Waves of Progress: The Cyclical History of Artificial Intelligence in Management and Organizations

Abstract

This article examines the historical development of Artificial Intelligence (AI) in management and organizational studies and practices through a wave framework, shedding light on the cyclical nature of technological progress, academic contributions, and organizational adoption. By analyzing five distinct waves—symbolic AI, the AI Winter, the resurgence of machine learning, the big data era, and the emerging phase of human-AI collaboration—it uncovers recurring misalignments among these elements. The study highlights how periods of stagnation, often driven by overhyped expectations or theoretical gaps, have been followed by transformative innovations that reshaped decision-making and organizational processes. The findings stress the importance of adaptive strategies to address ethical challenges, trust issues, and organizational preparedness. This work enhances theory by deepening the understanding of AI's influence on organizational thought and practices, identifies key research directions for future exploration, and provides actionable insights for practitioners and policymakers to effectively navigate the complexities of AI integration.

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