<p>Restaurant food waste is used as feedstock. It is transformed into high-value protein through precision fermentation. This process is powered by AI and automation, revolutionizing sustainable protein production. This review explores AI-driven precision fermentation as a solution to the growing global protein demand. The demand is projected to increase by 70% by 2050. At the same time, this technology aims to reduce the 931 million tons of food waste generated globally each year. Precision fermentation leverages machine learning for strain optimization and digital twins for bioprocess simulation. Autonomous bioreactors enable real-time adaptive control. This technology converts nutrient-rich food waste into functional proteins. It produces up to 90% fewer greenhouse gas emissions compared to conventional animal sources. The paper explores the technical foundations of microbial engineering. It also examines the role of robotics in high-throughput fermentation screening. Additionally, the integration of IoT and blockchain enhances process transparency and traceability. It highlights case studies and pilot programs in the USA, France, Brazil, and China, identifying opportunities and bottlenecks in feedstock variability, regulations, and public acceptance. Key research gaps include the need for AI models that handle noisy biological data and standardized platforms for academic-industry collaboration. The findings emphasize the potential of decentralized biomanufacturing hubs to support local food systems, reduce urban waste, and boost environmental resilience. This review highlights AI-driven precision fermentation to convert food waste into high-value protein, addressing both waste reduction and protein sustainability. With AI as a catalytic layer, this approach offers a scalable, economically viable model for future food systems.</p>