Factors affecting user satisfaction with artificial intelligence assistants
Published: August 14, 2026
Abstract
Artificial intelligence assistants have become increasingly integrated into everyday life. This study identifies and measures the factors affecting user satisfaction with AI assistant tools. Data were assessed using Cronbach’s Alpha reliability testing and factor analysis, after which structural equation modeling was employed to test the research hypotheses. The findings identify four determinants of user satisfaction, ranked from strongest to weakest: perceived performance, expectations, expectation confirmation, and trust. Perceived performance has the greatest influence, indicating that users are more satisfied when AI assistants effectively complete tasks and deliver useful results. The findings provide practical information for technology companies seeking to improve virtual assistant functions, strengthen user trust, manage expectations, and develop strategies that enhance the overall user experience.
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