The growing environmental, social, and economic challenges of unchecked industrial development have led to the widespread adoption of sustainable development principles, rooted in balancing economic growth with environmental protection and social equity. Circular economy enterprises, which seek to minimize waste and optimize resource use, are increasingly recognized as key players in achieving sustainability. This research explores the potential of artificial intelligence (AI) to support circular enterprises by improving decision-making, enhancing resource efficiency, and reducing waste. Through AI-driven predictive analytics, automation, and data analysis, circular enterprises can optimize their processes, making strides towards sustainable operations while addressing challenges such as resource management, production efficiency, and supply chain optimization.
The study builds on foundational sustainable development theories while focusing on AI's role in advancing circular economy principles in small municipalities and small-to-medium enterprises (SMEs). In its initial phase, the research defines critical elements within circular enterprises, collects relevant data (including a nationwide survey of local governments), and identifies opportunities for AI integration to solve operational challenges. By aligning circular economy goals with AI capabilities, this work contributes an innovative framework that bridges the digital divide and drives businesses toward a more sustainable future.
