The Impact of Artificial Intelligence on Strategic Decision-Making in Business Administration: An Analytical Study Including Educational and Business Environments
The Impact of Artificial Intelligence on Strategic Decision-Making in Business Administration: An Analytical Study Including Educational and Business Environments

Summary/Abstract: Background/purpose. The study examined the impact of artificial intelligence on strategic decision-making in business management, focusing on Educational and Business Environments, with a particular emphasis on internal capabilities, organizational readiness, ethical considerations, and regional contextual factors that affect AI integration. Materials/methods. A mixed-methods approach that combines quantitative and qualitative approaches. Purposive sampling of businesses from different industries and geographical areas that employ AI in strategic decision-making. Data were collected through semi-structured interviews with professionals from nine diverse work environments, including Jordan, Germany, Saudi Arabia, and the United States. Results. The findings reveal that most businesses are still in the planning phase of AI adoption, with limited strategic implementation and reliance on machine learning and predictive analytics in operational tasks. The majority of businesses are still in the planning phase of AI adoption, with limited strategic use and reliance on predictive analytics and machine learning in day-to-day operations. Organizations often lack the necessary frameworks, technical expertise, and strategic alignment to fully leverage AI technologies, despite growing awareness. Despite the widespread use of AI in educational institutions, many lack infrastructure for staff training. Conclusion. Lack of ethical frameworks, low employee AI literacy, and difficulty tailoring AI tools to specific industries are among the main obstacles. To facilitate successful AI integration, the study recommends enhancing employee training, establishing moral guidelines, and coordinating internal and external resources.

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