Concerns about the impact of artificial intelligence (AI) on individual stocks and sectors have clearly been growing in recent months.
Just one recent example: On Monday, February 23, AI startup Anthropic PBC announced that its Claude Code tool could modernize the COBOL coding language, which is a major asset of International business machines (NYSE: IBM). That sent IBM shares down 13% on the day, its worst single-day loss since 2000.
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But new and bigger concerns are suddenly emerging about the emergence of AI on the market. One is that, by displacing large numbers of white-collar workers, AI could do real damage to the broader U.S. economy in just a couple of years.
Last weekend, investment research firm Citrini Research published a note titled “The Global Intelligence Crisis of 2028” that outlined a possible scenario – two years from now – when AI’s job displacement has pushed the unemployment rate above 10% and aggregate demand in the economy has begun to plummet as people lose income.
If, like me, you read a lot of commentary on investing and macroeconomics, you would have noticed that the Citrini report was the only thing everyone was writing about at the beginning of the week. To be sure, the authors of the research report emphasized that what they described is a scenario, not a prediction, but the report spooked the markets anyway, and the S&P 500 The index fell 1% on Monday.
Could such a scenario become a reality? And how should investors prepare for this contingency?
Well, the gist of Citrini’s scenario is that AI will get better and cheaper in the coming years. That allows companies to lay off workers, and companies use the savings from doing so to further bolster their AI capabilities, allowing them to lay off more workers. Displaced workers spend less. Companies that sell things to consumers sell less and therefore invest more in AI to protect their margins. Etc.
To cite just a small part of the report on what happens in this scenario between the beginning of 2026 and 2028:
AI capabilities improved, companies needed fewer workers, management layoffs increased, displaced workers spent less, margin pressure pushed companies to invest more in AI, AI capabilities improved… It was a negative feedback loop with no natural brake.