Applications of generative artificial intelligence in the personalization of digital marketing strategies

Abstract

The study systematically explores the impact of generative artificial intelligence on the personalization of digital marketing, contextualizing its use in a business environment that demands competitive differentiation and individualized experiences. Through a comprehensive literature review of recent studies, relevant research from the last decade was identified, analyzing methodologies, findings and practical implications. The results show that generative artificial intelligence increases communication efficiency by producing hyper-personalized content and improving interaction with consumers, optimizes user experience by anticipating preferences and strengthening brand loyalty, and raises ethical challenges related to algorithmic transparency and personal data protection. It also highlights the absence of standardized metrics to rigorously quantify the return on investment of these strategies. The research concludes that, although the adoption of these technologies represents a significant opportunity for innovation and competitive differentiation, their effective implementation requires a balance between commercial efficiency, regulatory compliance and social responsibility, as well as the development of comprehensive evaluation frameworks and algorithmic governance policies that ensure sustainable and legitimate practices in the eyes of consumers.