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The role of artificial intelligence in transforming the management processes of commercial organizations

https://doi.org/10.24182/2073-9885-2026-19-3-23-29

Abstract

In the context of the digital transformation of the economy, artificial intelligence (AI) is becoming a key factor in improving the efficiency of management processes in commercial organizations. The relevance of the research is due to the need to rethink traditional approaches to management in connection with the transition from intuitive expert solutions to databased management and algorithmic analytics. The purpose of the work is to analyze the role of AI in the transformation of management processes and identify conditions that ensure its effective implementation in commercial organizations.

To achieve this goal, the following tasks were solved: the influence of AI on the structure of management decisions was investigated; key changes in functional management processes (planning, control, personnel management) were identified; organizational and technological models of AI implementation were analyzed, and the main barriers and limitations were identified.

As a result of the study, it was found that the introduction of AI facilitates the transition to a predictive management model, increases forecasting accuracy, reduces transaction costs and strengthens control over business processes. It is revealed that the greatest effect is achieved when using hybrid architectures and control models of the «hub spokes» type, providing a balance between centralization and operational flexibility. It has also been proven that the effectiveness of AI depends not only on technological factors, but also on the level of organizational maturity, data quality, and staff readiness for change.

About the Author

A. S. Efremov
Synergy University
Russian Federation

Student

Moscow



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For citations:


Efremov A.S. The role of artificial intelligence in transforming the management processes of commercial organizations. Entrepreneur’s Guide. 2026;19(3):23–29. (In Russ.) https://doi.org/10.24182/2073-9885-2026-19-3-23-29

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ISSN 2073-9885 (Print)
ISSN 2687-136X (Online)