Research on the impact of generative artificial intelligence (GenAI) on enterprise innovation performance: a knowledge management perspective

Purpose This study aims to investigate the impact of generative artificial intelligence (GenAI) on enterprise innovation performance, particularly from the perspective of knowledge management. It addresses key challenges in GenAI adoption – such as data biases, information overload and technological dependence – and proposes strategies to overcome these obstacles to enhance innovation. Design/methodology/approach Adopting a theoretical approach, this research analyzes the role of knowledge management in bridging the gap between GenAI and enterprise innovation. A structured framework based on four essential knowledge management processes – knowledge creation, retrieval and storage, transfer and sharing and application – is developed to tackle these challenges effectively. Findings The study reveals that while GenAI presents both opportunities and challenges for enterprise innovation, leveraging a structured knowledge management framework is key to unlocking its potential. It underscores the critical role of human–AI collaboration in mitigating issues such as data biases and integration challenges, ultimately improving innovation performance. The findings highlight the importance of complementing AI capabilities with human judgment to ensure successful outcomes in GenAI-driven innovation. Research limitations/implications This conceptual study calls for further empirical research to validate the findings and expand their generalizability. Future studies should explore contextual factors such as organizational characteristics, business environments and policy frameworks to refine the proposed framework. Originality/value This research offers novel insights into the intersection of GenAI, knowledge management and enterprise innovation. It stresses the importance of human involvement alongside GenAI, providing actionable recommendations for organizations navigating the complexities of AI adoption. In addition, it contributes to the evolving discourse on AI and innovation management, offering pathways for businesses to harness GenAI’s full potential and drive performance.