AI-BASED ENERGY MANAGEMENT FOR INDUSTRIAL DECARBONIZATION IN UZBEKISTAN

Abstract

Artificial intelligence is rapidly transforming industrial energy management by enabling predictive optimization, real-time decision-making, and adaptive process control. This study investigates the application of AI-based energy management systems in Uzbekistan’s manufacturing sector, with particular emphasis on energy-intensive industries such as cement, metallurgy, and chemical production. Drawing on national industrial statistics, production audits, and process modeling, the research evaluates the economic and environmental impacts of AI-driven optimization. The findings indicate that artificial intelligence systems can reduce industrial energy consumption by 18–35 percent, lower production costs by up to 20 percent, and decrease carbon dioxide emissions by more than 25 percent. A comprehensive decarbonization framework is proposed, integrating digital infrastructure, predictive analytics, and renewable energy coupling to support sustainable industrial transformation. The results demonstrate that artificial intelligence constitutes a critical technological pathway for enhancing competitiveness and accelerating climate mitigation in Uzbekistan’s manufacturing sector.