A Longitudinal Study of AI Adoption in an Enterprise
A longitudinal study of an enterprise '2x mandate' to double merged pull requests per engineer found that throughput eventually reached 2.09x the pre-mandate baseline, with gains linked to AI adoption and usage intensity. Code review was restructured, with automated review overtaking human review and reviewer load doubling.
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[Submitted on 2 Jul 2026]
Title:AI Writes Faster Than Humans Can Review: A Longitudinal Study of an Enterprise 2x Mandate
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Abstract:Enterprises increasingly mandate AI coding tools and report large productivity gains, yet longitudinal evidence on how such a mandate unfolds is scarce. In this paper, we present a quantitative case study of a documented enterprise "2x" mandate at a mid-sized, AI-forward company that has been committed to doubling merged pull requests per engineer since mid-2025. In a panel of 802 developers and 196,212 pull requests (January 2024-April 2026), per-capita throughput eventually doubled, reaching 2.09x the pre-mandate baseline in April 2026, among the largest gains reported from a field deployment of AI coding tools to our knowledge. A staggered difference-in-differences design links the within-developer share of this gain to AI adoption and to a further gain that grows with accumulated use, with the mandate acting as a catalyst rather than a direct driver. Because adoption and usage intensity were not randomly assigned, we read this evidence as strongly implicating an adoption-and-use channel rather than as exact causal attribution. The gain is broadly shared across seniority yet concentrated in newer code and not separable across model generations. Adoption also restructured code review around automation: per-reviewer load roughly doubled and automated review overtook human review, while merge and revert rates held steady.
Subjects:
Software Engineering (cs.SE)
Cite as: arXiv:2607.01904 [cs.SE]
(or arXiv:2607.01904v1 [cs.SE] for this version)
https://doi.org/10.48550/arXiv.2607.01904
arXiv-issued DOI via DataCite
Submission history
From: Bogdan Vasilescu [view email] [v1] Thu, 2 Jul 2026 09:03:32 UTC (421 KB)
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