The Empowering Mechanisms and Challenges of Generative AI for Business Management Innovation – A Case Study Based on Multi-Scenario Applications of GAI

The rapid advancement of Generative Artificial Intelligence (GAI) is profoundly reshaping the underlying logic and operational modes of enterprise management. Unlike traditional artificial intelligence, GAI not only analyzes and comprehends data but also possesses capabilities such as multimodal content generation, natural language interaction, and adaptive evolution, opening up entirely new possibilities for management innovation. This paper systematically reviews the technological evolution and core capability characteristics of GAI, and reveals the micro‑mechanisms through which GAI enables management innovation from three dimensions: knowledge recombination and abductive reasoning, simulation and counterfactual reasoning, and dynamic resource orchestration. On this basis, the paper conducts an in‑depth analysis of GAI's innovative applications in four key scenarios—new product design, customer relationship management, precision marketing, and supply chain management—and incorporates typical domestic and international cases for empirical examination. The findings indicate that while GAI drives management innovation, it also faces multiple challenges, including content quality risks, technological application risks, and developmental constraints. Finally, this paper proposes countermeasures from three levels—technical governance, organizational transformation, and institutional safeguards—aiming to provide theoretical references and practical guidance for enterprises to effectively harness GAI and achieve management innovation in the process of intelligent transformation.