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The circular bioeconomy (CBE) is an evolving paradigm that promotes sustainable economic development. Artificial intelligence (AI) emerges as an important enabler within this paradigm, offering capabilities that could significantly enhance operational efficiencies and innovation. Despite its recognized potential, the full value of Al across the diverse areas of the CBE remains underexplored. This paper introduces a novel framework for assessing and harnessing the role of Al to facilitate a transition towards a CBE. The framework was developed through an interdisciplinary literature review and conceptual modeling. The framework maps ten key CBE domains against eight core AI functions (such as prediction, optimization, and discovery) that can be leveraged to enhance the circularity of bioeconomic processes. A case study on biowaste valorization, employing a framework-guided literature review methodology, demonstrates the framework’s utility in identifying research gaps and opportunities in using AI. The case study reveals a current emphasis on AI for prediction and optimization tasks, while highlighting significant underutilization in discovery and design functions. The framework can help guide researchers, policymakers, and industry stakeholders in identifying and deploying AI-driven solutions that help support a more sustainable bioeconomy.
Shah et al. (Tue,) studied this question.