Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/323494 
Authors: 
Year of Publication: 
2024
Citation: 
[Journal:] Management Review Quarterly [ISSN:] 2198-1639 [Volume:] 75 [Issue:] 2 [Publisher:] Springer International Publishing [Place:] Cham [Year:] 2024 [Pages:] 1-45
Publisher: 
Springer International Publishing, Cham
Abstract: 
Abstract The early detection of discontinuous change plays a decisive role in the performance and competitiveness of organizations. Whether and how top managers perceive change is mostly determined by their attention. However, research has shown that many top managers are often unable to allocate their attention properly and may therefore react with inertia or not at all to relevant changes. This raises the question of how managerial attention can be influenced to make top managers more receptive to discontinuous changes. A promising approach to this problem may come from the growing research field on the impact of AI on strategic decision-making. In this paper, I provide a conceptual framework of how the use of AI might help top managers better focus their attention on discontinuous change. Based on a systematic literature review and an attentional model, I highlight factors that influence top managers' attention allocation and likely enhance or inhibit it through the use of AI. This allows me to derive propositions for the application of AI in discontinuous change detection that can serve as a starting point for future empirical research. My paper contributes to broadening the research field of AI in the area of managerial attention.
Subjects: 
Managerial attention
Discontinuous change
Artificial intelligence
Strategic management
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Creative Commons License: 
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Document Type: 
Article
Document Version: 
Published Version
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