This research examines the nexus between audit features and timely financial reporting in the GCC region. The delay in submitting audit reports (ARL) amplifies uncertainty and diminishes confidence in financial statements. Thus, the study focuses on audit firm size, auditor change, busy audit season, institutional ownership (IO), and the timeliness of audit reports for non-financial companies listed on the stock exchanges of Gulf Cooperation Council (GCC) economies. The research draws on 5,271 firm-year observations spanning from 2009 to 2023. To test the hypotheses, the study employs both the generalized method of movements (GMM) technique combined with propensity score matching (PSM) approach. The study reveals that changes in auditors, a busy audit season, and the implementation of the Big 4 significantly increase the ARL in the GCC. Furthermore, institutional ownership cannot mitigate the detrimental effects of these three audit features on ARL. However, IO with at least a 20% stake significantly curtails the negative role of audit features in increasing the ARL in the region. Our research concludes that audit-related features and institutional ownership are very critical in preventing unnecessary delays in the audit report. The increasing ARL in GCC requires the regulator to revisit the legislation regarding the appointment of auditors, auditor change, busy audit season, and the stake of institutional ownership for the listed companies.

This study examines how the relationship between perceived financial accounting disclosures (FAD) and investor reactions to negative financial news (IRNFN) is conditioned by two individual-level moderators among 310 retail investors holding shares in project-based organisations (PBOs) listed on the Dubai Financial Market and Abu Dhabi Securities Exchange. The two moderators are framing bias susceptibility, a cognitive predisposition to be influenced by presentational form, and AI channel reliance (AICR), the extent to which investors rely on AI-mediated information channels—including algorithmic news aggregators, robo-advisory tools, AI-curated social media feeds, and automated sentiment-scored financial alerts—for receiving and interpreting corporate disclosures. Drawing on Behavioural Finance Theory and the Theory of Planned Behaviour, the study investigates whether the strength of the FAD–IRNFN association depends on these cognitive and informational processing conditions. The measurement model was estimated using confirmatory factor analysis in AMOS 25, and the moderation hypotheses were tested through path analysis with mean-centred composite scores and bias-corrected bootstrap inference, with a latent interaction robustness check reported in parallel. AI channel reliance emerged as a substantial moderator of the FAD–IRNFN relationship, while framing bias provided a smaller, marginally significant moderating effect. The findings are consistent with the theoretical expectation that, in AI-mediated information environments, the perceived quality and presentation of complex disclosures are associated with stronger, rather than weaker, investor reactions to negative news. Because the design is cross-sectional and based on self-reported data, the results are interpreted as associations rather than causal effects, with implications for disclosure regulation, corporate communication, and AI platform design in the UAE and comparable emerging markets.