Open-source software (OSS) is foundational to modern digital infrastructure, yet this context for group work continues to struggle to ensure sufficient contributions in many critical cases. This literature review explores how artificial intelligence (AI) is being leveraged to address critical challenges to OSS sustainability, including maintaining contributor engagement, securing funding, ensuring code quality and security, fostering healthy community dynamics, and preventing project abandonment. Synthesizing recent interdisciplinary research, the paper identifies key applications of AI in this domain, including automated bug triaging, system maintenance, contributor onboarding and mentorship, community health analytics, vulnerability detection, and task automation. The review also examines the limitations and ethical concerns that arise from applying AI in OSS contexts, including data availability, bias and fairness, transparency, risks of misuse, and the preservation of human-centered values in collaborative development. By framing AI not as a replacement but as a tool to augment human infrastructure, this study highlights both the promise and pitfalls of AI-driven interventions. It concludes by identifying critical research gaps and proposing future directions at the intersection of AI, sustainability, and OSS, aiming to support more resilient and equitable open-source ecosystems.

翻译：开源软件（OSS）是现代数字基础设施的基石，然而这种群体协作模式在许多关键场景中仍难以确保足够的贡献。本文献综述探讨了如何利用人工智能（AI）应对开源软件可持续性面临的核心挑战，包括维持贡献者参与度、保障资金支持、确保代码质量与安全性、培育健康的社区生态以及防止项目废弃。通过综合近期的跨学科研究，本文梳理了人工智能在该领域的关键应用，涵盖自动缺陷分诊、系统维护、贡献者引导与培养、社区健康度分析、漏洞检测及任务自动化等方面。同时，综述也审视了在开源场景中应用人工智能存在的局限性与伦理问题，包括数据可获取性、偏见与公平性、透明度、滥用风险，以及在协作开发中如何保持以人为本的价值观。本研究将人工智能定位为增强人类基础设施的工具而非替代品，从而揭示了人工智能干预措施的双重性——既蕴含潜力亦存在隐患。最后，通过指出关键研究空白并提出人工智能、可持续性与开源软件交叉领域的未来方向，旨在为构建更具韧性且公平的开源生态系统提供支持。