Novice-Expert Asymmetry

The novice-expert asymmetry is one of the most cited and contested findings of the early AI era: that large language models help the least skilled workers most. Erik Brynjolfsson, Danielle Li, and Lindsey Raymond documented the pattern in their 2023 study of 5,179 customer service agents who gained access to an AI assistant on a staggered schedule. Average productivity improved 14 percent. But novice and low-skilled workers improved by 34 percent, while experienced, highly skilled workers saw minimal impact. The mechanism was precise: the AI model appeared to be capturing and spreading the tacit knowledge of the best workers, helping newer employees move down the experience curve faster than any prior training could manage. The finding suggested something hopeful—AI might compress inequality rather than widen it, disseminating expertise that had previously been locked in senior employees. But subsequent evidence complicated the optimism in a way that Brynjolfsson himself has been careful to name: in AI-exposed occupations,