GitHub Copilot Metrics: Measuring the Impact

The integration of AI tools in software development promises significant productivity gains, yet measuring their actual impact has remained challenging. Based on composite Allstacks customer data, this analysis of engineering teams using GitHub Copilot reveals nuanced patterns in development efficiency and code quality.

What's inside

Real-world examples of Copilot's impact — how engineering teams are quantifying improvements in cycle time, developer productivity, and forecast accuracy.

A data-driven approach to measuring impact — a detailed breakdown of the KPIs organizations should track to measure AI-driven development.

Productivity gains and risk factors — how to use your team's Copilot data to address key challenges, risks, and best practices.