Organizational and Technological Barriers to AI-Driven Marketing Strategies in FMCG: Implications for Campaign Performance Enhancement

This study explores the organizational and technological barriers that hinder the effective integration of AI-driven marketing strategies in the FMCG sector, with a particular focus on social media campaigns. Drawing on a mixed-methods approach—including 20 expert interviews and a survey of 372 marketing professionals—the research examines how these barriers influence key performance indicators such as reach and engagement, while accounting for differences in company size. The findings highlight that AI-driven content personalization significantly enhances marketing outcomes, yet its effectiveness is constrained by persistent challenges including poor data quality, lack of algorithmic transparency, bias in audience segmentation, and limited real-time adaptability. In addition to these technological obstacles, the study identifies organizational-level barriers, such as insufficient internal capabilities, delayed model updates, and a lack of proactive AI system tuning, which collectively reduce campaign agility and responsiveness. Key recommendations emphasize the need for AI-human collaboration, real-time data integration, and explainable AI frameworks to support trust and performance optimization. The study offers both theoretical contributions and actionable insights for marketing professionals, emphasizing that successful AI deployment requires not only advanced tools, but also supportive organizational structures and continuous adaptation.