Principles of building a model of adaptive intelligent management in information systems

Abstract

Today, the dynamism of the external environment and the exponential growth of data volumes require a transformation of traditional administrative methods. The purpose of the study is to develop a model for coordinating the resources of an information system that ensures the stability of functioning in conditions of uncertainty. The article uses methods of system analysis, the theory of multi-agent systems and predictive modeling to create an adaptive control loop. The results reflect the advantages of the author’s adaptive intelligent management (AI) model, which combines decentralized decision-making with centralized monitoring. The mathematical apparatus describes the dynamics of changes in the quality of the system through indicators of information capacity, reaction speed and stability. Comparative calculations confirm an increase in management efficiency by 109.5% and an increase in the level of intellectual support by 294.4%. Automation of routine operations minimizes human involvement in administrative cycles, freeing up cognitive resources for strategic planning. The findings confirm the effectiveness of the transition to predictive regulation to ensure the organization’s survivability in a turbulent environment. The proposed approach contributes to the formation of an organizational culture based on algorithmic transparency and objective data. The practical implementation of the model guarantees a quick return on investment by reducing transaction costs and minimizing the risks of erroneous decisions.