Artificial Intelligence–Driven Intelligent Marketing Transformation in the FMCG Industry: A Perspective of Consumer Behavior Prediction and Dynamic Resource Allocation

Abstract

With the rapid advancement of artificial intelligence (AI) technologies and the full-scale expansion of the digital economy, the fast-moving consumer goods (FMCG) industry is undergoing a profound transformation toward intelligence. Leveraging powerful capabilities in data processing and prediction, AI has been widely applied in consumer behavior analysis, market segmentation, and resource allocation within FMCG enterprises, driving the shift from experience-based to data-driven decision-making and from static marketing to intelligent decision systems. Grounded in intelligent-marketing and dynamic-capability theories, this paper systematically reviews recent progress in AI applications for consumer behavior prediction and dynamic resource allocation, with particular attention to representative practices and key challenges in the FMCG sector. Through case analyses of Unilever and Coca-Cola, the study reveals the intrinsic logic and practical pathways of AI-enabled marketing intelligence. Findings indicate that AI can significantly enhance market-forecast accuracy and resource-utilization efficiency, yet it remains constrained by barriers to data integration, limited model interpretability, and uneven levels of digital maturity among organizations. Finally, the paper proposes future research directions-including multimodal data fusion, explainable AI, and human–machine collaborative decision-making-to provide theoretical and practical guidance for the digital and intelligent transformation of FMCG enterprises.