The integration of Artificial Intelligence (AI) into manufacturing enterprises is transforming traditional decision-making processes, enhancing operational efficiency, reducing costs, and improving product quality. This paper explores the development of AI-based decision-making models specifically designed for manufacturing environments. It examines key AI technologies, such as machine learning, predictive analytics, optimization algorithms, and reinforcement learning, and their applications in areas like production optimization, predictive maintenance, and supply chain management. Additionally, the paper highlights challenges in implementing AI systems, including data quality, system integration, and workforce skills, and discusses future trends like edge computing and digital twins. The findings emphasize AI’s potential to revolutionize decision-making, drive innovation, and improve overall competitiveness in the manufacturing industry.

Artificial Intelligence, Decision-Making Models, Manufacturing Enterprises, Machine Learning, Predictive Maintenance, Production Optimization, Supply Chain Management, Optimization Algorithms, Digital Twins, Edge Computing

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