Twenty-first International Conference on Knowledge, Culture, and Change in Organizations

Abstract

Knowledge work refers to the creative reproduction of idiosyncratic knowledge of white-collar workers. Employees’ work processes, communication with their colleagues, and interaction with ICT constitute important areas of their professional expertise. However, the introduction of learning and autonomous artificial intelligence (AI) systems drastically affects knowledge workers’ tasks and processes. First, AI systems increasingly take over employees’ routine tasks. Second, for non-routine tasks, employees have to share their tasks with these systems, are often unable to influence their work processes, and cannot alter the AI derived decision outcome in the way they used to. Moreover, the transfer of knowledge between employees within and across hierarchies is highly impaired due to the opaqueness of many of these algorithms. As a result, knowledge workers’ ways to acquire knowledge is challenged, their professional expertise is threatened, and they are confronted with inherent tensions between the ICT and their work processes. In order to understand how the implementation of AI systems affects employees’ and organizations’ knowledge work, we qualitatively investigate the introduction of an AI system in the financial industry by using an in-depth case study of a corporate organization using a learning and autonomous AI system for customer relationship management. From a theoretical perspective, we contribute to the understanding of the effect of AI systems on knowledge work and illustrate employees’ attempts to pertain and regain their ability to create, conserve, and reproduce knowledge. From a practical perspective, we highlight organizational challenges in sustaining knowledge and provide recommendations on how to face respective consequences.