Workplace learning and AI challenges: causes and effects

Purpose The use of artificial intelligence (AI) in workplaces is rapidly increasing in our society. This means that AI is fundamentally reshaping workplaces, how tasks are performed and how the authors interact with colleagues. This study aims to develop explanatory knowledge about the challenges of AI-augmented workplaces. Design/methodology/approach A qualitative and deductive research approach was applied. Key challenges discovered in the literature review were used as predefined themes to identify and analyse empirical data. Findings The authors have identified five key challenges: AI Strategy, AI Education, Control, Meaningfulness and Integrated Work Processes for Human-AI Collaboration. These challenges were examined in terms of their causes and effects, and an explanatory model (AICH) was developed. Research limitations/implications The study collected data from five companies, which provides some generality beyond this study’s empirical domain. However, it poses challenges in making broader generalisations. Future research could be designed as broader studies to confirm, modify or challenge the findings. Practical implications The findings contribute to workplace learning and provide a basis for identifying risks and potential measures. Social implications The identified challenges regarding AI-assisted workplaces will most likely have broader social ramifications, affecting employees’ overall well-being and company culture. Originality/value The authors do not claim that the challenges per se are new. However, the authors claim that the models consisting of explanatory knowledge visualised as cause-and-effect models are new.