Observations on Lean Office and artificial intelligence intricacies in the context of public administration scenarios using a systematic literature review

Purpose This study aims to discuss the state of the art in Lean Office, its technological advancement through artificial intelligence (AI) and its application in the public sector, while proposing a way to unify these three areas. Design/methodology/approach A systematic literature review (SLR) following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol identified literature published between 2020 and 2024. The final sample underwent bibliometric analysis (Bibliometrix and R language) to map the field’s conceptual and intellectual structures. Findings “Lean Principles” and “Public Sector” emerged as motor themes alongside “AI,” with “Lean Office” positioned as a transitional topic. The intellectual structure centers on Lean public sector adaptation. The analysis identifies two integration modes: AI for automating administrative tasks and AI as a support tool for Lean methods. However, tension exists between centralized AI development and the decentralized nature of Lean culture and principles. Research limitations/implications Despite querying multiple databases, literature simultaneously addressing AI, Lean Office and Public Administration is scarce, indicating an underexplored niche. Additionally, software functionality constraints limited the bibliometric analysis. These findings highlight a knowledge gap and the pressing need for further extensive literature reviews. Practical implications This study provides information on current research, trends and analysis regarding AI and Lean Office for the public administration community. Originality/value This research bridges the knowledge gap by integrating three disparate themes: Lean Office, AI and public administration. The findings offer a novel conceptual lens, enabling stakeholders to leverage synergistic relationships between these advancements and helping practitioners interpret complex concepts.