Exploring the Intersection of AI, Language, and Law: A Bibliometric Analysis

This study investigates the interdisciplinary nexus of AI, language, and law through a comprehensive bibliometric analysis of 610 peer-reviewed publications sourced from Web of Science and Scopus (2001–2024). Utilizing VOSviewer, CiteSpace, and R bibliometrix, we map intellectual structures, collaboration networks, and thematic trajectories in this emerging field. Results reveal three developmental phases, an incubation period (2001–2013) dominated by symbolic systems, an emergence phase (2014–2018) with increasing cross-domain integration, and a maturation phase (2019–2024) marked by the mainstream adoption of LLMs in legal applications, yet the domain remains fragmented with limited co-citation coherence and underdeveloped interdisciplinary synthesis. Keyword co-occurrence and citation burst analyses indicate evolving focal points from traditional NLP to explainable AI and forensic linguistics, with ethical concerns and semantic complexity emerging as critical bottlenecks. This study contributes a systematic framework for understanding the epistemological, methodological, and geopolitical contours of AI-language-law scholarship and offers strategic directions for fostering integrated, inclusive, and transparent legal-AI systems.