Welcome to the latest issue of Engineering Enablement, a weekly newsletter sharing research and perspectives on developer productivity.
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Social media and vendor marketing have set high expectations for AI, suggesting as much as 2-3x productivity gains. But from the data weâre seeing, the reality on the ground is far more modest.
At DX, weâre currently conducting a longitudinal study to measure the long-term impact of AI adoption on key engineering productivity metrics. As part of this study, we analyzed data from 40 companies between November 2024 through February 2026 to track whether teams are shipping more pull requests as AI adoption increases.
We found that, during this time, AI usage increased significantlyâby an average 65%. However, PR throughput only increased by 9.97%.
Note: This figure is particularly robust because weâve filtered out potential gamification effects by excluding teams that set PR throughput targets for individual engineers, which could drive metric inflation rather than genuine output.
What this means for leaders
A ~10% gain is consistent with what weâre hearing from engineering leaders more broadly: most organizations are landing in the 8â12% range. It is a real improvement, but itâs a long way from the 2â3x gains many executives and boards have come to expect. AI is moving the needle, but leaders may need to reset expectations internally.
Why gains arenât higher
To understand whatâs driving this, we spoke with developers across several of these organizations. The explanation we heard most consistently: writing code was never the bottleneck.
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