A viral research note on AI gets its economics wrong
The Economist
February 25, 2026
AI-Generated Deep Dive Summary
A research note by Citrini Research claiming that artificial intelligence (AI) could render significant portions of white-collar work obsolete by 2028 has gone viral but has been criticized for flawed economic reasoning. The note envisions a future where major companies like American Express, DoorDash, and parts of the software industry are heavily disrupted or even made redundant due to AI's capabilities. However, experts argue that the economic analysis in the note is oversimplified and fails to account for key factors such as the cost of job displacement, the pace of technological adoption, and the potential for new industries to emerge.
The note paints a dramatic picture of a world where AI automation reshapes the business landscape, eliminating millions of jobs and fundamentally altering the nature of work. While it is true that AI could displace certain roles, particularly in sectors like customer service, data analysis, and software development, the economic impact of such widespread disruption would not happen overnight. The note also overlooks the fact that companies often invest heavily in new technologies to improve efficiency rather than eliminate entire industries.
Critics point out that the note's economic assumptions are overly simplistic, as it does not consider the potential for retraining workers, the creation of new job categories, or the gradual nature of technological change. Additionally, the note's framing of AI as a "silver bullet" solution to business problems ignores the reality that many companies will need to carefully weigh the costs and benefits of adopting AI technologies.
For businesses and investors, understanding the limitations of such speculative analyses is crucial. While AI undoubtedly holds transformative potential, it is not a guaranteed path to obsolescence or success. Instead, organizations should focus on strategic planning, investing in adaptive workforces, and exploring how
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Originally published on The Economist on 2/25/2026