This study explores how artificial intelligence (AI) can enhance strategic decision-making by integrating with four established strategic schools: Classical, Adaptive, Resource-Based, and Processual. While AI improves data-driven insights, it lacks the strategic foresight, contextual awareness, and ethical judgment inherent in traditional frameworks. Using a structured literature review, this conceptual study evaluates the synergy between AI and strategic schools. Sources were selected from peer-reviewed databases, including Scopus and Web of Science, using keywords such as "AI-driven strategy," "strategic management," and "decision support systems." The findings reveal that AI enhances Classical strategy through predictive analytics and scenario planning, strengthens Adaptive strategy via real-time responsiveness, supports RBV by optimizing resource identification, and complements Processual strategy by facilitating continuous learning. However, AI’s limitations in handling tacit knowledge, ethical considerations, and contextual judgment highlight the need for human oversight. This study proposes a hybrid framework where AI supports, rather than replaces, strategic decision-making. It offers actionable recommendations for business leaders, including AI-powered strategy frameworks, governance policies for ethical AI deployment, and human-AI collaboration to navigate dynamic business environments effectively.
Strategic Decision-Making Artificial Intelligence AI-Driven Strategy Classical School Adaptive School Resource-Based View Processual School Decision Support Systems.
This study explores how artificial intelligence (AI) can enhance strategic decision-making by integrating with four established strategic schools: Classical, Adaptive, Resource-Based, and Processual. While AI improves data-driven insights, it lacks the strategic foresight, contextual awareness, and ethical judgment inherent in traditional frameworks. Using a structured literature review, this conceptual study evaluates the synergy between AI and strategic schools. Sources were selected from peer-reviewed databases, including Scopus and Web of Science, using keywords such as "AI-driven strategy," "strategic management," and "decision support systems." The findings reveal that AI enhances Classical strategy through predictive analytics and scenario planning, strengthens Adaptive strategy via real-time responsiveness, supports RBV by optimizing resource identification, and complements Processual strategy by facilitating continuous learning. However, AI’s limitations in handling tacit knowledge, ethical considerations, and contextual judgment highlight the need for human oversight. This study proposes a hybrid framework where AI supports, rather than replaces, strategic decision-making. It offers actionable recommendations for business leaders, including AI-powered strategy frameworks, governance policies for ethical AI deployment, and human-AI collaboration to navigate dynamic business environments effectively.
Strategic Decision-Making Artificial Intelligence AI-Driven Strategy Classical School Adaptive School Resource-Based View Processual School Decision Support Systems.
Primary Language | English |
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Subjects | Strategy, International Business |
Journal Section | Theoretical Article |
Authors | |
Early Pub Date | February 26, 2025 |
Publication Date | February 28, 2025 |
Submission Date | February 11, 2025 |
Acceptance Date | February 26, 2025 |
Published in Issue | Year 2025 Volume: 9 Issue: 17 |
Dergide aşağıdaki alanların kapsamına giren nitelikli çalışmalar yayımlanabilir;
İşletme, İktisat, Çalışma Ekonomisi ve Endüstri İlişkileri, Maliye, Kamu Yönetimi, Uluslararası İlişkiler ve Siyaset Bilimi, Ekonometri, Yönetim Bilişim Sistemleri, Eğitim Yönetimi, Sağlık Yönetimi, Turizm Yönetimi, Havacılık Yönetimi, Denizcilik İşletmeleri Yönetimi, Mühendislik ve Teknoloji Yönetimi, Enerji Yönetimi, Lojistik Yönetimi, Çevre Yönetimi, Medya ve İletişim Yönetimi, Afet Yönetimi, Multidisipliner Yönetim ve Ekonomi Çalışmaları.
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