Code review was already a bottleneck before AI tools arrived. CodeRabbit's analysis of 13 million PRs found that AI-coauthored PRs have 1.7x more issues per review than purely human PRs. PR size is up 154%. Reviews are taking longer, not shorter, because AI generates more code faster than reviewers can absorb it.
The standard code review checklist was designed for human-authored code. It doesn't account for AI-specific failure modes: hallucinated function calls that look plausible but don't exist, security patterns that pass syntax checks but fail semantically (XSS fails 86% of the time in OWASP tests of AI code), and logic that is syntactically correct but doesn't match the stated intent.
GitIntel augments the review process by flagging AI-generated segments before the reviewer sees them. This lets reviewers apply appropriate scrutiny — deeper verification on AI-generated sections, lighter-touch review on human-authored code they can attribute to a known author. It also surfaces the AI tool that generated each segment, since different tools have different known failure patterns.
The result: review time drops because reviewers know where to focus, not because they're skipping steps.