The diffusion of generative artificial intelligence (AI) in marketing communication has intensified personalization, scalability, and message optimization. Existing research largely assumes that such improvements translate proportionally into stronger customer engagement. This study challenges that implicit linearity by introducing communicative agency—the perceived locus of intentional authorship behind a marketing message—as a structurally consequential construct. Drawing on engagement theory, attribution theory, anthropomorphism research, and persuasion models, the article develops a mechanism-based framework explaining how AI-generated communication reshapes engagement through agency attribution processes. As AI intensity increases, customers are more likely to attribute communication to system-based rather than human-intentional sources. This shift enhances cognitive engagement through improved processing fluency and perceived competence, while simultaneously attenuating affective engagement by reducing perceived intentionality and relational warmth. The divergence between cognitive and affective engagement generates non-linear aggregate effects and temporally asymmetric strategic outcomes. In relationally intensive markets, excessive reliance on AI-generated communication may strengthen short-term responsiveness while weakening long-term attachment. By reconceptualizing engagement as compositionally sensitive under system mediation, the study extends engagement theory and reframes the strategic evaluation of AI-enabled marketing communication.
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