Abstract
With the development of artificial intelligence (AI) and its applications, such as learning algorithms, it seems likely that work and organization will be profoundly reshaped. While this subject has been debated in broad terms (Arntz et al., 2016; Brynjolfsson & McAfee, 2014; Faraj et al., 2018), little has been written specifically from the perspective of employees (Phan et al., 2017). Little is known about the impact of AI on their work experiences and how they may respond. In a qualitative study of 27 bank employees, we investigated how learning algorithms shaped working conditions, how they affected autonomy and the meaning of work and how these constructs changed over time. The employees responded to the changes through job crafting behaviours (Wrzesniewski & Dutton, 2001). By considering the effects of the learning algorithms on the employees’ work experiences from their perspective, we offer a novel application of job crafting theory to AI technology. The employees responded to AI by changing task and relationship boundaries, and cognitively reframed their jobs. Their job crafting behaviours can be interpreted broadly as attempts to rebalance their levels of autonomy (which were initially reduced by the introduction of AI), to move toward closer personal relationships with customers and to reposition their meaning of work. In general, employees’ job crafting also had implications for employees’ managers, customers, and their work context in terms of the meaning of the AI tools and how they were used. Employees’ concerted response across the three job crafting dimensions underlines the importance of synergy across job crafting dimensions if they are to be successful in altering employees’ experience of work and enhancing the human value of their services.
Original language | English |
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Number of pages | 20 |
Journal | Relations Industrielles |
Volume | 77 |
Issue number | 3 |
DOIs | |
Publication status | E-pub ahead of print - 30 Nov 2022 |
Keywords
- artificial intelligence
- job redesign
- job crafting
- algorithms
- banking