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Job attitudes and career behaviors relating to employees' perceived incorporation of artificial intelligence in the workplace: a career self-management perspective

心理学 透视图(图形) 感知 独创性 职业生涯管理 职业发展 社会心理学 人力资源管理 应用心理学 工作表现 价值(数学) 工作满意度 公共关系 知识管理 计算机科学 机器学习 人工智能 神经科学 政治学 创造力
作者
Alfred Presbitero,Mendiola Teng‐Calleja
出处
期刊:Personnel Review [Emerald (MCB UP)]
卷期号:52 (4): 1169-1187 被引量:14
标识
DOI:10.1108/pr-02-2021-0103
摘要

Purpose Artificial intelligence (AI) continues to be deployed in workplaces. While there are many positive outcomes of AI integration, understanding the extent of its consequences on employees is limited. Hence, this study examines employee perceptions of AI and the consequent influences on employee job attitudes and career behaviors. Utilizing the career self-management perspective, the authors explore the mechanisms related to employee perceptions of AI and potential career exploration behaviors. Design/methodology/approach The authors tested several hypotheses using employee survey data ( N = 345 call center agents) collected from a firm that recently integrated AI in their operations. The authors collected data on four occasions (one-week intervals between data collection) to determine employee perceptions of AI taking over jobs (Time 1); job insecurity (Time 2); psychological distress (Time 3); and career exploration behavior (Time 4). Findings The findings reveal that perceptions of AI taking over jobs are significantly associated with higher career exploration behaviors. In addition, the authors found job insecurity and psychological distress as pathways that explain why employees having perceptions of AI taking over their jobs influences their career exploration behaviors. Originality/value These findings fill a gap in the literature by revealing how AI integration in the workplace, despite its many positive outcomes for organizations, can have a negative influence on employees. The negative employee perceptions of AI can lead to career exploration behaviors. From the career self-management perspective, the authors offer novel insights that have practical implications for talent management, particularly the need to communicate effectively to employees about AI integration in the workplace to avoid them feeling threatened and leaving their jobs.
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