The rise of hybrids: plastic knowledge in human-AI interaction

Purpose – The aim of this research is twofold: firstly, to get more insights on digital maturity to face the emerging 4.0 augmented scenario, by identifying AI competencies for becoming hybrid employees and leaders; secondly, to investigate digital maturity, training, and development support and HRs satisfaction with the organization as valuable predictors of AI competencies enhancement. Design/methodology/approach – A survey was conducted on 123 participants coming from different industries and involved in functions dealing with the ramifications of Industry 4.0 technologies. The sample has included predominately small-to-medium organizations. A quantitative analysis based on both exploratory factor analysis and multiple linear regression was employed to test the research hypotheses. Findings – Three main competencies clusters emerge as facilitators of AI-human interaction: i.e., leadership, technical, and cognitive. The interplay among these clusters gives rise to plastic knowledge, a kind of moldable knowledge possessed by a particular human agent, here called hybrid. Moreover, organizational digital maturity, training and development support, and satisfaction with the organization were significant predictors of AI competencies enhancement. Research limitations/implications – The size of the sample, the convenience sampling method, and the geographical context of analysis (i.e., California) required prudence in generalizing results. Originality/value – Hybrids’ plastic knowledge conceptualized and operationalized in the overall quantitative analysis allows to fill in the knowledge gaps that an AI agent-human interplay may imply, generating alternative solutions and foreseeing possible outcomes.