Agentic AI and Autonomous Marketing Systems: A Systematic Review and Integrative Framework
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Agentic artificial intelligence describes systems that plan and carry out multi-step workflows, use external tools, and adapt from feedback with limited human prompting. In marketing, the shift from content generation to autonomous decision and execution may improve speed, learning, and personalization, while also amplifying governance risks related to privacy, fairness, compliance, and brand harm. An open-source systematic review was conducted using PRISMA 2020, focusing on marketing-relevant applications, autonomy configurations, oversight mechanisms, and reported outcomes. An open-only search of arXiv, ACM Digital Library metadata, and DOI/publisher landing pages yielded 26 eligible studies. Building on this evidence, an integrative framework is proposed that links antecedents, agent design, governance controls, value mechanisms, and performance-risk trade-offs. The paper concludes with a research agenda aimed at producing cumulative, testable knowledge for responsible autonomous marketing systems
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