Artificial intelligence in marketing: a knowledge management perspective on decision-making

Purpose This study aims to examine how artificial intelligence (AI) is implemented across marketing functions and analyses how the knowledge associated with AI is managed. It also explores how AI-related knowledge supports marketing decision-making and organizational learning while identifying future research lines for strengthening knowledge management (KM) practices in marketing contexts. Design/methodology/approach This study follows a two-stage research design. First, a systematic literature review is developed to identify and classify the main variables linking AI, marketing and KM. These variables are coded into a binary matrix and analyzed through multiple correspondence analysis under a homogeneity analysis by alternating least squares, implemented in R and Visual Studio Code. Findings AI adoption in marketing is primarily associated with four interconnected areas: customer-oriented personalization and behavioral response, KM foundations, strategic knowledge-based decision support and AI-enabled operational marketing applications. The analysis shows meaningful associations between AI use and customer knowledge, market knowledge, predictive analytics, personalization and strategic marketing capabilities. Originality/value This study contributes to the intersection of AI, marketing and KM by conceptualizing AI in marketing as a knowledge-based organizational mechanism rather than only as an operational technology. It shows how AI-related knowledge is integrated into marketing functions and decision-making processes, offering a structured mapping of the field and clarifying AI’s potential to support organizational learning and strategic marketing decisions.