Consumer behaviour has significantly evolved, with clients seeking tailored solutions. This necessitates that organisations incorporate AI-driven personalisation as a fundamental marketing approach. Nevertheless, current research analyses organisational and consumer views in isolation, neglecting to elucidate how these factors collectively influence the efficacy of personalisation.This study establishes a conceptual framework that connects organisational implementation with customer acceptance in AI-driven marketing personalisation. Utilising resource-based view theory, technology acceptance literature, and the privacy calculus framework, we propose a dual-perspective model that identifies critical organisational factors (firm size, industry type, marketing team competencies) and consumer perceptions (surveillance concerns, trust) as combined determinants of success. We articulate six theoretical propositions examining direct effects and interaction mechanisms.Our contributions encompass: (1) synthesising disparate research on AI adoption and consumer privacy, (2) emphasising the moderating influence of trust in alleviating surveillance concerns, and (3) offering a comprehensive supply-side and demand-side viewpoint. The framework underscores the importance of transparent data procedures, skill enhancement, and the cultivation of trust for practitioners. This offers a framework for forthcoming empirical investigations in many circumstances.
- et al. (Thu,) studied this question.