Mapping generative AI governance readiness in Kurdistan Region universities

Abstract Generative artificial intelligence (GenAI) is reshaping higher education by challenging established ideas of plagiarism, authorship, academic integrity, assessment, disclosure, digital literacy, and institutional responsibility. Many universities already have plagiarism or academic-misconduct policies, but these policies may not be sufficient for guiding the educational use of tools such as ChatGPT and other GenAI systems. This study examines public-facing GenAI readiness across a 30-university audit sample in the Kurdistan Region of Iraq. Using website-based document analysis, it assesses publicly available evidence across 11 dimensions: plagiarism policy, academic integrity guidance, GenAI guidance, acceptable and unacceptable AI use, AI-use disclosure, assessment redesign, student AI literacy, staff guidance, privacy and data protection, institutional governance, and Kurdish/local-language accessibility. The findings show that public-facing GenAI governance remains at an early stage. Most universities were classified as Stage 1, indicating low public visibility or a narrow plagiarism-control orientation. A smaller number showed evidence of broader academic integrity or AI awareness, while only one institution demonstrated a more developed public-facing AI governance position. The weakest areas were AI-use disclosure, acceptable-use guidance, privacy protection, and AI-aware assessment redesign. A purposively selected subset of 10 universities (six public and four private after sector verification; 110 coding decisions) was independently double-coded; initial exact agreement was 95.5% and quadratic weighted kappa was 0.975. The study proposes a preliminary four-stage model of public-facing GenAI readiness – plagiarism control, academic integrity, AI awareness, and AI governance – and an 11-component AI governance checklist for Kurdistan higher education. It argues that universities should move beyond plagiarism control toward transparent, multilingual, locally grounded AI governance that supports academic integrity, responsible learning, assessment fairness, data protection, and student and staff AI literacy.