Generative AI and Task Redesign: Evidence for Managers and Policymakers

Authors

  • Jason Roberts Author

Keywords:

generative AI, work design, productivity, labor markets, management

Abstract

This evidence review examines generative artificial intelligence and task redesign. The organizing question is which tasks are augmented, displaced, recombined, or newly created when generative tools enter organizations. Ten related scholarly sources are synthesized through a decision-centered framework spanning problem definition, mechanism, measurement, evaluation, implementation, and governance. The review does not invent experiments, pooled estimates, or unreported quantitative results. It instead evaluates the strength and transferability of the available evidence, with particular attention to generalizing short-run experimental productivity gains to whole occupations or long-run welfare. The resulting framework links technical or empirical performance to explicit use conditions and identifies tests that should precede wider adoption in organizational adoption and labor-market policy.

References

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Published

2026-08-05

Issue

Vol. 1 (2026): Archive

Section

Evidence Review

License

Copyright (c) 2026 Markets, Organizations & Public Value

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.