Adoption of Large Language Models in Scrum Management: Insights from Brazilian Practitioners

TL;DR

This study empirically examines how Brazilian Scrum practitioners use Large Language Models for management tasks, highlighting benefits like productivity gains and risks such as confidentiality issues and hallucinations.

Contribution

It provides one of the first empirical analyses of LLM adoption in Scrum management, detailing current practices, benefits, risks, and future directions.

Findings

High proficiency and frequent use of LLMs among practitioners

Benefits include increased productivity and reduced manual effort

Risks involve output inaccuracies, confidentiality, and hallucinations

Abstract

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.