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AI Adoption

Measure the AI adoption in your company by seeing how many contributors are actively using AI Coding tools.

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At this time, this feature only integrates with GitHub Copilot. Additional integrations may be available in the future.

See the AI Adoption of your organization in the Health section of the sidebar menu.

In the top right corner of the page, you can see how many GitHub Copilot licenses your organization has and when they were acquired. This data helps track how AI adoption has impacted certain engineering metrics over time.

The graph visualizes these changes, comparing performance before and after AI adoption:

  • The grey area represents metrics before AI adoption.
  • The blue area reflects how the metrics evolved after adopting AI.

Here are the metrics you can see in this graph:

  • Churn: Churn is defined as the proportion of code that has been rewritten or deleted within the first 21 days after its creation. This value is adjustable on the Settings page.
  • Cycle Time: Cycle Time is one of the best measures of an engineering organization’s velocity. It measures the elapsed time from the first commit made to the production release.
  • Coding time: Measures the average amount of time it takes for a contributor to issue a pull request after starting work on a code change or feature.
  • Review time: Measures how fast do submitters incorporate feedback from their peers in code review and is the time from a PR's first review to that PR being merged.

Daily Users

The Daily Users graph shows how much usage the AI copilot has daily. You can track the following metrics:

  • Active users: The active users interacted with the Copilot, but they didn’t necessarily accept its suggestions.
  • Engaged Users: The engaged users interacted with the Copilot, and they accepted at least one of its suggestions.
  • Adoption rate: The percentage of users engaged with the Copilot out of all acquired licenses.
  • Silent users: The percentage of active users who didn't accept any Copilot suggestions from all acquired licenses.

Usage Graph

The usage graph provides insights into the number of code suggestions GitHub Copilot has generated and the number of those that were accepted.

Available Metrics

  • Code suggestions – The total number of code suggestions made by the AI.
  • Code acceptance – The number of accepted AI-generated suggestions.
  • Acceptance rate – The percentage of accepted code suggestions.

Additional Breakdown
You can also filter the graph by:

  • Coding language – Identify which programming languages are used most with AI-generated suggestions.
  • Coding editor – See which code editor has the highest AI-assisted activity.
  • AI model – Analyze which AI model is being used the most.

Updated 1 day ago