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Application of Artificial Intelligence in Business Planning

Author

Listed:
  • Yu. A. Rakovskaya
  • M. N. Koniagina

Abstract

The paper presents an innovative method of business planning using artificial intelligence technology. In rapidly changing conditions, the possibility of reliable forecasting and planning with an error of less than 10% is in high demand. The introduction of artificial intelligence technology and automation of analysis and planning processes allows us to create a completely new dynamic multi-agent model of financial business planning that quickly responds to changes in external macroeconomic factors and reduces the risk of human factor influence, which became the result of the study. Having set the goal of developing a new, relevant, modern and highly accurate technological approach to business planning, the authors studied a number of modern scientific studies on the introduction of artificial intelligence in the processes of financial planning and forecasting, systematized them and identified interesting and practically implementable ideas. As a result, an approach was proposed that allows for fairly flexible and quickly implemented business planning, showing a highly reliable result in a short period and implementing the possibility of promptly changing the parameters of the company's activities. However, its implementation requires modification of business planning processes and implementation of an autonomous multi-agent system, which are also developed and proposed in the study. The article will be of interest to practicing economists and business representatives involved in business planning, as well as to scientists and students involved in projects to stimulate entrepreneurial activity.Â

Suggested Citation

  • Yu. A. Rakovskaya & M. N. Koniagina, 2025. "Application of Artificial Intelligence in Business Planning," Administrative Consulting, Russian Presidential Academy of National Economy and Public Administration. North-West Institute of Management., issue 5.
  • Handle: RePEc:acf:journl:y:2025:id:2834
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    File URL: https://www.acjournal.ru/jour/article/viewFile/2834/2073
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    References listed on IDEAS

    as
    1. Söhnke M. Bartram & Jürgen Branke & Mehrshad Motahari, 2020. "Artificial intelligence in asset management," Working Papers 20202001, Cambridge Judge Business School, University of Cambridge.
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