Bridging technology and sustainability: a systematic review of AI applications in global food systems

The global food system is under increasing pressure from multiple critical challenges. It is struggling to deliver sustainable, resilient, and equitable food globally due to many factors, including climate change, resource depletion, population growth, and supply chain inefficiencies, which threaten global food security and environmental health. Consequently, the possibilities for using artificial intelligence (AI) as a disruptive technology have expanded significantly in recent years. AI provides a wide array of powerful tools (e.g., machine learning, computer vision, and predictive analytics) that have the potential to increase efficiency and significantly reduce waste, while also enhancing the quality of environmental stewardship across the entire food value chain (from farm to fork). This systematic literature review (SLR) provides an exhaustive overview of 7 years of published research between 2018 and 2025, focusing primarily on synthesizing current research on the use of AI to achieve a sustainable food system. This research is purposefully aligned with and framed by key targets of the UN Sustainable Development Goals (SDGs), specifically SDG 2 and SDG 12.