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Eduard Merc, University of Hawaiʻi at Mānoa, United StatesAbstract
Artificial intelligence (AI) is rapidly transforming organizational decision-making processes, yet undergraduate business education has been slower to systematically integrate AI-supported decision making into its curricula. While students are increasingly exposed to analytics tools, there remains a gap in how these tools are structured within a coherent decision-making approach that combines data-driven insights with human judgment, ethical considerations, and contextual awareness. This paper proposes the DIAL (Decision Intelligence with AI Learning) Framework, which conceptualizes decision making as a multi-layered process consisting of input, process, and output components. At the input level, students develop data literacy and engage with AI tools to generate, interpret, and contextualize insights. The process level emphasizes the central role of human judgment and ethical awareness in critically evaluating AI-generated outputs, mitigating potential biases, and ensuring responsible and context-sensitive decision making. At the output level, the framework focuses on improving decision quality and enhancing business impact in real-world organizational settings. The framework is informed by teaching practices and industry experience in a diverse higher education environment in the State of Hawaiʻi, USA, highlighting the importance of culturally relevant, applied, and student-centered learning contexts. The DIAL Framework contributes to business education by offering a structured and scalable approach to integrating AI into decision-making instruction and provides a foundation for future empirical research on AI-supported learning in higher education and workforce preparation.
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