AI on AI: Unveiling Trends and Patterns in AI in Marketing Using Large Language Models
(A2025-126352)

AUTHORS

Faridoddin Rezaei, University of Bremen; Maik Eisenbeiss, University of Bremen; Kristina Klein, University of Bremen

ABSTRACT

This study explores the application of artificial intelligence (AI) in marketing by addressing several research questions concerning patterns in marketing elements, methodologies used, and AI domains. Using a knowledge discovery in databases (KDD)-based methodology, the study employs Large Language Models (LLMs) to screen a dataset of over 300,000 papers, thereby significantly enhancing the depth and efficiency of the literature review process. Filtering identifies more than 9,000 relevant studies. We analyze those papers with the support of LLMs to uncover patterns of AI applications in marketing. The study’s primary contribution lies in demonstrating the transformative potential of LLMs in conducting large-scale literature reviews, setting a new benchmark for research synthesis in rapidly evolving fields. Findings reveal rising trends such as a growing focus on relationship and consumer-focused solutions elements, alongside the sustained dominance of consumer, behavioral influence, and decision making.