The digital transformation of production systems and the advent of Industry 4.0 have led to significant changes in the way work in the field of artificial intelligence is organized. As companies increasingly rely on automated processes and digital tools, they are looking for new and more efficient ways to manage their systems while maintaining flexibility and modularity. This article proposes an interdisciplinary approach to identifying gaps in the implementation of digital technologies in industry, with an emphasis on artificial intelligence. The author offers a methodological framework based on the principles of artificial intelligence development and machine learning methods to eliminate these gaps that have been identified in the course of research. In particular, artificial intelligence consists of machines with intelligence, characterized by sufficient computing resources and algorithms that determine the learning process in order to gain knowledge, as well as increase productivity. In order to enhance the efficacy of production processes, the author puts forth a model that integrates the fundamentals of Industry 4.0 with advanced digital technologies, such as artificial intelligence, on an enterprise-wide scale. The outcome of this work is a successful implementation of a well-designed model for the digital platform in the of Industry 4.0.