The Impact of ChatGPT Enterprise on Knowledge Management: Opportunities, Challenges and Implications - Ciro Alexander GONCALVES DA SILVA; Michal GREGUS (Communications of International Proceedings, 2025)
The rapid advancement of generative artificial intelligence is transforming the ways in which organizations create, manage, and disseminate knowledge. While previous research has explored the general implications of AI-driven systems in knowledge management (KM), a clear gap remains regarding the enterprise-specific impact of ChatGPT Enterprise, particularly with respect to governance, data protection, organizational readiness, and integration into existing KM infrastructures. This paper addresses this research void by examining how ChatGPT Enterprise influences knowledge creation, storage, retrieval, and collaboration in organizational settings. Drawing on an integrative literature review and conceptual analysis, the study synthesizes existing KM frameworks with emerging insights on large language models (LLMs) in enterprise environments. The methodological approach includes a structured assessment of opportunities and risks, focusing on capabilities such as secure knowledge augmentation, enhanced decision support, and scalable organisational learning, as well as challenges related to model reliability, bias, employee acceptance, and the need for revised KM governance structures. The findings highlight that ChatGPT Enterprise can significantly enhance knowledge accessibility and the efficiency of knowledge-intensive processes, provided that organizations implement robust governance mechanisms, clear guidelines for responsible AI use, and a balanced alignment between technological capabilities and human expertise. The paper concludes with practical implications for managers and scholars, emphasising that the effective adoption of ChatGPT Enterprise requires both technological integration and organisational maturity to maximise value creation while mitigating emerging risks.
Keywords: knowledge management; ChatGPT Enterprise; generative artificial intelligence; AI governance