Evolution of usage and application of machine learning and artificial intelligence in the development of en-terprise information systems and in decision support systems

Usage of large language models (LLMs) in enterprise information systems has been growing more common in recent years. The purpose of the study is to consider the evolution of technologies used in enterprise information systems from mathematical models to neural networks, including large language models, as well as suggest recommendations on the application of LLMs in enterprise systems and assume future tendencies and risks of using artificial intelligence (AI) in such systems. Methods and materials. A retrospective method was used to analyze the development of artificial intelligence algorithms. Several approaches to using LLMs in enterprise systems and decision support systems were considered and compared by several criteria identified based on the existing studies. Results. The conducted study includes several recommendations on the best practices of applying LLM-based approaches to enterprise systems. It also covers the advantages and disadvantages of a new LLM-based programming approach, where a person acts as a system architect, while a model performs the technical tasks. The study describes the most recent advanced technology, agentic AI, which allows large language models to interact with their external environments and perform diverse tasks using various tools. The study also includes assumptions about future tendencies of AI usage in enterprise information systems and the corresponding risks. Conclusion. The results of this study can be used as a base for managers’ decision making regarding the feasibility of using LLM-based methods considered in the study and their corresponding risks when building enterprise information systems.