Artificial-intelligence (AI) targeting now mediates a growing share of consumers’ commercial encounters, personalising advertisements, product recommendations, pricing, and content across e-commerce and social-media platforms. While such targeting improves relevance and convenience, it simultaneously raises acute ethical concerns surrounding surveillance, opacity, and the fairness of algorithmic inference, thereby unsettling the consumer–firm relationship. Drawing on Privacy Calculus Theory, the Technology Acceptance Model, and organisational Trust Theory, this study develops and tests an integrated framework explaining how ethical AI attributes—AI personalisation, perceived transparency, perceived fairness, AI explainability, and ethical perception—shape consumer privacy concern and trust in AI, and how these cognitions translate into purchase intention, consumer acceptance, and consumer resistance. A cross-sectional survey was designed for consumers aged 18 and above in the Delhi–National Capital Region (NCR) who regularly encounter AI-driven recommendations on platforms such as Amazon, Flipkart, Instagram, YouTube, and Netflix, targeting approximately 450 respondents with an expected 380–420 usable responses. The measurement instrument adapts validated multi-item scales and employs a five-point Likert format. The planned analytical strategy comprises data screening (missing-value treatment, outlier detection via Zscores and Mahalanobis distance, and common-method-bias assessment through Harman’s single-factor test), reliability and validity assessment (Cronbach’s alpha, composite reliability, exploratory factor analysis, and convergent/discriminant validity), followed by descriptive statistics, crosstabulation, chi-square tests, t-tests, one-way ANOVA with Tukey HSD posthoc comparisons, correlation analysis, and stepwise multiple linear regression with full diagnostic checks. The framework predicts that transparency, fairness, explainability, and ethical perception strengthen trust while privacy concern erodes it, and that trust is the pivotal mechanism converting ethical AI design into favourable behavioural outcomes and reduced resistance. The study is positioned to advance ethical-AI marketing theory and to inform managers, policymakers, and AI developers.