The rapid diffusion of generative artificial intelligence (AI) in marketing has transformed how firms design, personalize, and disseminate persuasive messages across global markets. However, limited research has theorized how consumers develop trust in AI as an active source of marketing communication rather than as a background analytical infrastructure. This study introduces algorithmic trust in interactive marketing as a multidimensional construct that captures cognitive, emotional, ethical, and institutional confidence in AI-generated marketing messages and the socio-technical systems that produce and govern them. Drawing on trust theory, technology acceptance research, source credibility theory, and cross-cultural institutional frameworks, we developed a conceptual model explaining how cultural values, regulatory environments, and transparency strategies shape the psychological mechanisms underlying trust formation and its behavioral outcomes. The framework advances interactive marketing theory by repositioning AI as a relational actor in consumer–brand communication. We derive six theoretically grounded propositions and outline a research agenda to guide empirical investigations into transparency, governance, and human–AI interaction in marketing contexts.

algorithmic trust, interactive marketing, rtificial intelligence, AI governance, algorithmic persuasion, transparency, cross-cultural consumer behavior

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