This study explores AI's role in driving organizational change in management research, suggesting solutions to overcome identified challenges.
Artificial intelligence (AI) technology is profoundly reshaping the global management ecosystem, transforming its role from a tool for efficiency to a structural force driving organizational change. This study, grounded in the context of China's modernization, systematically explores the multidimensional applications of AI technology in management research and the challenges it faces. The study finds core challenges in the current management field, including a crisis of adaptability between the industrial-era paradigm and the intelligent ecosystem, the dissipation of governance effectiveness caused by algorithmic black boxes, and cognitive barriers to human-machine collaboration. These issues stem from the conflict between mechanistic cognition and complex systems, the imbalance between instrumental and value rationality, and the paradigmatic differences between biological and machine intelligence. To address these challenges, the study proposes three solutions: building an AI-enabled distributed dynamic knowledge network, establishing a hierarchical and transparent governance system, and developing cognitive coupling interfaces. This research not only provides new perspectives for innovation in management theory but also offers practical paths for AI management practice in the Chinese context.
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Ning et al. (2025) studied this question.
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