The concept of the Smart Aided Process Planning (SAPP) system is presented in this paper. This system represents the next generation of CAPP systems, utilizing AI and machine learning techniques. SAPP features a modular architecture that includes the main Hybrid Expert System, modules for Supervised Learning, and Reinforcement Learning, making it an intelligent tool. Input data are automatically downloaded from the STEP format. Proprietary solutions have been developed to automatically load STEP data from files into the database. Algorithms for the automatic recognition of technological features have also been implemented. The designed technological machining processes are primarily intended for CNC machine tools. Therefore, the output data are stored in a proprietary format based on an extended STEP-NC standard. To implement the supervised learning procedure, numerous predictive models were trained with data obtained from the database. These models perform tasks such as generating the correct structure of the machining process, selecting appropriate tools, and determining cutting parameters. The concept of using reinforcement learning is also presented. The main application of this module is to generate tool paths and control programs for CNC machine tools. For this purpose, it is proposed to build a digital twin of the machine tool, which will serve as a simulation environment for the agent's actions.