The Impact of AI-Driven Predictive Marketing on Ethical Perceptions and Strategic Business Outcomes

AI-driven predictive marketing promises superior targeting, personalization, and decision speed, yet its strategic payoffs depend on how customers and managers judge the ethics of its use. This study examines whether and how capability in AI-powered predictive marketing improves strategic business outcomes by shaping ethical perceptions in privacy and consent, transparency and explainability, and fairness and non-discrimination. Drawing on Resource-Advantage theory, we propose and test a model in firms from Makassar, Indonesia, spanning creative industries, financial services, food and beverage, and technology. Using Partial Least Squares Structural Equation Modeling with higher-order constructs, we assess direct, indirect, and conditional effects, including mediation by governance quality and moderation by perceived manipulation and perceived market concentration or data dominance. The estimates show that stronger AI-PM capability is associated with more favorable ethical perceptions, and these perceptions relate positively to brand trust and credibility, innovation readiness, competitive advantage, and performance. Governance practices, consent management, bias audits across pre-, in-, and post-processing, and explainability routines, act as the primary mechanism strengthening ethical perceptions and outcomes. Conversely, perceived manipulative design weakens capability–outcome links, and perceptions of market concentration reduce the ethical appraisal of personalization efforts. The findings position ethics-by-design as a market-based resource that renders data and algorithmic investments more legitimate and defensible over time. Managerially, firms should pair analytics stacks with governance stacks and invest in complementary IT and organizational readiness, while policymakers can enhance contestability and transparency to preserve choice and fairness in data-intensive markets.