Artificial Intelligence in the Strategic Management of International Companies under Global Uncertainty

Abstract

The relevance of the study stems from the growing strategic role of artificial intelligence under conditions of global uncertainty, geoeconomic fragmentation, regulatory pressure, cyber risks, and the growing unpredictability of global value chains. In this context, international companies increasingly require strategic management systems capable of processing heterogeneous information, preparing alternative courses of action, and preserving human responsibility for final strategic decisions. The purpose of the article is to clarify the role of artificial intelligence in the strategic management of international companies under global uncertainty and to substantiate the organizational mechanisms through which AI can strengthen adaptability, analytical capacity, and the timely revision of strategic decisions without replacing human strategic judgment. Methods. The methodological design combines qualitative document analysis, comparative case study, generalization, systematization, comparison, synthesis, and analysis. The theoretical basis includes recent scholarly publications from 2024-2026 on strategic decision-making, international business, scenario planning, dynamic capabilities, human-AI interaction, and risk governance in the deployment of intelligent systems. The empirical corpus consists of official corporate documents issued by Microsoft, DHL Group, SAP, and Unilever, including annual and integrated reports, as well as corporate materials on responsible AI, digital transformation, and the redesign of global operating processes. Results. The article argues that the most methodologically cautious interpretation of artificial intelligence is not as an autonomous strategist, but as an adaptive infrastructure supporting strategic management. Based on the literature review and comparative corporate case analysis, four interconnected contours of strategic AI use are identified: continuous monitoring of the external and internal environment, analytical processing of weak and strong signals, scenario modeling of strategic alternatives, and managerial interpretation of outputs. The comparative document-based case analysis shows that, in the international companies under review, AI is most frequently integrated into three strategic domains: forecasting and planning, redesign of the operating model, and corporate governance, control, and ethics systems. The findings indicate that strategic value is generated not by isolated algorithms, but by the combination of AI with high-quality corporate data, integrated digital platforms, cross-functional coordination, managerial capability development, and formalized rules for responsible use. Conclusions. The article argues that, under global uncertainty, artificial intelligence should be understood as a tool for accelerating the strategic cycle, broadening the horizon of analysis, increasing organizational sensitivity to environmental change, and preparing better managerial alternatives. At the same time, its effectiveness depends not only on technological sophistication, but also on the company's digital maturity, data quality, governance architecture, and the ability of top management to critically combine algorithmic outputs with professional strategic judgment. The results may serve both as a theoretical basis for further empirical research and as a practical reference point for international companies redesigning their strategic management systems in response to AI-driven transformation.