Purpose <p>This study investigates the integration of artificial intelligence (AI), including deep learning (DL) and machine learning (ML), across the agri-food value chain. It aims to explore how AI is transforming agriculture and food industries by enhancing sustainability, efficiency, and precision, while addressing global food security and environmental challenges.</p> Methods <p>A comprehensive review of recent literature and technological advancements was conducted, focusing on AI applications in agriculture, food processing, packaging, safety, fraud detection, personalized nutrition, and sensory evaluation. Various AI models and their sector-specific implementations were analyzed to assess their impact and potential.</p> Results <p>AI has evolved as a transformative tool in the agri-food sector. Applications include automated harvesting, predictive crop modeling, pest and disease detection, intelligent irrigation, supply chain optimization, and quality control. The study highlights how AI-driven solutions are improving traceability, reducing waste, and enabling data-driven decision-making across the food system.</p> Conclusion <p>The convergence of modern AI technologies with traditional agricultural practices is driving a transformative change in the global food industry. Urgent adoption of AI by stakeholders, industries, and academia is essential to meet nutritional demands, ensure food safety, and align with sustainability goals. This study serves as a strategic reference for leveraging AI to advance and sustain the agri-food ecosystem.</p>