In the current years, the artificial intelligence (AI) technique has been utilized for waste management due to its higher accuracy. Understanding the future disposal demand of wastewater (WW) and sludge generation accurately is essential for WW treatment and sludge management. This study proposed an AI-based approach to predict the daily demand for WW and generation amounts of sludge, demonstrated for Ulaanbaatar, Mongolia. A machine learning approach was developed to predict the daily disposal amounts of WW and generation amounts of sludge based on the daily records from a WW treatment plant. In the validation process, the monthly-mean accuracy of the predicted disposal amounts of WW for the last month of 2020 was about 98.0% (predicted by the Medium Gaussian SVM model). Meanwhile, the monthly-mean prediction accuracy of the sludge generation in the same period was increased from about 83.1% to 84.7% by using the proposed approach. The proposals on future applications were made for WW treatment, e.g., optimizing the personnel arrangement, procurement of chemicals, and prediction of the sludge generation. For sludge management, our proposals were made from future treatment plans and recovery of resources and energy aspects. This study demonstrated that the AI technique is helpful for waste management.