{"id":654,"date":"2026-10-09T06:18:20","date_gmt":"2026-10-09T06:18:20","guid":{"rendered":"https:\/\/www.journals.utgjiu.ro\/JES\/?post_type=articol&#038;p=654"},"modified":"2026-10-09T06:18:20","modified_gmt":"2026-10-09T06:18:20","slug":"consumers-trust-in-ai-powered-services-determinants-and-future-perspective","status":"publish","type":"articol","link":"https:\/\/www.journals.utgjiu.ro\/JES\/articol\/consumers-trust-in-ai-powered-services-determinants-and-future-perspective\/","title":{"rendered":"Consumers Trust in AI-Powered Services: Determinants and Future Perspective"},"content":{"rendered":"<p>Artificial intelligence (AI) is becoming an increasingly visible component of consumer services, ranging from conversational agents and recommendation systems to banking, retail, healthcare, travel and public services. As AI moves from a background technological infrastructure to a direct interface between firms and consumers, trust becomes a central condition for adoption, continued use, data disclosure and willingness to delegate decisions. This paper examines the principal determinants of consumer trust in AI-powered services and discusses the future development of trustworthy AI from a consumer perspective. The study uses a structured literature review and thematic synthesis of research on trust in AI, consumer behaviour, explainability, privacy, perceived risk, service quality and AI autonomy. The analysis indicates that consumer trust is multidimensional and emerges from the interaction of system-level attributes, firm-level signals and individual consumer characteristics. Perceived competence, reliability, transparency, explainability, privacy protection, security, controllability, personalization and the reputation of the service provider are repeatedly identified as relevant drivers, while perceived risk, opacity, lack of human oversight and concerns about misuse of personal data can reduce trust. The literature also shows that trust is not synonymous with acceptance: consumers may appreciate the usefulness of AI while simultaneously resisting high levels of autonomy. Future research should therefore move from static measures of trust toward dynamic and context-sensitive models that examine calibration, cultural differences, human-AI collaboration, generative AI and the long-term consequences of automated service encounters.<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}}},"class_list":["post-654","articol","type-articol","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.journals.utgjiu.ro\/JES\/wp-json\/wp\/v2\/articol\/654","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.journals.utgjiu.ro\/JES\/wp-json\/wp\/v2\/articol"}],"about":[{"href":"https:\/\/www.journals.utgjiu.ro\/JES\/wp-json\/wp\/v2\/types\/articol"}],"wp:attachment":[{"href":"https:\/\/www.journals.utgjiu.ro\/JES\/wp-json\/wp\/v2\/media?parent=654"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}