METHODOLOGICAL PRINCIPLES OF IMPLEMENTING ARTIFICIAL INTELLIGENCE INTO ORGANIZATIONAL MANAGEMENT SYSTEM

The article examines the theoretical and methodological principles of integrating artificial intelligence into an organization's management system. It presents a cumulative model illustrating the impact of artificial intelligence on the organization's management mechanism, which identifies the subjects of influence, tools of influence, directions, and dimensions of influence. Additionally, it describes the challenges posed by the influence of artificial intelligence on the organization's management mechanism and outlines the main outcomes of this influence. The ways of improving management productivity in various dimensions (socio-technical, strategic-structural, innovative- organizational, task-oriented, information-system) have been systematized. The main results that the use of artificial intelligence offers to the organization have been highlighted, comprising the automation of routine tasks, the reallocation of working time to strategic and creative tasks, increased efficiency in decision-making through analytics and forecasting provided by artificial intelligence, improved external and internal communication, enhanced effectiveness in HR management, formulation of realistic and achievable strategies aligned with future changes, and the development of innovative products and services. An algorithm for introducing artificial intelligence into the organization's management system has been proposed. The allocation of 8 stages is substantiated as follows: formation of organizational culture; determination of the goals for implementing artificial intelligence; identification of the main performance indicators; establishment of an information base on the state of the management system; analysis of products using artificial intelligence; integration of artificial intelligence products into the management system; monitoring the results of artificial intelligence implementation; and conducting a management system audit. The factors related to the development, implementation, and adaptation of artificial intelligence within the organization's management system at each stage of its implementation have been considered. These factors include: rethinking the interaction between people and machines in the work environment; awareness among management and staff; organizational support; openness to innovation; staff resistance to change; the presence of a system for disseminating best practices; availability of critical skills for artificial intelligence implementation; ensuring ethical components such as bias, confidentiality, and transparency; integration of model results into relevant business processes; compatibility with other available information systems; and the satisfaction level of stakeholders with the outcomes of artificial intelligence implementation