Developer Productivity With and Without GitHub Copilot: A Longitudinal Mixed-Methods Case Study
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Abstract (arXiv)
This study investigates the real-world impact of the generative AI (GenAI) tool GitHub Copilot on developer activity and perceived productivity. We conducted a mixed-methods case study in NAV IT, a large public sector agile organization. We analyzed 26,317 unique non-merge commits from 703 of NAV IT's GitHub repositories over a two-year period, focusing on commit-based activity metrics from 25 Copilot users and 14 non-users. The analysis was complemented by survey responses on their roles and perceived productivity, as well as 13 interviews. Our analysis of activity metrics revealed that individuals who used Copilot were consistently more active than non-users, even prior to Copilot's introduction. We did not find any statistically significant changes in commit-based activity for Copilot users after they adopted the tool, although minor increases were observed. This suggests a discrepancy between changes in commit-based metrics and the subjective experience of productivity.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Sep 2025.
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Citing papers per year: 2025: 1; 2026: 4.
5 papers.
- 2025Speed at the Cost of Quality: How Cursor AI Increases Short-Term Velocity and Long-Term Complexity in Open-Source Projectscited by 24
- 2026Agentic AI in Industry: Adoption Level and Deployment Barrierscited by 4
- 2026The State of Generative AI in Software Development: Insights from Literature and a Developer Surveycited by 2
- 2026Adoption and Impact of Command-Line AI Coding Agents: A Study of Microsoft's Early 2026 Rollout of Claude Code and GitHub Copilot CLIcited by 1
- 2026Obey, Diverge, Collapse: Blind Obedience to Incorrect Instructions Drives Code LLMs to Irrecoverable Code Semantic Collapsecited by 1
- 2026Obey, Diverge, Collapse: Blind Obedience to Incorrect Instructions Drives Code LLMs to Irrecoverable Code Semantic Collapse5 Jul 2026
- 2026Adoption and Impact of Command-Line AI Coding Agents: A Study of Microsoft's Early 2026 Rollout of Claude Code and GitHub Copilot CLI1 Jul 2026
- 2026Agentic AI in Industry: Adoption Level and Deployment Barriers14 May 2026
- 2026The State of Generative AI in Software Development: Insights from Literature and a Developer Survey17 Mar 2026
- 2025Speed at the Cost of Quality: How Cursor AI Increases Short-Term Velocity and Long-Term Complexity in Open-Source Projects6 Nov 2025