Sustainable marketing requires businesses to make strategic decisions aligned with their long-term environmental, social, and economic objectives. In this context, artificial intelligence (AI) and data analytics are transforming these processes by enabling more intelligent and efficient decision-making. Today, businesses integrate AI-driven technologies—such as big data analytics, machine learning, natural language processing (NLP), and computer vision—into their marketing strategies to enhance sustainability. This study examines the integration of AI-based smart solutions into marketing processes and highlights the critical role of data analytics in measuring sustainability performance. Machine learning and predictive analytics facilitate data-driven decision-making in key areas such as carbon footprint reduction, supply chain optimization, and energy efficiency. NLP techniques enhance sustainable brand communication by analyzing consumer sentiment, while computer vision-based systems provide innovative approaches for assessing recyclable packaging materials and monitoring sustainability standards in production processes. Moreover, big data analytics enables businesses to tailor their sustainable marketing campaigns to consumer expectations and optimize resource utilization. Smart solutions not only help businesses achieve their sustainability goals but also offer significant opportunities for optimizing operational processes and gaining a competitive advantage. However, the ethical implications of these technologies, particularly in terms of data security and algorithmic transparency, must be carefully addressed. This study explores the current academic and sectoral landscape of AI-driven sustainable marketing strategies and provides forward-looking insights for businesses and scholars alike.