Container terminal operations are rapidly adopting artificial intelligence (AI) technologies to improve efficiency, sustainability, and automation amid ongoing digital transformation. This study conducts a comprehensive bibliometric analysis of 391 publications (1992-2024) from the Web of Science Core Collection using Biblioshiny 4.0. The findings reveal a paradigm shift toward AI-driven optimisation across key areas, including berth allocation, crane scheduling, truck fleet management, and intelligent port automation. Despite this progress, a critical gap remains: the lack of empirical validation using real operational data. This gap highlights the urgent need for cross-industry collaboration to bridge theory and practice. The study urges policymakers and port authorities to implement standardised AI frameworks, invest in workforce upskilling, and enhance digital infrastructure. Future research should focus on scalable, data-validated AI applications and on promoting longitudinal case studies and industry partnerships to ensure the effective, sustainable integration of AI technologies into port logistics.