Harvard study: AI coding boosts output 30%, but code review becomes the bottleneck
A paper by Harvard researchers Fiona Chen and James Stratton found developers produced about 30% more code with AI, with commits up roughly 20% and pull requests up about 23%, yet completed software showed no statistically significant improvement. Time spent reviewing and merging pull requests rose about 49%, reviewer comments per pull request about 35% and the share of employees doing reviews about 14%, with average review time stretching from 7.03 to 10.48 days. The authors conclude that AI-generated code needs more corrections and that productivity gains are absorbed by downstream constraints, making code review the bottleneck.
It shows AI coding gains don't automatically translate into shipped software, pushing teams to invest in review capacity and process fixes.