharply. Coupled with Nassim Taleb’s market warnings and statements from AI startup Anthropic, IBM’s stock price plummeted 13% in a single day; DoorDash, American Express, KKR, and Blackstone all fell more than 6%; related software ETFs declined 4.8%, with the cumulative drop from September last year’s high reaching about 35%.

It is worth emphasizing that the report does not offer new insights but systematically consolidates several core issues discussed in the market over the past year: AI replacing white-collar workers, deterioration of SaaS business margins, exposure of private credit leverage, and loosening income assumptions for high-quality mortgages. What truly triggered market panic was the fact that these scenarios are linked into a closed-loop system, with each hypothetical scenario and transmission link showing early signals in reality. This has prolonged the previous AI panic trading sentiment and led to a “shoot first, ask questions later” selling pattern.

The current trading logic has shifted from focusing on “how AI will disrupt corporate profit models” to a more macro question: when labor income continues to decline and consumption shrinks accordingly, who will absorb the ever-expanding output? This is essentially a fundamental challenge to the distribution mechanism and the capacity of the system to bear it.

Increased production efficiency no longer benefits ordinary workers, and asset pricing is being reconstructed