AI-enabled administrative contracting: A bibliometric review of the legal-tech literature

This study provides a bibliometric review of the legal-tech literature on AI-enabled administrative contracting, and it is focused on research published between 2021 and 2026 in the Web of Science Core Collection database. It used a structured search strategy and a screened dataset of 484 publications, the analysis maps publication patterns, source distributions, and citation performance. Bibliometric mapping in VOSviewer software was used to visualize the field's conceptual structure through keyword co-occurrence networks and to examine international collaboration patterns. The results identify four thematic clusters that organize the literature: (1) machine learning for integrity and risk analysis (including collusion detection), (2) NLP and deep learning for contract text interpretation, (3) digital procurement ecosystems connecting e-procurement, big data and blockchain-based traceability, and (4) performance-oriented contract management and automation. The findings highlight an increasingly interdisciplinary field where technical innovation converges with governance, accountability and the public interest.