Programmatic advertising uses artificial intelligence to target ads at predetermined user personas according to specific criteria, including user demographics, interests, and online activity (Shehu et al., 2021). In this type of online promotion, ad space bidding takes place based on understanding the surrounding platform environment (Häglund & Björklund, 2024). While legal frameworks such as GDPR provide some safeguards, they fail to grant users complete control over their data (Kawaf et al., 2023). This paper aims to comprehensively analyse existing academic research on programmatic advertising, focusing on its evolution, core concepts, challenges, and future research opportunities. A systematic literature review of 45 studies from Scopus and Web of Science databases was conducted using predefined keywords related to programmatic advertising and user privacy (NúnezBarriopedro et al., 2022). Papers were filtered by relevance, language, and alignment with research objectives. Thematic coding in MAXQDA was employed to extract insights and identify patterns across the literature. The findings reveal six critical themes: privacy risks related to minimal transparency, user profiling, and unethical data handling. The literature further highlights users' insufficient education about online privacy and inadequacies in current regulatory policies (Kawaf et al., 2023). This study contributes to programmatic advertising by synthesising existing research and addressing gaps in understanding ethical digital advertising (Chen et al., 2019). It provides valuable insights for academics, marketers, and policymakers aiming to foster transparency and trust in digital advertising practices.

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Programmatic advertising,ePrivacy,Third-party Cookies,Tracking

• Economics and Business - Social Sciences