The Use of Artificial Intelligence in Digital Marketing: Conceptual Transformation, Strategic Applications, and Future Vision

Résumé fourni par la source

Aim: This study aims to investigate the strategic integration of artificial intelligence (AI) technologies into digital marketing, systematically analyzing how cognitive computing redefines traditional and extended marketing paradigms. Methodology: Utilizing a structured conceptual review methodology, this study synthesizes academic literature from core databases (Scopus, Web of Science, Google Scholar) published between 2010 and 2026. The conceptual framework tracks the evolutionary trajectory of web technologies and maps AI capabilities (Machine Learning, Deep Learning, and Natural Language Processing) onto the extended marketing mix (7Ps). Results: The synthesis reveals that AI functions as a key catalyst in transforming the 7Ps from static, standardized organizational functions into dynamic, hyper-personalized, and autonomous value propositions. Sectoral case analyses (such as Netflix, Spotify, FLO, and Nike) demonstrate that the practical application of AI primarily treats experience enrichment, predictive demand forecasting, and operational error reduction. Because this is a conceptual review, quantitative p-values are not applicable; however, the qualitative synthesis establishes a robust linkage between Web 5.0 concepts and emotion-aware marketing strategies. Conclusion: The integration of AI in marketing represents a fundamental shift from intuitive strategies to highly predictable, data-driven frameworks. To sustain competitive advantages, contemporary enterprises must balance technological optimization with strict compliance with data privacy regulations (GDPR/KVKK) and corporate environmental responsibilities regarding the computational carbon footprint of AI models.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.