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0How AI will divide the best from the rest
Tech bosses say the tech will be a great equaliser. Instead, it looks likely to widen social divides
Feb 13, 2025, The Economist
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At a summit in Paris on February 10th and 11th, tech bosses vied to issue the most grandiose claim about artificial intelligence. “AI will be the most profound shift of our lifetimes,” is how Sundar Pichai, Alphabet’s boss, put it. Dario Amodei, chief executive of Anthropic, said that it would lead to the “largest change to the global labour market in human history”. In a blog post, Sam Altman of OpenAI wrote that “In a decade perhaps everyone on earth will be capable of accomplishing more than the most impactful person can today.”
Mr Altman’s prediction taps into an established school of thought. As large language models first gained popularity in the early 2020s, economists and bosses were hopeful that they, and other AI tools, would level the playing field, with lower-skilled workers benefiting most. Software capable of handling tasks such as protein-folding and poetry-writing would surely democratise opportunity. Jensen Huang, chief executive of Nvidia, a chip designer, envisioned a future in which workers “are all going to be CEOs of AI agents”.
More recent findings have cast doubt on this vision, however. They instead suggest a future in which high-flyers fly still higher—and the rest are left behind. In complex tasks such as research and management, new evidence indicates that high performers are best positioned to work with AI (see table).
Evaluating the output of models requires expertise and good judgment. Rather than narrowing disparities, AI is likely to widen workforce divides, much like past technological revolutions.
The case for AI as an equaliser was supported by research showing that the tech enhances output most for less experienced workers. A study in 2023 by Erik Brynjolfsson of Stanford University and Danielle Li and Lindsey Raymond of the Massachusetts Institute of Technology (MIT) found that generative-AI tools boosted productivity by 34% for novice customer-support workers, helping them resolve queries faster and more effectively. Experienced workers, by contrast, saw little benefit, as the AI reinforced approaches they were already using. This suggested the tech could narrow gaps by transferring best practices from talented to less talented employees.
A similar trend was observed in other knowledge-intensive tasks. Research by Shakked Noy and Whitney Zhang, both of MIT, found that weaker writers experienced the greatest improvements in the quality of their work when using OpenAI’s ChatGPT to draft materials such as press releases and reports. Many saw better quality simply by using the AI’s unedited output, underscoring its ability to elevate baseline performance. Similarly, Jonathan Choi of the University of Southern California and co-authors found a general-purpose AI tool improved the quality of legal work, such as drafting contracts, most notably for the least talented law students.
The problem is that this is swamped by another effect. A job can be considered as a bundle of tasks, which tech may either commoditise or assist with. For air-traffic controllers, tech is an augmentation: it processes flight data while leaving decisions to humans, keeping wages high. By contrast, self-check-out systems simplify cashiers’ roles, automating tasks such as calculating change. This lowers the skill requirement, causing wages to stagnate.
Thus despite the early optimism, customer-service agents and other low-skilled workers may face a future akin to cashiers. Their repetitive tasks are susceptible to automation. Amit Zavery of ServiceNow, a business-software company, estimates that more than 85% of customer-service cases for some clients no longer require human involvement. As AI advances, this figure will probably rise, leaving fewer agents to handle only the most complex cases. Although AI may at first boost productivity, its long-term impact will be to commoditise skills and automate tasks.
