Artificial intelligence tools are increasingly embedded in everyday work, yet employees' uptake varies widely even within the same organization. Drawing on sociotechnical and work design perspectives, this research examines whether motivational job characteristics and multidimensional AI threat perceptions jointly predict workplace AI adoption and depth of use. Using cross-sectional survey data from 2,257 employees, we tested group differences across role level, years of experience, and region, along with multivariable predictors of AI adoption and use depth, specifically frequency and duration. Across models, job design, especially skill variety and autonomy, showed the most consistent positive associations with AI adoption, whereas threat dimensions exhibited differentiated patterns for depth of use. Perceived changes in work were positively associated with frequency and duration, while status threat showed a negative but not consistently significant relationship with deeper use. Findings are correlational given the cross-sectional and self-report design. Practical implications emphasize aligning AI enablement efforts with work design and monitoring potential workload expansion alongside adoption initiatives.

翻译：人工智能工具日益融入日常工作，然而即使在相同组织内，员工对其接受程度也存在显著差异。本研究基于社会技术系统和工作设计视角，探讨激励性工作特征与多维AI威胁感知是否共同预测职场AI采纳及使用深度。通过对2,257名员工的横断面调查数据分析，我们检验了不同职级、工作年限和地区间的群体差异，以及AI采纳与使用深度（具体表现为使用频率和持续时间）的多变量预测因素。在所有模型中，工作设计（特别是技能多样性和自主性）与AI采纳呈现最稳定的正相关关系，而威胁维度在使用深度方面则表现出差异化模式：感知到的工作变化与使用频率和持续时间呈正相关，地位威胁则与深度使用呈负相关但未达到持续显著性。鉴于横断面和自我报告的研究设计，本文发现仅反映相关关系。实践意义强调应将AI赋能举措与工作设计相结合，并在推进采纳过程中监测潜在的工作量扩张。