Paper Type
ERF
Abstract
The integration of open strategy and artificial intelligence (AI) in strategic decision-making presents both opportunities and challenges for organisations. While open strategy fosters transparency and inclusiveness by engaging internal and external stakeholders, AI enhances strategic analysis and formulation through data-driven insights. However, these approaches also introduce concerns about managerial control, as they can redistribute decision-making authority, reduce strategic differentiation, and challenge competitive advantage. This study examines the impact of managerial control levels on the effectiveness of AI-enabled and open strategy approaches. Using a 2×2+1 experimental design, strategy experts are assigned to different strategy-making conditions (open, closed, or AI-generated) under high or low managerial control settings. The findings will contribute to understanding how varying levels of control influence the quality and adaptability of strategic outcomes, offering practical insights for organisations navigating the evolving landscape of AI-driven and open strategic processes.
Paper Number
1272
Recommended Citation
Amrollahi, Alireza, "Who is in Charge? Examining the role of managerial control in AI-enabled and open strategy-making" (2025). AMCIS 2025 Proceedings. 2.
https://aisel.aisnet.org/amcis2025/scuidt/scuidt/2
Who is in Charge? Examining the role of managerial control in AI-enabled and open strategy-making
The integration of open strategy and artificial intelligence (AI) in strategic decision-making presents both opportunities and challenges for organisations. While open strategy fosters transparency and inclusiveness by engaging internal and external stakeholders, AI enhances strategic analysis and formulation through data-driven insights. However, these approaches also introduce concerns about managerial control, as they can redistribute decision-making authority, reduce strategic differentiation, and challenge competitive advantage. This study examines the impact of managerial control levels on the effectiveness of AI-enabled and open strategy approaches. Using a 2×2+1 experimental design, strategy experts are assigned to different strategy-making conditions (open, closed, or AI-generated) under high or low managerial control settings. The findings will contribute to understanding how varying levels of control influence the quality and adaptability of strategic outcomes, offering practical insights for organisations navigating the evolving landscape of AI-driven and open strategic processes.
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