Sustainable Digital Marketing: Towards the Integration of Artificial Intelligence and the Sustainable Development Goals

Abstract

This study presents a literature review on the emerging intersection of sustainable digital marketing, artificial intelligence (AI), and the Sustainable Development Goals (SDGs). As digital transformation accelerates and stakeholders increasingly demand more responsible business practices, organizations are reshaping their marketing strategies around sustainability while exploring the potential of artificial intelligence to support this transition. Drawing on a comprehensive body of recent scientific literature on sustainable digital marketing, responsible consumption, green marketing, and AI applications for sustainable development, this review provides a structured synthesis of the main theoretical and empirical contributions in the field.

The analysis identifies three major research streams. First, it examines digital marketing strategies designed to promote sustainable consumption behaviors, including personalization, social media engagement, influencer marketing, eco-labeling, and emotional storytelling. Second, it reviews the theoretical frameworks commonly used to explain consumers' cognitive, affective, and behavioral responses to green marketing initiatives, particularly the Theory of Planned Behavior, Signaling Theory, the Stimulus-Organism-Response (S-O-R) model, and the Value-Belief-Norm (VBN) Theory. Third, it highlights the emerging yet promising role of artificial intelligence in advancing the Sustainable Development Goals through machine learning, deep learning, and personalized recommendation systems. The review also identifies several persistent research gaps, including the attitude-behavior gap, the risk of greenwashing, and the limited attention devoted to the social dimensions of sustainability. Finally, the study outlines promising avenues for future research, particularly by encouraging empirical investigations within the Moroccan context, which remains underexplored in the existing literature.