Can AI Do Strategy?

Can artificial intelligence (AI) do strategy? This question is both urgent and foundational: urgent because AI is already reshaping strategic practice and foundational because answering it forces us to articulate what strategy actually is. In this introductory essay to the Strategy Science Special Issue on AI and Strategy, we propose a dual-ladder framework: a causal ladder that maps the cognitive hierarchy of strategic tasks and a delegation ladder that specifies when organizations will grant AI autonomy over those tasks. A core insight emerges: AI will not enter strategy where required reasoning is deepest but where its performance is most measurable. We organize the Special Issue contributions around what AI can do today, could do as capabilities develop, and should do given the imperatives of accountability and human judgment. We close with a challenge and an invitation: if strategy scholars do not define good strategizing precisely enough to be encoded, tested, and refined, other disciplines will, embedding thinner conceptions of strategy into the tools managers use. Teaching machines to strategize and support strategizing is ultimately a method for rediscovering what strategy is.

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Publication Details

Journal
Strategy Science
Published
2026-03-12
DOI
https://doi.org/10.1287/stsc.2026.intro.v11.n1
Primary Topic
Innovation, Sustainability, Human-Machine Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Can AI Do Strategy?

Peter Zemsky, Felipe A. Csaszar, Todd Zenger, G. S. Lee
Strategy Science
Innovation, Sustainability, Human-Machine Systems
article

Can AI Do Strategy?

Peter Zemsky, Felipe A. Csaszar, Todd Zenger, G. S. Lee
article en

Abstract

Can artificial intelligence (AI) do strategy? This question is both urgent and foundational: urgent because AI is already reshaping strategic practice and foundational because answering it forces us to articulate what strategy actually is. In this introductory essay to the Strategy Science Special Issue on AI and Strategy, we propose a dual-ladder framework: a causal ladder that maps the cognitive hierarchy of strategic tasks and a delegation ladder that specifies when organizations will grant AI autonomy over those tasks. A core insight emerges: AI will not enter strategy where required reasoning is deepest but where its performance is most measurable. We organize the Special Issue contributions around what AI can do today, could do as capabilities develop, and should do given the imperatives of accountability and human judgment. We close with a challenge and an invitation: if strategy scholars do not define good strategizing precisely enough to be encoded, tested, and refined, other disciplines will, embedding thinner conceptions of strategy into the tools managers use. Teaching machines to strategize and support strategizing is ultimately a method for rediscovering what strategy is.

Strategy Science
Purdue University West Lafayette (US), University of Utah (US), University of Michigan (US), Ross School (US), INSEAD (AE)
Peace, Justice and strong institutions
Openalex Percentile: Top 30%
Innovation, Sustainability, Human-Machine Systems
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