Too Personal to Persuade: Consumer Reactance and the Inferential Personalization Paradox in Responsible Generative AI Marketing

Generative artificial intelligence (GenAI) is compressing the distance between algorithmic inference and personalized persuasion. Consumer signals can be interpreted, synthesized into latent knowledge, and converted into bespoke messages within the same interaction. This capability can improve relevance while simultaneously making a firm's inferential reach visible. This paper develops the Inferential Personalization Paradox (IPP), in which the capabilities that enhance personalization value also increase the risk that consumers judge algorithmically constructed knowledge as illegitimately knowable or actionable. Integrating Psychological Reactance Theory with Contextual Integrity, the paper conceptualizes perceived inferential boundary violation (PIBV) as the legitimacy appraisal connecting inferential personalization to autonomy threat and reactance. PIBV comprises inferential knowability and inferential actionability. Inferential salience activates the appraisal process, while contextual congruence and meaningful inferential agency define conditions under which personalization can remain autonomy-preserving. Eight propositions specify a dual-pathway framework and a shift from compensatory privacy calculus toward autonomy defense as PIBV intensifies. The framework advances consumer psychology and socially responsible marketing by defining responsible personalization as legitimate, contestable use of inferred knowledge rather than maximal predictive accuracy.

Marketing

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