Artificial intelligence (AI) has transformed marketing analytics from a predominantly reporting-oriented function into a predictive, prescriptive, and increasingly generative decision infrastructure. Yet this transformation cannot be understood solely through the lenses of computational efficiency or firm performance. As AI systems shape segmentation, personalization, communication, and meaning production, they also raise questions of legitimacy, authorship, bias, trust, and governance that require interdisciplinary interpretation. This article develops an integrative review of 21 DOI-traceable scholarly sources published between 2014 and 2025 to explain how marketing analytics has evolved across four stages: descriptive-diagnostic measurement, predictive-prescriptive inference, generative-conversational production, and reflexive governance. The review shows that AI has deepened analytical capability, expanded analytics into narrative and symbolic domains, intensified tensions between assistance and anxiety narratives, and increased the need for explainable and ethically accountable systems. The article concludes that the future of marketing analytics lies not in automation alone,
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