AI-Driven Marketing Strategies: Their Role in Organizational Decision-Making

Abstract

Artificial intelligence (AI) is reshaping contemporary marketing and has become a key strategic factor for organizational competitiveness. This study analyzes how recent academic literature characterizes the incorporation of AI into marketing strategies and the implications attributed to it for organizational decision-making and for the personalization of the customer experience. The approach is qualitative, with a structured narrative documentary design. Literature retrieved from Scopus and Web of Science was reviewed, limited to the 2014-2024 period and analyzed through thematic category matrices and coding with ATLAS.ti 23 software. Following a documentary screening process that identified 38 eligible primary sources, the analytical corpus was composed of 11 primary sources selected for their empirical content density and academic quality. A total of 313 citations were identified, coded under 12 codes grouped into three families: AI tools in marketing (139 citations), implementation barriers (99 citations), and transformation of the brand-consumer relationship (75 citations). The most widely adopted tools recommendation systems, chatbots, predictive analytics, and advertising automation increase operational efficiency and conversion rates according to the reviewed studies. Drawing on the findings, an interpretive model is proposed that articulates the three families in a conditional sequence: technological adoption translates into competitive advantage only when it clears the filter of implementation barriers and when the organization governs the tension between personalization, which requires data, and trust, which requires transparency and consumer control over that data. It is concluded that this balance, rather than adoption itself, determines the sustainability of the advantage. Longitudinal and regionally focused studies are suggested to empirically validate these findings in Latin American contexts.