Ai-Powered Virtual Assistants In Uae E-Government: A Utaut-Based Assessment
Abstract
This study investigates the adoption of Artificial Intelligence-driven Virtual Assistants in public service platforms in the United Arab Emirates with the UTAUT model. A questionnaire was administered to 340 respondents from different demographic backgrounds via online methods. The results affirm that Behavioral Intention to adopt AI-VA is significantly influenced by Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, and Voluntariness of Use with a high reliability ranging from 0.89 to 0.94 and explain 79.6% of the variance in BI. ANOVA test results indicate there are significant differences regarding the adoption of AI-VA with respect to gender, age, and nationality. Through these results, the perceived usefulness, ease of use, social influences, and voluntariness turn out to be the main drivers that determine AI-VA adoption intentions. Further, these findings also mean that gender-sensitive design, age-friendly interfaces, and culture-sensitive strategies will be of utmost importance. This can be achieved by promoting AI-VA adoptions in the UAE public services. As this research provides critical insights for policymakers and practitioners into ways of improving AI-VA integration in public service platforms, it covers current literature on the technology adoption phenomenon in the context of the UAE and similar contexts.
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Publication Date
01 September 2026
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European Publisher
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1st Edition
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1-1
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Accounting and Finance, Business and Management, Communication, Law and Governance
Cite this article as:
Noordin*, N. A., NE Nohuddin, P., & Ibrahim Albloushi, K. W. (2026). Ai-Powered Virtual Assistants In Uae E-Government: A Utaut-Based Assessment. In Y. Naoyuki, A. Peng Hwa, & J. Matthes (Eds.), GLY-Upcoming Volume: Innovating Together: The Convergence of Management, Communication, and The Digital Transformation, vol -. European Proceedings of Social and Behavioural Sciences (pp. 0-0). European Publisher. https://doi.org/10.15405/epsbs.2026.09.26