An Empirical Study of GenAI Adoption in Open-Source Game Development: Tools, Tasks, and Developer Challenges
Xiang Echo Chen, Wenhan Zhu, Guoshuai Albert Shi, Michael W. Godfrey

TL;DR
This paper empirically investigates how open-source game developers adopt and integrate generative AI tools, highlighting differences from traditional AI and identifying developer challenges through GitHub issue analysis.
Contribution
It provides the first empirical analysis of GenAI adoption in open-source game development, comparing usage patterns, concerns, and integration practices with traditional AI.
Findings
GenAI is primarily used for content creation and design ideation.
Developers express unique challenges related to GenAI integration.
GenAI adoption differs significantly from traditional AI in open-source projects.
Abstract
The growing capabilities of generative AI (GenAI) have begun to reshape how games are designed and developed, offering new tools for content creation, gameplay simulation, and design ideation. While prior research has explored traditional uses of AI in games, such as controlling agents or generating procedural content. There is limited empirical understanding of how GenAI is adopted by developers in real-world contexts, especially within the open-source community. This study aims to explore how GenAI technologies are discussed, adopted, and integrated into open-source game development by analyzing issue discussions on GitHub. We investigate the tools, tasks, and challenges associated with GenAI by comparing GenAI-related issues to those involving traditional AI (TradAI) and NonAI topics. Our goal is to uncover how GenAI differs from other approaches in terms of usage patterns, developer…
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Taxonomy
TopicsResearch Data Management Practices · Educational Games and Gamification · Big Data and Business Intelligence
