Purpose: This study aimed to investigate the status of generative AI policies in Iranian journals of Information Science and Knowledge Studies, comparatively analyze existing policy components, and propose a comprehensive policy framework.
Methodology: This applied study employed a descriptive-analytical design using directed qualitative content analysis. The research population consisted of all 27 accredited journals in the field of Information Science and Knowledge Studies indexed in the Iranian Ministry of Science's journal evaluation system up to the end of 2025. A census sampling approach was adopted. Data were collected through a systematic review of journal websites, including sections such as author guidelines, publication ethics statements, reviewer instructions, and publication policies. In addition, the responsible AI guidelines of the Iran National Science Foundation (INSF), as well as policies issued by international organizations and publishers, including COPE, UNESCO, Elsevier, Springer Nature, and Wiley, were examined as reference documents. Data were analyzed using directed qualitative content analysis and a three-level coding scheme (explicit presence, implicit presence, and absence).
Findings: The findings revealed that only three journals (11.1%)—Library and Information Organization Studies, Scientometrics Research Journal, and Library and Information Science Research Journal—had published explicit policies regarding the use of generative AI, while the remaining 24 journals (88.9%) lacked any formal policy statements. Comparative analysis of 16 key policy components showed that Library and Information Organization Studies had the most comprehensive policy, with a particular focus on protecting sensitive data in Information Science.