Smart farming and technological development in agriculture have become pivotal in ensuring global food security and ensuring sustainability in agriculture. The application of intelligent systems and machine vision is critical in crop management, resource estimation, and yield forecasting. Considering the expanding use of artificial intelligence (AI) and machine learning (ML) in agriculture, the identification of existing research trends is crucial. Such technologies are very relevant to precision farming given that they have a major influence in matters to do with efficiency and decision-making. Bibliometric analysis of this context shows the interests of different countries in technology adoption in agriculture and their research interest in applying intelligent systems in agriculture. Despite extensive research, a comprehensive understanding of the global landscape on the adoption of AI and ML in precision agriculture will help in understanding the emerging trends in agriculture technology. The main objective of this study is to map and analyze publications concerning the historical background and the status of AI and ML in precision agriculture from 2008 to 2024. Major areas of research cover digital agriculture, smart farming, and how technology enhances sustainability in agriculture. This assessment benefits researchers, policymakers, and practitioners based on proposed directions for future research and optimal funding in AI-applied precision agriculture.