Generative AI (GenAI) is rapidly reshaping software development workflows. While prior studies emphasize productivity gains, the adoption of GenAI also introduces new pressures that may harm developers' well-being. In this paper, we investigate the relationship between the adoption of GenAI and developers' burnout. We utilized the Job Demands--Resources (JD--R) model as the analytic lens in our empirical study. We employed a concurrent embedded mixed-methods research design, integrating quantitative and qualitative evidence. We first surveyed 442 developers across diverse organizations, roles, and levels of experience. We then employed Partial Least Squares--Structural Equation Modeling (PLS-SEM) and regression to model the relationships among job demands, job resources, and burnout, complemented by a qualitative analysis of open-ended responses to contextualize the quantitative findings. Our results show that GenAI adoption heightens burnout by increasing job demands, while job resources and positive perceptions of GenAI mitigate these effects, reframing adoption as an opportunity.

翻译：生成式人工智能（GenAI）正在迅速重塑软件开发工作流程。尽管已有研究强调其带来的生产力提升，但GenAI的采纳也引入了可能损害开发者福祉的新压力。本文探讨了GenAI采纳与开发者职业倦怠之间的关系。我们采用工作需求-资源（JD-R）模型作为实证研究的分析框架，并运用了嵌入式并行混合研究方法，整合了定量与定性证据。我们首先调查了来自不同组织、岗位和经验水平的442名开发者，随后采用偏最小二乘结构方程模型（PLS-SEM）与回归分析建模了工作需求、工作资源与职业倦怠之间的关系，并通过对开放式回答的定性分析来阐释定量研究发现。研究结果表明：GenAI采纳通过增加工作需求加剧了职业倦怠，而工作资源及对GenAI的积极认知能够缓解这种影响，从而将技术采纳重新定义为发展机遇。