Substitution and complementarity between human and artificial intelligence: a dynamic capabilities view

Purpose This paper draws on the dynamic capabilities (DC) view to develop a conceptual framework that explicates the mechanisms through which human intelligence (HI) and artificial intelligence (AI) substitute and complement each other for organizational knowledge management (KM) while considering the role of ethics. Design/methodology/approach This is a conceptual paper that draws on DC theory and integrates insights from the burgeoning literature on organizational AI adoption and application to develop a conceptual framework that explains the mechanisms through which HI and AI may substitute and complement each other for organizational KM to develop DC. Findings The conceptual framework demonstrates that substituting HI with AI is suitable for external environmental scanning to identify opportunities, while AI substitution for HI is ideal for internal scanning through data analytics. Additionally, HI complementing AI is effective for seizing opportunities by aligning internal competencies with external opportunities, whereas AI complementing HI is beneficial for reconfiguring assets by transforming tacit knowledge into explicit knowledge. This substitution and complementarity between HI and AI shape KM processes—acquisition, conversion, application, and retention—that influence organizational performance, depending on how internal and external ethical standards govern organizational AI use. Research limitations/implications The paper presents key insights into how AI may substitute for HI for internal data analytics in KM but may be ineffective for external environmental scanning to sense opportunities. It further reveals that using AI to capture and convert tacit knowledge (HI) to explicit knowledge requires ethical considerations at the organizational level, but ethical considerations are necessary at the employee/manager level when HI relies on AI-generated insights for strategic decisions. Practical implications The study implies that in environments with defined regulations for AI and KM (e.g. privacy protection), responsibility for the consequences of AI-HI substitution and complementarity in developing DC can be assigned to specific steps in the KM process. However, in environments with undefined regulations, responsibility must be assigned to people, units or departments who manage the entire KM process to ensure accountability for ethical breaches. Originality/value This study proposes AI-HI substitution and complementarity in organizations to extend the understanding of the relationship between AI and HI to DC development.