Coping with Artificial Chaos

Sammanfattning

The rapid rise of artificial intelligence (AI) has placed retail organisations at the centre of a transformation that employees are largely left to navigate on their own. This study with the title Coping with Artificial Chaos: How Retail Organisations Make Sense of Disruptive Technological Innovations – A Qualitative Study on the Example of AI examines how retail employees make sense of disruptive technological innovation using AI as its focus. While existing research addresses AI adoption at the strategic level, little attention has yet been paid to how employees actually navigate this disruption in their daily professional lives. This study aims to shed light on the employee perspective and the consequences they face when adopting disruptive technologies, while providing problem areas of sensemaking that both managers and academics can act on. It addresses this by answering the following research question: How do employees of retail organisations make sense of new disruptive technology such as AI? Semi-structured interviews were conducted with eight employees across two German fashion retailers and analysed through Weick’s (1995) sensemaking theory, further challenged by the frameworks of Diffusion of Innovations (Rogers, 2003) and Organisational Ambidexterity (O’Reilly & Tushman, 2004). The findings reveal that AI is experienced as simultaneously impossible to ignore and difficult to grasp. In the absence of organisational guidance, employees develop six tactics for navigating the disruption. Three are rooted in sensemaking: forming fears and fascinations, managing identity and organisational contradictions. Further, there are three coping mechanisms: exploring through experimentation, framing the unfamiliar through language and redistributing responsibility to others. The study concludes that disruptive technologies cause significant hardship and worry when organisations fail to provide frameworks for meaning-making, leaving the burden of navigating artificial chaos with the individuals least equipped for it. The findings contribute to the literature on innovation management, while offering managers guidance on supporting employees through AI-driven transformation and raising broader societal questions about who bears responsibility when disruption comes before being thoroughly prepared.