Automation of information-processing tasks reduces returns to analytical skills while raising returns to social and manual skills

str 8 12/31/2099 · 1 article

structural · economic · AI, labor · US

Analysis

LLM automation, which targets information-processing and analytical tasks, structurally shifts the relative value of different skill types in the labor market. Workers with high analytical skills—concentrated at the top of the wage distribution—face declining returns, while those with social and non-routine manual skills see rising returns, creating a mildly progressive distributional effect.

Key actors

workersskill types

Source article

FM_AI

pdf-archive — Work, Skills and Society · — · extracted in run pdf-import-undated-1779224753682-107 · 5/19/2026, 10:48:14 PM

"AI raises the return to social and non-routine manual skills, while reducing the return to analytical skills." [return to analytical skills]

This directly names the structural shift in skill returns caused by LLM automation, showing which skills gain and lose value as a result of the shock.

Reasoning from this article

The article demonstrates this through both historical validation (RBTC analysis) and forward-looking projections. The mechanism is job transformation: as analytical tasks are automated, occupations reweight toward social and manual tasks, raising their relative importance. Because analytical skills are concentrated at the top of the wage distribution and social/manual skills are more equally distributed, this creates a progressive effect. This pattern would apply to any automation technology that disproportionately affects one skill category.