Artificial Intelligence Driving the Sustainable Development of Smart Cities: A Bibliometrics Study from 2014-2025

Driven by global urbanization and goals like the “United Nations 2030 Agenda” and “dual carbon targets,” research on AI and smart cities has emerged as a leading interdisciplinary field. This paper analyzes 950 papers from the Web of Science core database (2014–2025) using bibliometric tools like VOSviewer and CiteSpace, focusing on keyword co-occurrence, collaboration networks, and national patterns. The findings show: (1) Strong collaboration within author teams but limited cross-team interaction, focusing on AI for urban resource optimization and efficiency; (2) Diverse research orientations among institutions, with some leading in output and influence, and cross-regional collaboration driving international exchange; (3) Significant differences in research influence among countries, with a few dominating output and quality; (4) Keywords have shifted from technical themes like “big data” and “Internet of Things” to sustainable issues like “blockchain” and “carbon neutrality,” highlighting the integration of AI with sustainability goals. This study provides a comprehensive overview of field hotspots and insights into sustainable pathways for AI-driven smart cities.