Intelligent design of corporate information systems

Abstract

This paper explores modern approaches to the intelligent design of corporate information systems in the context of digital transformation and rapidly increasing architectural complexity. The study focuses on the integration of artificial intelligence, machine learning, simulation modeling, and data-driven architectural principles to enable a transition from reactive system management to proactive and self-optimizing architectures. Special attention is given to the use of digital twins as high-fidelity simulation models that allow safe evaluation of architectural changes prior to deployment, significantly reducing operational risks and technical debt. The results demonstrate that intelligent design approaches provide a robust methodological foundation for the continuous evolution, optimization, and sustainable operation of modern corporate information systems.