Proceedings of the International scientific and practical conference ―Cambridge Science and Education Conference‖ (May 15-17, 2026) / Publisher website: www.naukainfo.com. - Cambridge, United Kingdom, 2026. - 429 p.

39 The contemporary stage of cost management development is characterized by a transition from traditional accounting-based control toward a more strategic, digital, and predictive approach. Whereas cost management previously relied primarily on the analysis of retrospective data and cost accounting control, today many large enterprises, particularly in digitally advanced industries, are increasingly shifting toward the adoption of artificial intelligence, big data analytics, and automated decision-support systems. An emerging analytical perspective, referred to as a research stream extending Strategic Cost Management through AI-driven analytics, is taking shape, within which costs are viewed as an integral component of the strategic management of resources and enterprise competitiveness. One of the most important contemporary directions is AI-assisted Cost Management (AI-enhanced Cost Management), i.e., cost management supported by artificial intelligence. Modern AI systems are capable of forecasting future expenditures, detecting anomalies in resource utilization, supporting optimization and decision-making processes in cost management, and enabling scenario analysis of managerial decisions, as well as providing near real-time monitoring of business process efficiency in digitally mature organizations. Research indicates that AI significantly enhances the effectiveness of strategic management of enterprise technologies and resources; however, the human-AI collaboration model is generally considered the most effective approach, in which strategic decision-making remains the responsibility of management. [1, 2, 6] Traditional cost management systems were based on periodic reporting and had a retrospective character. Modern digital technologies provide opportunities for near real-time cost management, enabling enterprises to manage costs continuously and dynamically in advanced digital implementations. ERP systems, IoT technologies, cloud analytics, and predictive analytics allow companies in highly digitalized enterprises to identify cost overruns in near real time, forecast deviations, analyze process efficiency, and promptly adjust managerial decisions. This significantly transforms the nature of cost management from a periodic reporting function into a continuous, data-driven analytical and decision-support process. [3, 4]