The integration of circular economy principles with artificial intelligence (AI) offers transformative potential for enhancing the efficiency, sustainability, and scalability of algal biorefineries. Algal bio refineries, which convert algae into valuable products such as biofuels, biofertilizers, and pharmaceuticals, align closely with circular economy objectives by promoting resource efficiency, waste minimization, and carbon sequestration. AI technologies, including machine learning, predictive analytics, and optimization algorithms, provide significant advantages in the management of bio refinery operations by improving algal growth predictions, optimizing biomass production, and enhancing nutrient cycling. This chapter reviews the role of AI in algal bio refineries, highlighting its applications in predictive modelling, real-time monitoring, and process optimization. AI-driven decision support systems enable better management of cultivation parameters, resulting in improved productivity and reduced environmental impact. The review also discusses successful case studies where AI has been implemented in industrial-scale algal cultivation and processing, demonstrating substantial gains in operational efficiency and resource recovery. Furthermore, this chapter identifies the key challenges, such as data quality, integration with existing infrastructure, and the need for explainable AI models, and outlines future research directions. Emphasis is placed on the importance of interdisciplinary collaborations between biotechnology, data science, and policy development to maximize the potential of AI in algal bio-refineries. Ultimately, this review suggests that AI, when coupled with circular economy principles, can unlock the full potential of algal bio refineries as a cornerstone of the sustainable bio economy.