ARTIFICIAL INTELLIGENCE-AUGMENTED OPEN INNOVATION AND KNOWLEDGE MANAGEMENT: AN EXTENSION OF THE INTEGRATED OIKM FRAMEWORK FOR TELECOMMUNICATION ORGANIZATIONS

This paper extends the author's Integrated Open Innovation and Knowledge Management (OIKM) framework, originally developed for a telecommunications operator, to account for generative and agentic artificial intelligence (AI), which the original model predates. Literature published between 2024 and 2026 on generative AI's role in knowledge management, absorptive capacity and intellectual capital is reviewed and used to formulate five theoretical propositions that recast AI as a boundary condition strengthening or conditioning the OIKM framework's existing mediating and moderating relationships, and, in one case, contributing a new direct effect on the knowledge management process itself. A mixed-methods design combining qualitative case analysis with survey-based PLS-SEM is proposed for future empirical validation. The paper offers an AI-Augmented OIKM (AI-OIKM) model comprising five propositions: AI-mediated open innovation, generative-AI-mediated knowledge flow, AI-enabled absorptive capacity, and AI/digital intellectual capital, each extending an original construct without altering its identity, plus a fifth proposition on generative AI's direct effect on the knowledge management process. As a conceptual paper, the propositions are not yet empirically tested; the proposed mixed-methods design offers a research agenda for future validation across telecommunication contexts. The paper builds a theory-driven connection between the knowledge-based view of the firm and the emerging literature on organizational AI capability, extending a previously validated framework while preserving comparability with the original study. The paper offers telecommunications executives a conceptual basis for integrating AI into innovation and knowledge processes as a core operating capability rather than a bolt-on efficiency tool.