Making Management Decisions Based on the Method of Expert Assessments When Choosing a Counterparty

This article discusses how introducing expert assessment methods into management decisions helps to improve efficiency and reduce the organization’s costs, emphasizing the study relevance. The article also discusses how the application of machine learning methods in management decisions is a significant step forward in improving the decision-making accuracy. Machine learning, as part of artificial intelligence, provides tools and algorithms for analyzing large amounts of data, identifying hidden patterns and predicting future trends. In management practice, this opens up new opportunities for optimizing processes, improving strategic planning and increasing the organizations’ competitiveness. The paper shows that machine-learning algorithms can automate routine tasks, analyze customer data to personalize services, forecast demand and manage supply chains, assess risks and detect fraud; also, they can influence the decision-making psychology by the organization’s management, reducing subjective human factors. Thus, using machine-learning algorithms allows managers to obtain more accurate and timely analytical data, which contributes to making informed decisions. The article concludes by discussing the challenges associated with introducing machine learning methods into management decisions. These include the need for high-quality data collection and processing, ensuring the security and confidentiality of information, and the necessity for specialized knowledge and skills to develop and interpret artificial intelligence models. In addition, it is important to consider the ethical aspects and possible social consequences of automated decisions. Thus, integrating machine-learning methods into management practice requires a comprehensive approach that includes technical training, organizational changes, and attention to ethical issues. When applied correctly, machine-learning methods can become a powerful tool for improving management efficiency and achieving organizations’ strategic goals.