Measure and demonstrate the impact of GitHub Copilot

Understanding how Copilot is used across your enterprise is the first step to demonstrating its value. Follow this path to establish a usage baseline, see how code is being generated, and connect adoption to measurable outcomes.

  1. Phase 1: Choose metrics to monitor Copilot adoption.

    2 Articles

    Understand what Copilot usage metrics measure and where the data comes from before you start monitoring adoption. Use the reference articles for metric definitions, methodology, and schemas.

    1. GitHub Copilot usage metrics
    2. Data available in Copilot usage metrics

  2. Phase 2: Monitor usage and adoption

    5 Articles

    Establish a usage baseline, compare active users with assigned licenses, and identify where teams may need more support to adopt Copilot.

    1. Viewing the Copilot usage metrics dashboard
    2. Tracking license activation and initial usage with Copilot usage metrics
    3. Interpreting usage and adoption metrics for GitHub Copilot
    4. Reconciling Copilot usage metrics across dashboards, APIs, and reports
    5. Team-level Copilot usage metrics

  3. Phase 3: See how code is generated

    2 Articles

    Review code generation and Lines of Code metrics to understand how people and agents are using Copilot to produce code.

    1. Viewing the code generation dashboard
    2. Lines of Code metrics

  4. Phase 4: Connect adoption insights to engineering outcomes

    2 Articles

    Compare outcome measures with Copilot usage and adoption trends to assess progress toward engineering goals such as improving test coverage or reducing security debt.

    1. Achieving your company's engineering goals with GitHub Copilot
    2. Viewing the Copilot impact dashboard