Introduction. AI is actively being implemented in various areas of economic activity, automating routine processes, reducing manual labour and increasing productivity. Current market trends indicate that the growing share of Generation Z and Alpha employees will contribute to even greater automation, as it is the younger generation that positively perceives the replacement of humans with technology in the performance of repetitive tasks.
Problem statement. Despite the active interest of businesses in the possibilities of using artificial intelligence in their activities, companies still lack sufficient knowledge and understanding of how AI can be used — comprehensively or fragmentarily, improving the work of individual departments or the enterprise as a whole, what resources are needed for this and what the results will be, what data is needed for AI to work in a particular company, and how accurate the results of artificial intelligence are, etc. These issues need to be addressed in order to develop an understanding of a systematic approach to the application of artificial intelligence in the activities of an enterprise, starting with marketing forecasting processes and ending with the resulting optimisation of resource use and increased competitiveness of the company.
Purpose. The purpose of the article is to present a comprehensive approach to the application of artificial intelligence in the work of an enterprise, to identify problematic issues in the application of AI and the advantages of its use in all areas of the company’s activities in order to optimise the use of its resources and, as a result, gain competitive advantages in the market.
Materials and methods. To achieve the objective of the study, the following methods were used: the method of analysis and synthesis to study literary sources and publications, the comparative method to compare traditional forecasting methods with approaches based on artificial intelligence, and a systematic approach to consider artificial intelligence as a tool that comprehensively affects all areas of the enterprise’s activities.
Results. Particular attention is paid to the use of AI in marketing forecasting as a key element of enterprise planning. The advantages of using modern forecasting methods, in particular based on Big Data and machine learning, compared to traditional statistical approaches are described. The practical aspects of applying S&OP to improve the management of production resources, supply and personnel are highlighted. The paper highlights the importance of quality forecasts for operational planning, resource provision, logistics decisions and demand management. Traditional statistical forecasting methods are compared with approaches based on Big Data and machine learning. The latter enable higher accuracy, reveal complex interrelationships and respond quickly to changes in the market environment. Attention is also focused on the need for high-quality information support and qualified personnel for the effective use of these technologies.
It is argued that the use of AI provides flexibility, accuracy, and speed in decision-making and contributes to improving the efficiency of enterprises in areas such as inventory management, customer service, resource optimisation, pricing, and profitability. A comprehensive approach to the implementation of AI to achieve the strategic goals of the enterprise is outlined.
Conclusions. It has been proven that the comprehensive implementation of AI is an effective tool for ensuring flexible management, increasing efficiency, and achieving strategic goals of enterprises in today’s dynamic market environment.
