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dc.contributor.authorKhaustova, Yevgeniia-
dc.contributor.authorRiabokin, Taras-
dc.date.accessioned2025-11-06T09:52:54Z-
dc.date.available2025-11-06T09:52:54Z-
dc.date.issued2024-
dc.identifier.citationKhaustova Y. Integration of Artificial Intelligence into the Corporate Management System / Y. Khaustova, T. Riabokin // Economics, Finance and Management Review. - 2024. - № 4 (20). - P. 68–79.uk
dc.identifier.issn2674-5208uk
dc.identifier.urihttps://er.knutd.edu.ua/handle/123456789/31680-
dc.description.abstractThe 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.uk
dc.language.isoenuk
dc.subjectArtificial intelligenceuk
dc.subjectgovernance solutionsuk
dc.subjectcorporate managementuk
dc.subjectMachine learninguk
dc.subjectMachine learninguk
dc.subjectbusiness process automationuk
dc.subjectDeep learninguk
dc.subjectBig data;uk
dc.titleIntegration of Artificial Intelligence into the Corporate Management Systemuk
dc.title.alternativeІнтеграція штучного інтелекту в систему корпоративного управлінняuk
dc.typeArticleuk
local.contributor.altauthorХаустова, Євгенія-
local.contributor.altauthorРябокінь, Тарас-
local.subject.sectionЕкономіка, фінанси, менеджментuk
local.sourceEconomics, Finance and Management Reviewuk
local.subject.facultyФакультет управління та бізнес-дизайнуuk
local.identifier.sourceЗарубіжні виданняuk
local.subject.departmentКафедра смарт-економікиuk
local.identifier.doi10.36690/2674- 5208-2024-4-68-79uk
local.identifier.urihttps://public.scnchub.com/efmr/index.php/efmr/article/view/311uk
local.subject.method1uk
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