This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: A practitioner article published in the SMS Explorer, "AI Will Help Formulate Strategy, But Should Never Finish It," by Michael Olenick challenges a growing assumption in the business world: that generative AI can take strategy off executives' plates. As AI tools grow more capable, the debate has shifted from whether AI can contribute to strategy to whether it should lead it.
Olenick, drawing on more than two decades of AI-aided strategy research, argues it should not—and explains precisely where the line must be drawn. The article examines the role generative AI can—and cannot—play in the strategy process, drawing on Olenick's development of VSTRAT, an AI-aided strategy system he first built in 2002 and later advanced as a research fellow at INSEAD. The piece references published findings that large language models can generate and evaluate strategies at levels comparable to entrepreneurs and investors while insisting that the ability to produce strategic outputs is not the same as the authority to commit to them.
Olenick developed this perspective over two decades of building, testing and commercializing AI strategy tools—experience that, he argues, has made him acutely attentive to where AI-aided strategy reaches its limits. The central problem, he contends, is not that AI lacks analytical power but that it lacks accountability. Only the people who must execute a strategy and answer for its outcomes can legitimately make the final commitment.
The article's core argument draws on Adner and Zemsky's foundational research in the Strategic Management Journal, which established that supply-side technology creates advantage only through the consumer value it unlocks—making it catalytic, not competitive. Applied to generative AI, this logic yields a clear rule: AI everywhere in the strategy process, AI nowhere in the strategy decision. Like production equipment inside a Cirque du Soleil show, AI becomes indispensable to enabling the outcome without ever becoming the value itself.
For strategic leaders, the article identifies five practical implications: using AI for the grinding work of data gathering and option generation; deploying AI-simulated stakeholders to pressure-test strategies before the boardroom; requiring citation-backed outputs rather than accepting model authority; maintaining named human accountability for every strategic commitment; and building review processes that reward overriding flawed AI recommendations to prevent the quiet erosion of judgment. For executives navigating the rapid adoption of AI tools across their organizations, the article offers both a permission structure and a warning. Organizations that deploy AI throughout the strategy process will out-analyze those that do not.
But the moment a firm lets AI make the final call, it has not accelerated strategy—it has abdicated it. Ron Adner et al, A demand‐based perspective on sustainable competitive advantage, Strategic Management Journal (2026). DOI: 10.1002/smj.513 Journal information: Strategic Management Journal Provided by Strategic Management Society MA in English, copy editor since 2021 with experience in higher education and health content.
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