Traditional Arabic and Islamic Medicine (TAIM) originated in the seventh century, but unlike Chinese and Ayurvedic knowledge, TAIM has not evolved through evidence-based research and commercialization. Today, while global interest in traditional medicine is growing, TAIM ancestral knowledge remains unknown and unexplored. The purpose of this study is to provide baseline information on the status of TAIM research to guide future research and contribute to the growth of the sector. The focus of the study is the Fertile Crescent, a region of the Arab World endowed with a rich and diverse eco-geography. The method adopted was a scoping review following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. The databases used included the Arab World Research Source: Al Masdar, CAB Direct, Iraqi Academic Scientific Journals, MEDLINE, Scopus, Web of Science and Google Scholar. The timeline of the search spanned from the database inception date to June 2024. The search led to 10,171 records which were subsequently reduced to 1,990 publications after deleting duplicates and performing a two-stage screening. Artificial intelligence (AI) technology was used to analyze the data focusing on reported plant species, treatment applications, study types and countries. The Generative Pretrained Transformer 4 (GPT-4) Turbo, a large language model, was used to extract the key features and the results were validated by the researchers. The findings revealed that the types of studies were mostly laboratory-based (86%), while few studies (14%) were field based. The top five treatment applications include cancer (29%), bacterial infections (22%), inflammation (12%), fungal infections (9%), and diabetes (8%). The most notable plant species that were under investigation in the various studies were L. (Ranunculaceae), L. (Lamiaceae), Mill (Lamiaceae), L. (Lamiaceae), and L. (Lamiaceae). In this review we discuss our findings which suggest potential avenues for further developing TAIM research and exploring the development of botanical drugs. Our findings also revealed that the number of ethnobotanical studies was limited suggesting an urgent need to prevent the loss of ancestral knowledge by formalizing it through evidence-based research and policy guidelines. Addressing these gaps through interdisciplinary collaboration and improved data-sharing mechanisms will be crucial for advancing TAIM research and medicinal plants.