Autonomous driving paper index
The Empowering Mechanisms and Challenges of Generative AI for Business Management Innovation: An Integrative Conceptual Review
One-line summary
An autonomous driving research paper: The Empowering Mechanisms and Challenges of Generative AI for Business Management Innovation: An Integrative Conceptual Review.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
**The Empowering Mechanisms and Challenges of Generative AI for Business Management Innovation: An Integrative** **Zixuan Li** Department of Business Administration, Woosong University, Daejeon 34606, Korea **Abstract:** The rapid advancement of Generative Artificial Intelligence (GAI) is profoundly reshaping the underlying logic and operational modes of enterprise management. Unlike traditional artificial intelli-gence, 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 possi-bilities for management innovation. This paper systematically reviews the technological evolution and core capability characteristics of GAI and reveals the micro‑mechanisms by which GAI enables man-agement innovation across three dimensions: knowledge recombination and abductive reasoning, simu-lation and counterfactual reasoning, and dynamic resource orchestration. Based on a systematic literature search of Web of Science, Scopus, and CNKI (January 2020–June 2026), 86 relevant sources were iden-tified and synthesized. On this basis, the paper conducts an in‑depth analysis of GAI’s innovative appli-cations in four key scenarios—new product design, customer relationship management, precision mar-keting, and supply chain management—and incorporates typical domestic and international cases as il-lustrative examples. The distinctive contribution of this review lies in linking the three mechanisms to dynamic capabilities theory, specifying boundary conditions, and integrating enabling logic with gov-ernance frameworks. The findings indicate that while GAI drives management innovation, it also faces multiple challenges, including risks to content quality, technological application, and development. Limitations include reliance on secondary sources and the rapidly evolving technological landscape. Fi-nally, 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. **Keywords:** Generative Artificial Intelligence, Management Innovation, Enabling Mechanisms, Multi‑Scenario Applications, Human‑Machine Collaboration **Citation:** Li, Z. (2026). The Empowering Mechanisms and Challenges of Generative AI for Business Management Innovation: An Integrative Conceptual Review. _Business and Management Perspectives_, 01(02), 18–27. https://doi.org/10.67728/bmp.2026.007
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