INTEGRATION OF ARTIFICIAL INTELLIGENCE INTO THE CORPORATE MANAGEMENT SYSTEM

The article examines the potential of Artificial Intelligence (AI), with a focus on Machine Learning (ML) and Deep Learning (DL), in the domain of corporate management. A review of the literature and existing practices reveals that AI has the potential to significantly transform traditional business processes, enhance decision-making efficiency, and provide corporations with substantial competitive advantages in the market. The mail goal of thi study is to analyse some options for integrating artificial intelligence into the corporate management system, to explore the impact on the quality of management decisions, and to identify the main disadvantages and threats of using artificial intelligence models in corporate management. The following methods were used in the research process: literature review and systematization of knowledge, empirical analysis, case study and optimization method. The study in question provides a detailed examination of the application of Machine Learning (ML) and Deep Learning (DL) in a number of key areas of corporate management, including shareholder relations, forecasting, process optimization, risk management, and human resources management. A key finding of the study is that AI enables companies to gain deeper insights into their customers, markets, and internal processes through data analysis. This, in turn, facilitates the development of personalized products and services, optimization of marketing campaigns, and enhancement of customer loyalty and stakeholder understanding. However, the authors of the article also highlight several challenges associated with the implementation of AI, including: data quality (the effectiveness of an AI system directly depends on the quality and quantity of data used for training the models); transparency of algorithms: (the complexity of Machine Learning and Deep Learning models often complicates the understanding of the reasons behind specific outcomes, which can lead to skepticism about the reliability of artificial intelligence systems). The social implications of AI are multifaceted and warrant further investigation. The use of AI may give rise to moral issues, including discrimination, bias, and job displacement. For the successful implementation of AI in corporate management, the authors offer a number of recommendations, including investing in the development of data infrastructure, attracting qualified specialists, developing clear strategies and policies for the use of AI, as well as constant monitoring and evaluation of the effectiveness of AI systems.

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Publication Details

Journal
ECONOMICS FINANCE AND MANAGEMENT REVIEW
Published
2024-12-30
DOI
https://doi.org/10.36690/2674-5208-2024-4-68-79
Citations
1
Primary Topic
Economic and Technological Systems Analysis
Type
article
Field-Weighted Citation Impact
0.73
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article

INTEGRATION OF ARTIFICIAL INTELLIGENCE INTO THE CORPORATE MANAGEMENT SYSTEM

Yevheniia Khaustova, Т. В. Рябокiнь
1 citations
ECONOMICS FINANCE AND MANAGEMENT REVIEW
Economic and Technological Systems Analysis
0.73
article

INTEGRATION OF ARTIFICIAL INTELLIGENCE INTO THE CORPORATE MANAGEMENT SYSTEM

Yevheniia Khaustova, Т. В. Рябокiнь
article en
1 citations

Abstract

The article examines the potential of Artificial Intelligence (AI), with a focus on Machine Learning (ML) and Deep Learning (DL), in the domain of corporate management. A review of the literature and existing practices reveals that AI has the potential to significantly transform traditional business processes, enhance decision-making efficiency, and provide corporations with substantial competitive advantages in the market. The mail goal of thi study is to analyse some options for integrating artificial intelligence into the corporate management system, to explore the impact on the quality of management decisions, and to identify the main disadvantages and threats of using artificial intelligence models in corporate management. The following methods were used in the research process: literature review and systematization of knowledge, empirical analysis, case study and optimization method. The study in question provides a detailed examination of the application of Machine Learning (ML) and Deep Learning (DL) in a number of key areas of corporate management, including shareholder relations, forecasting, process optimization, risk management, and human resources management. A key finding of the study is that AI enables companies to gain deeper insights into their customers, markets, and internal processes through data analysis. This, in turn, facilitates the development of personalized products and services, optimization of marketing campaigns, and enhancement of customer loyalty and stakeholder understanding. However, the authors of the article also highlight several challenges associated with the implementation of AI, including: data quality (the effectiveness of an AI system directly depends on the quality and quantity of data used for training the models); transparency of algorithms: (the complexity of Machine Learning and Deep Learning models often complicates the understanding of the reasons behind specific outcomes, which can lead to skepticism about the reliability of artificial intelligence systems). The social implications of AI are multifaceted and warrant further investigation. The use of AI may give rise to moral issues, including discrimination, bias, and job displacement. For the successful implementation of AI in corporate management, the authors offer a number of recommendations, including investing in the development of data infrastructure, attracting qualified specialists, developing clear strategies and policies for the use of AI, as well as constant monitoring and evaluation of the effectiveness of AI systems.

ECONOMICS FINANCE AND MANAGEMENT REVIEW(4(20))
Kyiv National University of Technologies and Design (UA)
Peace, Justice and strong institutions
Openalex Percentile: Top 20%
Economic and Technological Systems Analysis
0.73
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