Artificial intelligence in adaptive strategy creation and implementation: Toward enhanced attentional control in strategy processes

This article focuses on the deployment of proprietary artificial intelligence (AI) systems in strategy creation and implementation processes, with a specific focus on their role in enhancing organizational attentional control. By employing the attention-based view (ABV) as an overarching theoretical framework, we examine how company-specific AI systems trained on proprietary data can support strategy processes. We identify three key contributions of AI in strategy creation and implementation processes: (1) broadening organizational attention to external and internal developments, (2) democratizing strategic processes through improved transparency and inclusivity, and (3) accelerating feedback loops with real-time monitoring of strategy implementation progress. Potential challenges associated with the deployment of AI systems for attentional control are also addressed. The paper concludes by putting forward potential directions for future research.

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Publication Details

Journal
Long Range Planning
Published
2025-06-17
DOI
https://doi.org/10.1016/j.lrp.2025.102561
Citations
9
Primary Topic
Cognitive Science and Mapping
Type
article
Field-Weighted Citation Impact
22.33

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article

Artificial intelligence in adaptive strategy creation and implementation: Toward enhanced attentional control in strategy processes

Tomi Laamanen, Ann‐Kristin Weiser, William Ocasio, Georg von Krogh
9 citations
Long Range Planning
Cognitive Science and Mapping
22.33
article

Artificial intelligence in adaptive strategy creation and implementation: Toward enhanced attentional control in strategy processes

Tomi Laamanen, Ann‐Kristin Weiser, William Ocasio, Georg von Krogh
article en
9 citations

Abstract

This article focuses on the deployment of proprietary artificial intelligence (AI) systems in strategy creation and implementation processes, with a specific focus on their role in enhancing organizational attentional control. By employing the attention-based view (ABV) as an overarching theoretical framework, we examine how company-specific AI systems trained on proprietary data can support strategy processes. We identify three key contributions of AI in strategy creation and implementation processes: (1) broadening organizational attention to external and internal developments, (2) democratizing strategic processes through improved transparency and inclusivity, and (3) accelerating feedback loops with real-time monitoring of strategy implementation progress. Potential challenges associated with the deployment of AI systems for attentional control are also addressed. The paper concludes by putting forward potential directions for future research.

Long Range PlanningVol. 58(4)
University of Illinois Urbana-Champaign (US), University of St.Gallen (CH), ETH Zurich (CH)
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Openalex Percentile: Top 1%
Cognitive Science and Mapping
22.33
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