AIORG-W034 Peer-reviewed research

The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers

Management Science 2025.00535 · Cui et al. developer field experiments

peer reviewed journal article

Recorded claims
2
coded from the inspected source
Evidence classes
1
scholarly-full-text
Recorded limitations
5
stated, never hidden

From the wave-0 evidence ledger

Recorded claims

Each claim states what the inspected source says, at the recorded location—bounded by its scope and graded by its confidence. Nothing here is a synthesis across works.

Across three field experiments involving 4,867 software developers at Microsoft, Accenture, and an anonymous Fortune 100 company, the preferred instrumental-variable/treatment-on-the-treated estimate for actual coding-assistant use induced by randomized access under imperfect compliance was a 26.08% increase in completed tasks; this is not the randomized-access intention-to-treat effect.

confidence: high within study scholarly-full-text

Scope: Software developers and measured completed tasks in three firms; not all high-skilled work or firm financial performance.

Gains were larger for less-experienced developers, reinforcing an expertise-gradient pattern, but the study does not imply that every experienced developer or mature repository benefits—an important contrast with the METR result in AIORG-C023.

confidence: high for within-study heterogeneity scholarly-full-text

Scope: Three company contexts and their coding workflows; external validity bounded.

Boundaries

Limitations & independence

Recorded at coding time, carried with the work forever. A claim without its limits is not evidence.

Recorded limitations

  • Software-development task family
  • Tool use and outcome logging differ across firms
  • Less-experienced-worker heterogeneity may not transfer to other professions
  • Task completion is not firm profit or software quality over the long run
  • Imperfect compliance means the preferred 26.08% IV/treatment-on-treated estimand is not the randomized-access intention-to-treat effect

Source independence

Academic/vendor-affiliated multi-company field experiments, including Microsoft, Accenture, and a Fortune 100 firm; product and employer involvement disclosed by setting.