In the context of global energy conservation and emission reduction, it is imperative to improve energy efficiency and promote sustainable development. The industry sector has consistently been a pivotal industry in implementing low-carbon practices, particularly in large industrial zones characterized by high energy consumption and carbon emissions. A focal point of research in such contexts revolves around the configuration of energy systems in industrial zone. This paper proposes a novel AI-driven multi-objective optimization approach for energy system design in industrial zone. Economy, environmental sustainability, and safety are considered as optimization objectives, and the Pareto front solution set is calculated using the NSGA-II algorithm. The optimal system design is determined based on the composite optimization objective function under different priority scenarios. This method provides valuable insights that could serve as a blueprint for energy system design in industrial zones, offering guidance towards more efficient and environmentally conscious energy configurations.