Paper Title
Aligning AI Models with Strategic Management Schools: A Framework for Decision-Making

Abstract
As artificial intelligence (AI) increasingly shapes organizational strategy, understanding how different AI models align with established strategic management schools offers valuable insights. This paper explores the relationship between four strategic schools—Classical, Adaptive, Resource-Based, and Processual—and prominent AI models, demonstrating how each AI system embodies distinct strategic principles. We examine well-known models like ChatGPT, AlphaGo, IBM Watson, and rule-based expert systems, showing how their decision-making processes align with specific strategic philosophies. For instance, ChatGPT’s iterative learning reflects the Processual School’s adaptive approach, while AlphaGo’s real-time responsiveness aligns with the Adaptive School’s emphasis on flexibility. IBM Watson exemplifies the Resource-Based View (RBV) by leveraging unique internal resources, while rule-based systems mirror the Classical School’s structured planning. This framework provides guidance for selecting AI models based on organizational strategy, highlighting the importance of aligning AI capabilities with strategic goals to maximize decision-making effectiveness.