Real-Time AI and Blockchain for Traceability and Transparency in the U.S. Food Supply Chain

Abstract

Abstract: The integration of Artificial Intelligence (AI) and Blockchain technology is reshaping the U.S. food supply chain, addressing critical challenges in traceability, transparency, and safety. As consumer demands for ethically sourced and high-quality products grow, these technologies provide innovative solutions to monitor and verify the journey of food products from farm to fork. Blockchain ensures immutable, decentralized records, enabling stakeholders to trace origins, verify certifications, and identify contamination sources in real-time. Complementing this, AI-driven analytics process vast amounts of data to optimize supply chain operations, predict risks, and ensure compliance with safety regulations. This paper explores the synergistic application of AI and Blockchain in building a resilient and transparent food supply chain in the United States. By analyzing case studies and real-world implementations, the study highlights how AI enhances blockchain’s functionality through predictive algorithms and anomaly detection, while blockchain guarantees data integrity and accessibility. We discuss challenges such as interoperability, scalability, and the need for standardized protocols, offering practical solutions and policy recommendations. Our findings demonstrate that the fusion of these technologies not only mitigates risks like food fraud and contamination but also promotes sustainability by enabling precise tracking of carbon footprints and waste reduction efforts. The adoption of AI and Blockchain offers stakeholders—including producers, regulators, and consumers—a trustworthy ecosystem, fostering confidence in the safety and authenticity of food products. This paper underscores the transformative potential of these technologies in achieving a future-ready food supply chain, emphasizing the importance of innovation, collaboration, and regulatory alignment.