Rolling out a powerful AI tool like GitHub Copilot is a big win for any engineering leader. But because it’s such a significant investment, leadership will inevitably ask if it was worth the cost. Until now, answering this was nearly impossible. While GitHub provides adoption stats, connecting that data to real-world performance metrics like cycle time or code quality has been a manual, frustrating process.
We built the Cortex AI Impact Dashboard to provide a clear answer. By integrating directly with GitHub Copilot, we combine adoption metrics to engineering performance, giving leaders insights that help maximize the value of AI.
A closer look at our new AI Impact Dashboard
The dashboard is designed to give you concrete evidence of your AI investment's value, moving beyond simple adoption stats to show you the real-world impact on performance. It provides views that answer the most critical questions at every level, from the overall organizational trends down to individual developer impact.
Correlate adoption with performance
At the highest level, a scatter plot shows the direct relationship between a team’s Copilot adoption and its performance. See at a glance if teams with higher adoption rates also have shorter cycle times or higher deployment frequencies. The trend line makes the correlation clear, and you can toggle between any core DORA or velocity metric to get a complete picture.
Compare user cohorts
This dashboard provides a clear comparison between active Copilot users and non-users. This cohort analysis allows you to see if active users have a consistently lower cycle time or a higher number of merges than their peers, providing definitive proof of productivity gains.
Drive adoption and measure what matters
The dashboard is powered by two new metrics, Active Copilot Users and Adoption Rate. You can use these metrics in your Scorecards to set clear standards for AI adoption across your organization. This closes the loop, allowing you to drive an initiative with Scorecards and then immediately measure its impact on performance in the dashboard.
Go deeper with custom analysis
The AI Impact Dashboard is more than a report, it’s part of a continuous improvement loop. Teams can:
Set goals with Scorecards
Track progress in the dashboard
Iterate and improve using Metrics Explorer for deeper analysis
Metrics Explorer now has a new, automatic CoPilot usage user label. This lets you filter or group any metric by Copilot activity, allowing for endless custom analysis to answer the specific questions that matter to your organization.
Ready to see the real impact of your Copilot investment? Learn more and schedule a demo of Cortex today.
