Causal combinations for successful implementation of RPA and AI in Human Resources: A qualitative comparative analysis (fsQCA)

Abstract

This study seeks to identify the combinations of factors that enable successful implementation of Robotic Process Automation (RPA) and Artificial Intelligence (AI) in Human Resources (HR), moving beyond the descriptive approaches that have dominated previous research. A Qualitative Comparative Analysis (fsQCA) was conducted on a set of 10 documented cases, examining four factors: repetitive process, structured approach, full automation, and type of technology (accuracy versus employee experience). The findings reveal the principle of adaptability, showing that multiple pathways can lead to success. Each factor individually proved to be sufficient (consistency = 1.0), with none being strictly indispensable. This suggests that success can be achieved either through the efficient automation of repetitive processes or through strategies focused on employee experience, provided they are grounded in a solid design. The study offers a perspective for analyzing different combinations that provide strategic flexibility to CEOs, integrates findings that appear contradictory in the literature, and demonstrates that the benefits of HR automation go beyond cost reduction, positioning it as an opportunity for the strategic reinvention of the HR function.