Imam Hossein University Strategic Management of Organizational Knowledge 2645-4262 Articles in Press 2026 07 08 Designing a Symbiotic Knowledge System Based on Generative Artificial Intelligence: From Positive Human Resource Management to Strategic Collective Intelligence Designing a Symbiotic Knowledge System Based on Generative Artificial Intelligence: From Positive Human Resource Management to Strategic Collective Intelligence 210850 10.47176/SMOK.2026.2029 FA Taimoor Marjani Assistant Professor, Department of Management, Faculty of Humanities, University of Science and Culture, Tehran, Iran, tmarjani@usc.ac.ir Ali Davari Associate Professor, Department of New Business, Faculty of Entrepreneurship, College of Management, University of Tehran, Tehran, Iran, ali_davari@ut.ac.ir 0000-0002-3304-8970 Ali Sadollah Assistant Professor, Department of Mechanical Engineering, Faculty of Engineering, University of Science and Culture, Tehran, Iran, sadollah@usc.ac.ir 0000-0002-7782-4126 Journal Article 2026 05 28 <strong>Purpose:</strong> Generative artificial intelligence has created opportunities for knowledge management and human resource management, yet a model that synergistically integrates employee flourishing and strategic knowledge creation is rare. This study aims to design a symbiotic knowledge system model based on generative artificial intelligence and to explain its causal relationships.<br /><strong>Methodology: </strong>An exploratory sequential mixed‑method approach was adopted in two phases. In the qualitative phase, fuzzy Delphi with 15 experts extracted the initial components. In the quantitative phase, fuzzy DEMATEL analyzed causal relationships, and fuzzy cognitive mapping combined with agent‑based simulation over a five‑year horizon modeled system dynamics. Content validity was confirmed using CVR, and reliability was confirmed using Kendall's coefficient (0.73).<br /><strong>Results: </strong>Five components were identified: algorithmic transparency, cognitive diversity preservation, human‑AI interaction feedback, generative personalized learning, and ethical AI governance. "Cognitive diversity preservation" with the highest causality (+3.78) was the strongest causal driver. Simulation showed the full system increases strategic knowledge creation by 87%, reduces burnout from 34% to 12%, and improves decision‑making accuracy by 48%.<br /><strong>Discussion:</strong> Contrary to traditional approaches, cognitive diversity preservation drives knowledge‑wellbeing synergy. Algorithmic transparency enables trust and feedback, while personalized learning operates under ethical governance.<br /><strong>Conclusion: </strong>This study provides an integrated framework linking positive HRM, generative AI, and strategic collective intelligence. Organizations should prioritize cognitive diversity preservation and algorithmic transparency in implementation. Generalizability is limited to Iranian knowledge‑based industries. <strong>Purpose:</strong> Generative artificial intelligence has created opportunities for knowledge management and human resource management, yet a model that synergistically integrates employee flourishing and strategic knowledge creation is rare. This study aims to design a symbiotic knowledge system model based on generative artificial intelligence and to explain its causal relationships.<br /><strong>Methodology: </strong>An exploratory sequential mixed‑method approach was adopted in two phases. In the qualitative phase, fuzzy Delphi with 15 experts extracted the initial components. In the quantitative phase, fuzzy DEMATEL analyzed causal relationships, and fuzzy cognitive mapping combined with agent‑based simulation over a five‑year horizon modeled system dynamics. Content validity was confirmed using CVR, and reliability was confirmed using Kendall's coefficient (0.73).<br /><strong>Results: </strong>Five components were identified: algorithmic transparency, cognitive diversity preservation, human‑AI interaction feedback, generative personalized learning, and ethical AI governance. "Cognitive diversity preservation" with the highest causality (+3.78) was the strongest causal driver. Simulation showed the full system increases strategic knowledge creation by 87%, reduces burnout from 34% to 12%, and improves decision‑making accuracy by 48%.<br /><strong>Discussion:</strong> Contrary to traditional approaches, cognitive diversity preservation drives knowledge‑wellbeing synergy. Algorithmic transparency enables trust and feedback, while personalized learning operates under ethical governance.<br /><strong>Conclusion: </strong>This study provides an integrated framework linking positive HRM, generative AI, and strategic collective intelligence. Organizations should prioritize cognitive diversity preservation and algorithmic transparency in implementation. Generalizability is limited to Iranian knowledge‑based industries. https://jkm.ihu.ac.ir/article_210850_32a8329aa1f1f35e5455eec14b032afd.pdf