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The AI Impact Dashboard for Copilot is available to all cloud customers as a Public Beta feature. You can provide us feedback here.
The AI Impact Dashboard provides insight into Copilot adoption and engagement across your engineering teams, including visualizations for:
  • Impact by team AI adoption rate
    • Correlate team adoption rate to delivery and reliability metrics. Adoption rates are provided daily by comparing active users against Copilot seats.
  • Impact of Copilot users vs. non-Copilot users
    • Compare delivery and reliability side-by-side between users who leveraged AI tools within the last 7 days, and those who did not. Understand whether recent AI usage affects engineering performance.
  • AI adoption trends
    • View the overall trends for AI adoption across your organization.
Use these insights to identify issues and drive continuous improvement. One of the AI Impact charts shows merged PR metrics for AI users vs. non-AI users.

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Using the AI Impact Dashboard

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Prerequisites

Before getting started:
  • You must have GitHub integration configured. See instructions below for each integration method:
    • Cortex GitHub app
    • Custom GitHub App
      • Add the following permission to your custom GitHub App: admin:org read
    • Personal Access Token
      • Add the following permission to your PAT: admin:org read
  • In Cortex, you must have the View Eng Intelligence permission to view the dashboard, and you must have the Configure Eng Intelligence permission to configure it.

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View the Dashboard

Navigate to Eng Intelligence > Dashboards to see the full list of Cortex-built and Custom Dashboards available in your workspace. Click the Copilot Dashboard. This Dashboard contains multiple charts that you can filter and compare with key engineering metrics:
View the impact that a team’s AI adoption rate has on their cycle time, deployment frequency, incident frequency, merged PRs, PR size, time to resolution, and work items completed.Hover over the data in the graph to see more information about a team and its metrics:Hover over the Team AI adoption rate chart to learn more about a metric point.Eng Intelligence compares active users against Copilot seats once daily.
See the impact that using AI, or not using AI, has on cycle time, merged PRs, PR size, time to resolution, and work items completed. Cortex automatically creates an “AI Usage” user label that is attached to any team member who was active in Copilot within the last 7 days.Hover over the data in the graph to see more information about the metrics:Hover over the chart to learn more about a metric point.
View your overall Copilot adoption metrics over time:See Copilot adoption metrics in the graph.

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Filter and configure the Dashboard

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Overlay a data point

To overlay a data point, click the dropdown in the upper left corner of a chart: Click the dropdown in the upper left to choose a data point.

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Filter the chart

You can filter at two levels:
  • Dashboard level - Click Filter at the top of the dashboard to apply a filter across all charts at once. The Copilot dashboard supports Domain and Team as dashboard-level filters.
  • Chart level - Click Filter in the upper-right corner of an individual chart to apply filters for group, owner, repository, user label, and more. Chart-level filters override dashboard-level filters for that chart.

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Driving continuous improvement

Use the AI Impact Dashboard to track and correlate key AI adoption metrics with engineering performance metrics. These insights allow you to identify issues in your processes, which enables the ability to take action and drive improvements. Example scenario: You view your dashboard and notice that teams who have higher rates of AI adoption have a lower average cycle time (the time it takes for a single PR to go through the entire coding process). However, you also see a spike in incident frequency for those teams.
  • Identify the issue: You conclude that their process is more efficient, but as a tradeoff, they’re shipping code that causes more incidents. You brainstorm with the affected engineering teams to learn how their processes have changed since adopting AI. You learn that SonarQube code coverage is lower than it has been previously.
  • Take action: You already have an AI Readiness Scorecard launched, and you see that the rule “Test coverage minimum met” is failing. You can create an Initiative on that Scorecard to ask developers to meet a particular rule by a specified deadline. In this case, you create an Initiative that asks the developers to pass the failing rule (i.e., they need to ensure higher than 80% test coverage) by the end of the month.
    • Initiatives and Scorecard tasks appear as to-do items on a developer’s homepage in Cortex.
  • Review the dashboard: As developers work toward meeting the requirements, check back in on the dashboard for a real-time update into their progress.
Last modified on September 29, 2026