AI Code Review Overhead measures the additional review time and effort required when evaluating AI-generated code compared to human-written code. Reviewers may need to more carefully verify logic, check for subtle bugs, and ensure adherence to architectural patterns when code originates from AI tools. Tracking this metric reveals whether AI-assisted development is truly reducing overall cycle time or merely shifting effort from writing to reviewing.
Increase in review time per PR. High AI adoption correlates with +91% longer review cycles and +154% larger PRs.
91% increase in review time with high AI adoption. 154% larger PRs from AI batching. At scale, reviewer bandwidth is already scarce — AI amplifies the bottleneck.
+91% review time directly increases lead time. Review becomes the bottleneck.
154% larger PRs from AI batching. AI enables generating more code faster, leading to bigger PRs.
Reviewers overwhelmed by large AI-generated PRs requiring architectural scrutiny.