Still doing it yourself? Investigating determinants for the adoption of intelligent process automation

Abstract

Abstract Intelligent process automation (IPA) augments symbolic process automation using artificial intelligence. Emulating human decision-making, IPA enables the execution of complex processes requiring decision-making capacities. IPA promises great economic potential as it enables more efficient use of the human workforce. However, the adoption rate in practice falls behind these potentials. Our study aims to investigate reasons and identify areas for action towards IPA adoption. To this end, we identified 13 determinants and created an extended UTAUT model. We tested the model with partial least squares structural equation modeling for significant influential relationships between the determinants based on a user study. We contribute to theory and practice finding a special role of trust and transparency for the adoption of IPA. Likewise, we show that organizations should cultivate a positive attitude towards IPA diffusion. Further, our results contribute with a focus on the potential adopters as IPA adoption is contingent upon their characteristics, such as experience and job level.