Zoominfo实测：程序员用Copilot编码效率提升，接受率超三成。
Experience with GitHub Copilot for Developer Productivity at Zoominfo
- 分四阶段部署，覆盖400+开发者，结合定量与定性评估。
- 建议采纳率33%，代码生成采纳率20%，满意度达72分。
- 揭示语言差异与局限，适合企业推进AI编程的参考。
本文系统评估了GitHub Copilot在Zoominfo（一家领先的市场拓展情报平台）中的部署与对开发人员生产力的影响。我们采用四阶段方法，在超过400名开发人员中实施并评估该工具，结合建议采纳率等量化指标与开发者满意度调查等质性反馈。结果显示，建议平均采纳率为33%，代码行生成采纳率为20%，开发者满意度高达72分。同时讨论了不同编程语言的表现差异、使用限制及企业级落地的经验教训。研究为人工智能辅助软件开发在企业环境中的应用提供了实证支持。
原文摘要 · Abstract (English)
This paper presents a comprehensive evaluation of GitHub Copilot's deployment and impact on developer productivity at Zoominfo, a leading Go-To-Market (GTM) Intelligence Platform. We describe our systematic four-phase approach to evaluating and deploying GitHub Copilot across our engineering organization, involving over 400 developers. Our analysis combines both quantitative metrics, focusing on acceptance rates of suggestions given by GitHub Copilot and qualitative feedback given by developers through developer satisfaction surveys. The results show an average acceptance rate of 33% for suggestions and 20% for lines of code, with high developer satisfaction scores of 72%. We also discuss language-specific performance variations, limitations, and lessons learned from this medium-scale enterprise deployment. Our findings contribute to the growing body of knowledge about AI-assisted software development in enterprise settings.
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