HARNESSING GENERATIVE AI TO BRIDGE OCCUPATIONAL SAFETY AND BUSINESS ANALYTICS: A PEDAGOGICAL AND ECONOMIC PERSPECTIVE

Occupational Safety and Environmental Health (OSEH) is increasingly recognized as a strategic business concern rather than a purely regulatory function. However, traditional instructional approaches often fail to connect safety decisions with business analytics and economic outcomes. This study introduces an AI-enabled pedagogical framework that uses generative artificial intelligence to integrate OSEH concepts into business education. Generative AI supports experiential learning through adaptive case studies, interactive simulations, and real-time financial modeling of safety decisions. Students evaluate tradeoffs between proactive safety investments and reactive cost exposure while receiving immediate analytical feedback. Findings highlight three core educational benefits: enhanced active learning, strengthened business relevance, and improved cross-disciplinary analytical competence. By positioning safety decisions within a business analytics context, the approach prepares future managers to make informed, economically sound decisions that support workforce stability and organizational performance. The study demonstrates that generative AI offers an effective mechanism for modernizing OSEH instruction within business curricula.