Organization and enterprise administrators can now observe the impact of AI Scan for pull requests in security overview. New metrics show how many AI Scan findings were generated, resolved, the remediation rate, which repositories generated findings, trends over the selected reporting period, and how often developers applied autofix suggestions.
The “CodeQL pull requests” page is now named “Code scanning on pull requests” and includes separate CodeQL and AI Scan tabs. The AI Scan tab shows total findings and how many findings include or do not include an autofix suggestion. Metrics from the “CodeQL pull requests” page are now under the CodeQL tab.
These metrics help security teams evaluate the effectiveness of AI Scan across their organization or enterprise, understand developer response, and make informed rollout and investment decisions without reviewing individual pull requests.
This public preview is available on github.com, including GitHub Enterprise Cloud, for customers with GitHub Code Security or GitHub Advanced Security. GitHub Enterprise Server isn’t supported for this release.
Learn more about AI Scan for pull requests and join the AI Scan Community discussion.