Bibliometric Visualisation of AI Research in Arab Countries (2013–2025): Emerging Trends, Gaps, and Future Directions

Abstract

Artificial Intelligence (AI) has become a key driving force of global digital transformation, with Arab international locations increasingly prioritising its adoption through country-wide techniques, which include Saudi Vision 2030 and Oman Vision 2040. Despite this momentum, AI studies output within the location stays thematically slender and fragmented, restricting its worldwide effect. This examines ambitions to map and compare the AI studies panorama in Arab countries, pick out rising tendencies, and find underdeveloped domain names requiring further scholarly attention. Data had been retrieved from the Scopus database, yielding 3,583 studies from 2013 to 2025, which have been passed through several filtering phases to arrive at 1405 documents. Using VOSviewer, the evaluation included co-authorship networks, keyword co-prevalence, and quotation styles. Results suggest that studies' pastime is focused among a restricted variety of prolific authors and institutions, with susceptible cross-country collaboration. The most often used terms are Deep Learning (DL), Saudi Arabia, ChatGPT, Machine Learning (ML), and Artificial Intelligence (AI). Research on COVID-19 accounted for 3.9% of the overall output, suggesting a brief shift toward healthcare packages and public health. Many concerns remain about Arabic natural language processing (NLP), regional datasets, AI ethics, and interdisciplinary programs. In order to strengthen the Arab region's position in global AI research, the low common citation impact emphasizes the necessity of excellent institutional coordination, theme diversification, and alignment with strategic national visions.