大语言模型在Scrum管理中的应用：来自巴西实践者的洞察
Adoption of Large Language Models in Scrum Management: Insights from Brazilian Practitioners
AI总结：
研究探讨了大语言模型在Scrum管理中的应用，发现其在提升生产率和减少手动工作方面有显著益处，但同时也面临输出准确性和保密性等风险。
摘要：
Scrum因其适应性和协作性而在软件项目管理中被广泛采用。近年来，大型语言模型（LLMs）的出现为支持知识密集型的Scrum实践创造了新的机会。然而，现有研究主要集中在技术活动如编码和测试上，对LLMs在管理相关Scrum活动中的使用证据有限。本研究通过调查70名巴西专业人士，探讨了LLMs在Scrum管理活动中的应用。其中，49人主动使用Scrum，33人报告在Scrum实践中使用基于LLM的助手。结果显示，受访者对LLMs的熟练程度较高，使用频率也较高，85%的受访者报告具有中级或高级熟练程度，52%的人每天使用。LLMs的使用集中在探索Scrum实践上，其中文档和事件获得有针对性但不均衡的支持，而更广泛的管理任务则被更谨慎地采用。主要益处包括生产率提高（78%）和手动工作减少（75%）。然而，仍然存在一些关键风险，受访者报告“几乎正确”的输出（81%）、保密问题（63%）以及使用中的幻觉（59%）。本工作提供了对LLMs在Scrum管理中应用的首次实证描述，识别了当前实践，量化了益处和风险，并概述了在敏捷环境中有责任采用和整合的方向。
英文摘要：
Scrum is widely adopted in software project management due to its adaptability and collaborative nature. The recent emergence of Large Language Models (LLMs) has created new opportunities to support knowledge-intensive Scrum practices. However, existing research has largely focused on technical activities such as coding and testing, with limited evidence on the use of LLMs in management-related Scrum activities. In this study, we investigate the use of LLMs in Scrum management activities through a survey of 70 Brazilian professionals. Among them, 49 actively use Scrum, and 33 reported using LLM-based assistants in their Scrum practices. The results indicate a high level of proficiency and frequent use of LLMs, with 85% of respondents reporting intermediate or advanced proficiency and 52% using them daily. LLM use concentrates on exploring Scrum practices, with artifacts and events receiving targeted yet uneven support, whereas broader management tasks appear to be adopted more cautiously. The main benefits include increased productivity (78%) and reduced manual effort (75%). However, several critical risks remain, as respondents report 'almost correct' outputs (81%), confidentiality concerns (63%), and hallucinations during use (59%). This work provides one of the first empirical characterizations of LLM use in Scrum management, identifying current practices, quantifying benefits and risks, and outlining directions for responsible adoption and integration in Agile environments.
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