Nitrogen heterocyclic compounds (NHCs) widely exist in industrial wastewater and presented significant environmental and health risks due to their toxicity and persistence. This review addressed the challenges in treating NHCs in industrial wastewater, focusing on developing sustainable and efficient treatment processes. While various technologies, including adsorption, advanced oxidation/reduction processes (AOPs/ARPs), and microbial treatments, have been studied at the experimental stage of treating synthetic wastewater, scale-up for industrial applications is imperative. After analyzing the characteristics of NHCs and evaluating different treatment methods with the aid of efficiency and cost-benefit analysis, efficient detoxification while maximizing energy recovery constitutes a critical requirement in treating NHC-containing wastewater. Hence, we proposed a comprehensive strategy combining hydrolysis-acidification pretreatment enhanced by electro-assisted micro-aeration with methanogenic anaerobic digestion as core treatment units. The process design for NHC-containing wastewater treatment should consider the dynamic balance between removal efficiency, energy consumption, and ammonia recovery, incorporating environmental and economic impacts through life cycle assessment and technical-economic analysis. The potential of machine learning in optimizing operational parameters, predicting effluent quality, and supporting process design decisions is promising. To develop interpretable and practical solutions, the integration of data-driven approaches with mechanistic understanding and prior knowledge is indispensable. This review provided novel insights into sustainable NHC treatment strategies in the context of energy valorization and artificial intelligence advancement, offering guidance for future research and industrial applications.