Investigating Executive Leadership Responses to AI-Induced Structural Change in Multinational Corporations-2025

This review examines how executive leaders in multinational corporations navigate the structural upheavals triggered by artificial intelligence adoption. Drawing on scholarly literature published between 2015 and 2025, we identify five distinct response patterns through which executives address AI-induced transformation: strategic realignment, organizational restructuring, leadership style adaptation, workforce transformation management, and governance framework development. Our analysis reveals that successful executive responses share common characteristics they address multiple organizational levels simultaneously, establish proactive governance mechanisms, and pursue balanced integration of human and AI capabilities rather than simple automation. The evidence suggests substantial efficiency improvements accompany AI-driven restructuring, though workforce displacement rates vary considerably across industries and organizational contexts. Critical gaps persist in understanding how cultural contexts shape leadership responses, particularly in Africa and other underrepresented regions where infrastructure constraints, regulatory environments, and cultural values create distinct challenges. Similarly, questions remain about the long-term sustainability of AI-induced structural changes and the ethical frameworks executives employ when making consequential decisions about workforce and organizational transformation. This review contributes an integrated theoretical framework that synthesizes organizational change theory, technology adoption models, leadership paradigms, and institutional perspectives. For practitioners, we offer evidence-based guidance highlighting the importance of comprehensive change programs, experimental learning approaches, substantial workforce investment, and early establishment of robust governance structures. The ultimate contribution lies in advancing scholarly understanding while providing actionable insights for executives, boards, and policymakers navigating AI transformation in increasingly complex multinational environments.