Exploring Generative and Agentic Artificial Intelligence in Knowledge Transfer and Management Effectiveness: A Hybrid Approach
Year: 2026
Type: conference-paper
Abstract: This paper explores and contrasts the roles of generative artificial intelligence (AI) and agentic AI in knowledge transfer (KT) and management (KM) across educational, organizational, and computational domains. With the proliferation of AI systems like ChatGPT, DALL·E, and autonomous agents such as AutoGPT, the distinction between generative and agentic capabilities has critical implications for how knowledge is created, contextualized, and transmitted. Drawing on several sources, this study provides a literature review, conceptual analysis, and forward-looking discussion on how each AI paradigm supports or hinders effective knowledge transfer and management. Furthermore, the paper proposes the integration of generative and agentic AI through a hybrid framework for ultimately enhancing knowledge transfer and management.
Authors: Jose Romero-Mariona, Esperanza Romero
Institutions: United States Department of the Navy, United States Navy
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W7154381069