This doctoral thesis examines how AI-powered digital channels impact customer satisfaction in the Saudi public social insurance sector, indicating significant implications for investment strategies.
This doctoral thesis empirically examines the impact of AI-powered digital channel quality on customer satisfaction within the Saudi public social insurance sector. Adopting a descriptive analytical approach, the study utilizes Structural Equation Modeling (SEM) to analyze data from 406 valid beneficiary responses. The research specifically evaluates the efficacy of AI-driven services across four key quality dimensions: Ease of Use, Responsiveness, Helpfulness of AI, and Reliability. Results indicate a statistically significant positive relationship between these four dimensions and customer satisfaction. Furthermore, the study confirms that higher satisfaction levels positively influence future behavioral intentions, specifically word-of-mouth promotion and continued engagement. By validating the link between AI service quality and user experience, this research offers actionable recommendations for public sector leaders to prioritize investment in AI usability and trust-building awareness programs, thereby supporting the digital transformation goals of the Saudi social insurance domain.
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Omar Dahan (2025) studied this question.
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