Does better work always mean better workers?

Judgment is what sets senior professionals apart from their junior peers. Building judgment requires thousands of hours learning on the job, usually through tedious but formative engagement with relatively routine work, often under guided supervision by experienced workers. But AI is already changing how on-the-job learning works. On the one hand, empirical studies in radiology, business problem-solving, job-seeker writing, and legal education show that when AI tools are thoughtfully embedded into training workflows, less-experienced workers can improve their independent performance.

On the other hand, recent experiments with software engineers, management consultants, high school students, and clinicians demonstrate that while AI serves as a temporary exoskeleton that boosts immediate output, those gains often fail to persist once the tool is removed. Understanding how AI can erode or enhance expertise requires three elements rarely found together: (1) sustained AI usage embedded in ordinary professional work over months rather than hours, (2) a credible evaluation of unassisted judgment when AI is unavailable, and (3) blinded grading by domain experts.

Better work with AI

When AI is removed

When the AI assistant was removed for the 90-day redlining task, the leveling effect vanished. Lawyers given AI tool access outperformed controls by 0.32 SD on this unassisted task (a 9-point equivalent climb in percentile rankings), but this effect was driven entirely by senior lawyers, who outperformed control subjects by 0.45 SD (a 13-point climb), while juniors showed no discernible improvement. Instead, scores of juniors bifurcated: more very low scores, fewer mediocre ones, more good ones, and no more excellent ones.