Agentic AI Personalization in Advertising: Realizing the True Potential of N = 1
With the rapid diffusion of generative artificial intelligence (AI), we have come closer than ever to achieving the holy grail of personalizing advertisements to individual consumers, i.e., the ideal of N = 1. AI-driven ad serving platforms act with unprecedented agency, dynamically creating highly tailored appeals and experiences. Such “agentic AI personalization” has both positive and negative consequences. This article traces the evolution from analog personalization to agentic personalization. It then explicates the latter concept in terms of breadth, depth, and length of personalized messaging. It overviews the processes underlying agentic AI personalization and describes the dualities inherent in both its foundation and operation. Finally, it offers a theoretical framework for studying the effects of agentic AI personalization on consumer responses to advertisements, followed by an illustrative set of propositions for empirical testing.
Authors
- Kirk A. Plangger (ORCID: https://orcid.org/0000-0002-0354-9707)
- S. Shyam Sundar (ORCID: https://orcid.org/0000-0002-5779-8864)
- Taylor Jing Wen (ORCID: https://orcid.org/0000-0002-6967-1617)
- Claire Monique Segijn (ORCID: https://orcid.org/0000-0002-2424-5737)
- Julien Cloarec (ORCID: https://orcid.org/0000-0002-9862-6137)
Institutions
- University of Minnesota (US)
- Pennsylvania State University (US)
- University of South Carolina (US)
- King's College London (GB)
- Sungkyunkwan University (KR)
- Université Jean Moulin Lyon III (FR)
Publication Details
- Journal
- Journal of Advertising
- Published
- 2026-10-28
- DOI
- https://doi.org/10.1080/00913367.2026.2744238
- Primary Topic
- Marketing and Advertising Strategies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- University of Minnesota
- Academy of Marketing
- European Commission
- Ministry of Science and ICT, South Korea