Exploring The Role of AI News Anchors in Content Quality and Continued Audience Engagement in Oman

Abstract

This paper discusses how artificial intelligence news reporters influence the level of perceived content and viewer interest in Omani media. With increasing adoption of AI anchors, it is now important to learn how audiences perceive and use these technologies. Drawing on expectation confirmation theory, the study suggests a conceptual framework examining perceived intelligence, novelty, information quality, and trust as predictors of continuance intention and consumer interest in AI-based news content. The research used a structured questionnaire to gather the data, which consisted of 465 valid answers, and was analyzed with the help of partial least squares structural equation modeling (PLS-SEM). The results show that perceived intelligence, perceived novelty and trust are significantly used in the quality of information and continuance intention. The mediating role of continuance intention is also influenced by these factors albeit indirectly on consumer engagement. Information quality and continuance intention are serial mediators between perceived intelligence, perceived novelty and trust to continuance intention. The consumer engagement variance is explained in 70% by the proposed model. The research adds to the growing body of literature on AI-driven media by explaining the processes by which AI anchors impact long-term audience interest in underexplored areas.