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Purpose: Research on artificial intelligence (AI) in marketing is fragmented across applications and theories, and rests largely on evidence from developed economies.This paper conceptualises AI as a firm-level marketing capability and explains how, and under what conditions, it improves marketing performance, with particular attention to developing economies.Design/methodology/approach: The paper adopts a conceptual, theory-synthesis design.It integrates the resource-based view, dynamic capabilities theory, the marketing capabilities perspective, and relationship marketing and customer equity theory, and develops a framework with nine testable propositions.Findings: AI capability is proposed to improve marketing performance indirectly, by strengthening marketing capabilities, which in turn create customer value.Because AI technologies are increasingly bought as standardised services, advantage is argued to come less from the technologies themselves than from the complementary resources and dynamic capabilities with which they are bundled.Ethical AI governance and human-AI collaboration condition whether AI-enabled marketing creates customer value, while the institutional voids common in developing economies weaken the conversion of AI capability into marketing capability. Research limitations/implications:The propositions await empirical testing, preferably with longitudinal, multi-source and cross-country designs.Practical implications: Managers should invest in data, skills, governance and human-AI routines alongside AI tools.Policymakers should address digital infrastructure, data protection enforcement and the AI capability of small and medium-sized enterprises.
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Bameyi et al. (2026) studied this question.
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