Advertising has rapidly evolved in recent years, with a significant increase in the use of artificial intelligence (AI) and its applications. While AI advertising literature dates to the 1990s, the field has experienced a surge in research attention and development in recent years, presenting varied potential avenues for future research. Despite this progress, understanding of the evolution of AI advertising research remains limited, and a state-of-the-art overview is required to advance future research. To address this gap, this review aims to map the field's evolution by conducting a bibliometric and framework-based analysis of 75 AI advertising articles published between 1990 and 2022. The study's key findings are the publication trends in AI advertising, TCCM classifi-cation, and research contexts identified through bibliographic coupling. Four themes emerged as key focus areas of AI advertising research: programmatic advertising and automation, ad planning and engagement, advertising effectiveness, and trust in AI advertising. In addition, this review offers practical guidelines and future research directions for developing AI advertising literature. Lastly, the review suggests broader implications for industry and academia, highlighting how the identified themes can inform advertising practice and contribute to the theoretical development of the field.