Evolutionary development and future of situational management technologies

Abstract

The article considers the evolution of methods and technologies of decision-making by officials in the context of their use of situational management capabilities in the «individual», «information layout», «intelligent systems» modes, and implementation of artificial intelligence (AI). The problems and disadvantages of different management models are considered. The requirements for the intellectualization of computers are defined. It is shown that the introduction of cloud technologies and analytics of extensive data have further expanded the operational capabilities of situational management systems. Key trends, including the integration of machine learning and AI, the introduction of advanced sensor technologies, and the development of network communication systems for the uninterrupted exchange of information in the network of situational centers, have expanded the operational capabilities of situational management systems. The need for the introduction of AI, which will become one of the main directions in the development of decision support systems, is proven. The possibility and necessity of using AI agents in situational management systems is also considered and substantiated. An AI agent is an intelligent system designed to perceive the environment, make decisions, and perform actions with the intention of achieving a specific goal. AI agents represent a paradigm shift in traditional computing. They are not just tools we use, but intelligent partners that can learn, adapt, and solve problems with us. The concept of AI agents is not new, but recent technological advances have transformed them from theoretical constructs into powerful practical instructions. The described transformative technology in the building blocks of AI agents and the large language model allow us to understand how they serve as the «brain» of AI agents.