Strategic Decision-Making in the AI Era: An Integrated Approach Classical, Adaptive, Resource-Based, and Processual Views

Abstract

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.

Keywords

• Strategic Decision-Making
• Artificial Intelligence
• AI-Driven Strategy
• Classical School
• Adaptive School
• Resource-Based View
• Processual School
• Decision Support Systems.

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