The potential of Mass Customisation (MC) strategy is continuously expanding through the implementation of Industry 4.0/5.0 technologies. In this study we present the novel approach to enhancing the potential of Artificial Intelligence-based techniques for MC level prediction. Firstly, the empirical research was conducted among more than 150 European manufacturing companies in the automotive sector concerning factors influencing the increase in the level MC, as well as the Industry 4.0 or 5.0 technologies applied. Next, the collected survey data is next pre-processed to eliminate infrequent responses and subsequently analysed using the k means clustering method for labelling purposes. The resulting dataset is then used to fine-tune parameters and train a classifier based on a Multilayer Perceptron (MLP), aimed at identifying the MC level in automotive enterprises. The developed classifier achieved average accuracies of 0.94 and 0.93 for training and testing, respectively. The proposed approach is validated through a real-life case studies from automotive industry, demonstrating the adaptability of our concept and its potential for diverse industrial applications.