Visible but not always usable: polarized generative artificial intelligence governance in university-linked Asian journals

Purpose: Universities increasingly issue institutional artificial intelligence (AI) guidance, but it remains unclear whether university-linked journals translate such guidance into publicly visible and usable editorial instructions. This study audited generative AI governance in Asian university-linked journals indexed in Scopus and traceable in SCImago and examined how core policy requirements co-occurred.Methods: This cross-sectional policy audit examined 75 unique university-linked Asian journals. Two trained coders independently coded the original 80-record journal-field frame. Across 11 paired pre-adjudication variables, reliability was substantial to almost perfect: Cohen κ=0.747–0.945, quadratic weighted κ=0.944 for the maturity index using 77 valid 0–4 pairs, and Krippendorff α=0.748–0.966. Journal-level analyses included latent class analysis and Firth penalized logistic regression.Results: Forty-two journals (56.0%) permitted AI use with disclosure and author accountability, 15 (20.0%) had no explicit AI statement, and 1 (1.3%) had a dedicated AI policy page. Disclosure and accountability signals were common (73%–76%), whereas the six operational requirements were less visible (24%–32%). The count of operational elements per journal was strongly bimodal, and latent class analysis separated journals into operationally nonarticulated (n=49) and operationally articulated (n=26) configurations. Firth regression identified positive associations with articulated configuration membership for health sciences and West Asia, although the estimates were imprecise; the confidence intervals for the other field, region, and ranking estimates included the null.Conclusion: The journals showed polarized public articulation of AI policy rather than a gradual continuum. Policy visibility did not necessarily translate into policy usability. The configurations should be interpreted as exploratory patterns, not as a maturity taxonomy.