The use of Artificial Intelligence (AI) in industrial settings has a transformative effect on the way companies produce and offers the potential of more efficient value creation processes in companies. An increasing number of development and research initiatives are focusing on the capabilities of AI implementations and on the areas in which AI applications can be profitably integrated into production processes. One application area is the integration of AI applications for predicting process times in manual assembly. Knowing these process times as accurately as possible is proving to be beneficial to companies, as it promises more efficiency in production planning and control. This paper focuses on the development of an industry-oriented demonstrator. This demonstrator includes a digital assistance system (DAS) for assembly lines which guides the worker through each step of an assembly process and records the individual process times of the workers. Based on the tracked process times, the DAS is able to generate AI-based process time predictions for unknown product variants. By tracking the individual performance of each worker in the assembly process, the system aims to create individual performance profiles for each worker, capturing effects such as learning curves and enabling individual process time predictions for each worker.