Compare Copilot Code Reviews on the Same Basis

GitHub’s 5 November 2026 update adds Copilot code-review outcome fields to enterprise and organization usage reports. A fair comparison starts with understanding the work included in each measure.

GitHub counts a comment as addressed when a developer acts on it, including a reply promising a fix in a later pull request. That definition matters when judging realized benefit.

Make the comparison decision-ready

The diagram shows why the two measures answer different questions. Neither should be presented as a universal percentage of defects fixed. A lack of later change requests also leaves open whether a person reviewed the work at all.

Before using a dashboard to justify expanding an AI review tool, ask for a small comparison record:

• The work included. Identify the repositories, merge dates and share of bot-opened work. Where possible, compare similar change sizes and risk levels. Record differences that cannot be controlled.
• The meaning of an action. Sample addressed comments and trace them to code changes, relevant tests or separately tracked follow-up. Keep deferred work visible when describing benefits already realized.
• The outcome that matters. Pair engagement with independently collected evidence such as human review effort or subsequent rework. Choose the outcome before comparing configurations, and retain examples that explain unexpected results.

For example, moving more proposed changes to bot-opened pull requests could change the work represented in the addressed-rate calculation. An apparent movement in the rate would then deserve investigation before being attributed to better or worse review quality.

For an Independent Technical Assessment, the practical request is simple: show the numerator, denominator, excluded work and representative examples behind a claimed improvement. That creates a fairer basis for evaluating the tool’s contribution without claiming that a dashboard establishes causality.