This review combines advances in the applications of artificial intelligence (AI) to enhance food safety and security, alongside recent scientific advances in sustainable agriculture, with a special focus on the case of Iran. A systematic approach was used, combining bibliometric analysis of the reviewed literature (2012–2024) from the Web of Science (WoS) and Scopus databases with a thematic assessment of case studies and empirical research. Keywords such as “artificial intelligence in food safety,” “machine learning,” “sustainable agriculture,” and “precision agriculture” guided the search. Key findings highlight the role of AI in contamination detection, supply chain optimization and predictive analytics, with specific applications in Iran, such as AI-based aflatoxin detection in pistachios. Challenges such as data quality, ethical concerns, and scalability are critically discussed, with Iran\\\'s unique conditions of water scarcity, economic sanctions, and limited infrastructure providing valuable insights. By using these technologies, Iran can increase food security, improve resource productivity and build climate-resilient agricultural systems. However, achieving these goals requires targeted investment in digital infrastructure, capacity building programs, and international collaborations. This review provides a comprehensive roadmap for researchers, policy makers and stakeholders to harness the transformative potential of AI and sustainable agriculture in Iran and other regions facing similar challenges.

Keywords