AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework

The extant literature has outlined the significance of collaborative intelligence stemming from effective partnership between artificial intelligence (AI) systems and human workers to achieve organisationally valued outcomes. However, there is paucity of research insights on the factors influencing AI-human partnership and its impact on business performance. To bridge this knowledge gap, this paper draws on the knowledge-based view, (KBV) socio-technical systems (STS) and organisational socialisation framework (OSF) to develop and validate a novel theoretical model examining the relationships between knowledge sharing, employees' AI skills, trust, and role clarity in a collaborative working environment to enhance business performance. A primary survey-based research method was used to capture responses from 164 employees in the UK creative industries, and further analysed by employing Structural Equation Modelling technique. Our findings will provide managers and the AI community with primary evidence and strategies that will help to develop collaborative intelligence capabilities within the organisations.

Automated summary

This paper addresses the lack of research insights on the factors influencing AI-human partnership and its impact on business performance. By drawing on the knowledge-based view, socio-technical systems, and organisational socialisation framework, the study examines the relationships between knowledge sharing, employees' AI skills, trust, and role clarity in a collaborative working environment. The findings provide evidence and strategies for developing collaborative intelligence capabilities within organizations.