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Implementation Path of Enterprise Strategic Decision Making Based on Generative Large Model

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  • Wang, Gang

Abstract

This paper explores the integration of generative large models into enterprise strategic decision-making. Combining theoretical analysis with empirical research, it highlights the practical value of these AI models in improving decision-making efficiency and accuracy. By processing vast and diverse data, generative models help organizations uncover hidden patterns and generate actionable insights, reducing risks and accelerating decision cycles. The study also discusses critical factors for successful adoption, including strategic alignment, data quality, and organizational readiness. Key implementation strategies and recommendations are provided to overcome common challenges. Overall, the paper offers valuable guidance for leveraging generative large models to enhance corporate strategy and competitiveness in a rapidly evolving business environment.

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  • Wang, Gang, 2025. "Implementation Path of Enterprise Strategic Decision Making Based on Generative Large Model," GBP Proceedings Series, Scientific Open Access Publishing, vol. 6(None), pages 110-117.
    • Handle: RePEc:axf:gbppsa:v:6:y:2025:i:none:p:110-117
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