Impact of AI-powered digital channels on Customer Satisfaction in Saudi Public Social Insurance Sector

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.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-10
DOI
https://doi.org/10.5281/zenodo.18316238
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

Impact of AI-powered digital channels on Customer Satisfaction in Saudi Public Social Insurance Sector

Omar Dahan
Zenodo (CERN European Organization for Nuclear Research)
AI in Service Interactions
article

Impact of AI-powered digital channels on Customer Satisfaction in Saudi Public Social Insurance Sector

Omar Dahan
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Openalex Percentile: Top 16%
AI in Service Interactions
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Impact of AI-powered digital channels on Customer Satisfaction in Saudi Public Social Insurance Sector — Omar Dahan · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS