Exploring the Role of AI-Enabled Collaboration for Sustainable Business Process Management

Sammanfattning

Artificial Intelligence (AI) is increasingly discussed as a means of supporting communication, knowledge retrieval, documentation, and decision-making in shop-floor environments. This study explores how AI can support Frontline Workers (FLWs) and managers in improving communication, collaboration, and decision-making. The research is based on ten semi-structured interviews conducted with FLWs, managers, and cross-functional employees working in industrial shop-floor environments in Small and Medium Enterprises (SMEs). The interviews were anonymized, transcribed, and analyzed in MAXQDA software using inductive thematic analysis. The findings revealed that FLWs play a significant role in identifying operational issues. However, their ability to translate process observations into actionable responses is influenced by role dependencies, communication structures, documentation quality, and access to process knowledge. The results indicate that AI-supported communication and documentation could support sustainable BPM by facilitating better escalation, knowledge reuse, and operational response. Participants primarily viewed AI as a supportive tool that can help analyze issue reports, translate and summarize shift data, retrieve historical knowledge, assist with expert routing, and provide decision-makin support. This study contributes to research on human-centered AI, socio-technical systems, and AI-supported collaboration by showing how AI may support everyday operational communication in SMEs. Since no AI-supported system was implemented or evaluated in the study, the findings should be interpreted as exploratory design implications, rather than direct evidence of improved performance or sustainability.