The increasing use of artificial intelligence (AI) in advertising has intensified the need to understand how disclosure of AI involvement influences consumer responses. This systematic literature review synthesizes empirical evidence on AI involvement disclosure in advertising, focusing on disclosure forms, consumer responses, psychological mechanisms, and contextual conditions. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, Scopus-indexed, English-language, peer-reviewed empirical studies published from 2022 to 2026 were considered for inclusion. After applying the predefined eligibility and journal-level selection criteria, 20 studies published from 2024 to 2026 constituted the final corpus. Methodological quality was considered using the Mixed Methods Appraisal Tool (MMAT), separately from the Journal Impact Factor used as a journal-level delimitation criterion. Seventeen of the 20 studies employed primary quantitative approaches, demonstrating the predominance of experimental, survey, and related quantitative designs. The synthesis indicates that consumer responses to AI disclosure are conditional rather than uniformly positive or negative. Disclosure was associated with variations in authenticity, credibility, trust, perceived effort, attitudes, engagement, and behavioral intentions, with these relationships shaped by psychological mechanisms and contextual factors such as perceived human involvement, disclosure format, advertising appeal, privacy concerns, and AI competency. The review contributes a mechanism-based understanding of AI disclosure by emphasizing a disclosure–interpretation–response process in which consumers interpret the role of AI and human involvement before forming advertising evaluations and behavioral responses. The findings highlight the importance of communicating not merely the presence of AI but also its specific role in advertising production and identify directions for more transparent and context-sensitive AI disclosure practices.
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Ruth Sealmoy (2026) studied this question.
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