A bibliometric analysis of RPA and AI research: Current trends and future directions

The integration of RPA and AI is increasingly driving business automation and intelligence. This study uses bibliometric analysis to explore the current landscape, key contributors, and trends in RPA+AI research, drawing on 396 publications from the Scopus database (2017–2024). The results identify influential authors, institutions, and countries, emphasizing the importance of interdisciplinary collaboration and the practical application of these technologies. The findings reveal a rapid rise in research output, with strong focus on RPA+AI development in finance, banking, and risk management, alongside the emergence of hyperautomation as a transformative trend. The analysis highlights four thematic clusters: RPA+AI applications in finance and accounting, automation tools in enterprise management, intelligent systems such as deep learning and natural language processing, and the expansive potential of hyperautomation. Network visualizations show a robust intersection between RPA and AI, reinforcing their synergistic relationship. This study provides a comprehensive review of RPA+AI research, offering insights into its academic evolution, interdisciplinary relevance, and industry-specific applications. The integration of advanced AI technologies into RPA is reshaping automation capabilities, improving operational efficiency, and fostering innovation. Future directions should include deeper exploration of hyperautomation frameworks, industry-specific applications, and the socio-organizational impacts of these technologies. By addressing existing gaps, this study lays a foundational for broader implementation and continued academic inquiry into RPA+AI domain.