Not Faster, but Better: Generative AI and Teacher Skill in Peru

Carla Z. Glave, Carolina Lopez, Ezequiel Molina and Román Andrés Zárate

No 11476, Policy Research Working Paper Series from The World Bank

Abstract: Generative AI is being deployed across the public sectors of developing countries on the premise that it makes workers faster. This paper tests this in a randomized trial with 1,269 sixth-grade teachers across 390 public schools in Lima, Peru. A low-cost program—a one-day training, an AI license, and eight months of light-touch follow-up—raised adoption sharply yet saved teachers no time on any of their core tasks, with precisely estimated nulls throughout. The gains lay elsewhere: treated teachers wrote markedly better prompts, including on a rubric designed independently of the training, and were sharper at catching weak AI outputs. These gains were largest for older teachers, who began furthest behind, narrowing rather than widening skill gaps. Taken together, the results indicate that AI training primarily develops the skills needed to generate and evaluate high-quality AI outputs, rather than reducing the time teachers spend on their work.

Date: 2026-10-01
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