AI as Strategist

Joshua Gans

No 33650, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: This paper examines the role of artificial intelligence as a strategist in organizational decision-making by extending van den Steen's formal theory of strategy. A mathematical model is developed comparing AI and human strategists across different decision contexts, focusing on how each type generates confidence, achieves agreement, and implements decisions through control versus influence. The analysis presumes that AI excels in data-rich domains but faces credibility challenges in judgment-intensive contexts, creating a counterintuitive result where AI requires less formal authority precisely where it demonstrates superior analytical capabilities. The paper identifies distinct mechanisms through which strategic value is created: direct decision quality improvement and enhanced coordination. The authors propose domain-contingent approaches to AI integration, including differentiated authority systems across decision types and progressive control models that evolve as AI demonstrates effectiveness. These findings contribute to strategy theory while providing practical guidance for organizations seeking to effectively integrate AI into strategic processes, highlighting that organizations must adapt to their strategists' capabilities as much as strategists must match their organizations.

JEL-codes: D81 L20 O32 (search for similar items in EconPapers)
Date: 2025-04
Note: PR
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