Approach or avoidance? Relationship between perceived AI explainability and employee job crafting

• Published in: Acta psychologica Vol. 257; p. 105097
• Main Authors: Huo, Weiwei, Xie, Jiaying, Yan, Jiaqi, Long, Tianyi, Liang, Bingqian
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.07.2025; Elsevier
• Subjects: Adult; Approach job crafting; Artificial Intelligence; Avoidance job crafting; Decision Making; Ethical climate; Female; Humans; Male; Middle Aged; Perceived AI explainability; Surveys and Questionnaires; Work design; Workplace - psychology; Perceived AI explainability; Ethical climate; Approach job crafting; Work design; Avoidance job crafting
• ISSN: 0001-6918; 1873-6297; 1873-6297
• DOI: 10.1016/j.actpsy.2025.105097

Amid growing concerns about the lack of transparency in algorithms, heightened focus has been placed on artificial intelligence (AI) explainability in workplace decision-making processes. This study leverages work design theory to explore when and how perceived AI explainability impacts two types of employee job crafting: approach job crafting and avoidance job crafting. We analysed multi-wave survey data of 278 medical staff to examine the effects of perceived AI explainability on approach and avoidance job crafting through a dual-pathway model. Results indicated that perceived AI explainability enhanced AI-oriented benefit perception and reduced AI-oriented threat perception, resulting in an increase in approach and avoidance job crafting. Furthermore, our findings suggested that ethical climate strengthened the impacts of perceived AI explainability on AI-oriented benefit perception and AI-oriented threat perception. We discuss key theoretical insights of our findings for advancing AI and job crafting research as well as implications for organisational practice.