Over the past few years, total financial investment in the agricultural sector has increased substantially. Palm tree is important for many countries’ economies, particularly in northern Africa and the Middle East. Monitoring in terms of detection and counting palm trees provides useful information for a variety of stakeholders; it helps in yield estimation and examination to ensure better crop quality and prevent pests, diseases, better irrigation and other potential threats. Despite their importance, these information still difficult to obtain. In this study, we systematically review research articles between 2011 and 2021 on artificial intelligence (AI) technology for smart palm tree detection. A systematic review (SR) was performed using the PRISMA approach based on a four-stage selection process. Twenty-two articles were included for the synthesis activity reached from the search strategy alongside the inclusion criteria in order to answer tow two main research questions. The study's findings reveal patterns, relationships, networks, and trends in the application of artificial intelligence in the palm tree detection over the last decade. Overall, despite the good results achieved in most of the studies, the effective and efficient management of large-scale palm plantations still a challenge. In addition, countries which their economy strongly related to intelligent palm services especially in North Africa should give more attention to this kind of studies. The results of this research could benefit both the research community and stakeholders.