Cited by 316Psychology of Social InfluenceAI in Service InteractionsEthics and Social Impacts of AI

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The potential of generative AI for personalized persuasion at scale

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Matz, S. C., Teeny, J. D., Vaid, S. S., Peters, H., Harari, G. M., Cerf, M.·2024·Scientific Reports

DOI 10.1038/s41598-024-53755-0PMC PMC10897294

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Abstract

Matching the language or content of a message to the psychological profile of its recipient (known as “personalized persuasion”) is widely considered to be one of the most effective messaging strategies. We demonstrate that the rapid advances in large language models (LLMs), like ChatGPT, could accelerate this influence by making personalized persuasion scalable. Across four studies (consisting of seven sub-studies; total N = 1788), we show that personalized messages crafted by ChatGPT exhibit significantly more influence than non-personalized messages. This was true across different domains of persuasion (e.g., marketing of consumer products, political appeals for climate action), psychological profiles (e.g., personality traits, political ideology, moral foundations), and when only providing the LLM with a single, short prompt naming or describing the targeted psychological dimension. Thus, our findings are among the first to demonstrate the potential for LLMs to automate, and thereby scale, the use of personalized persuasion in ways that enhance its effectiveness and efficiency. We discuss the implications for researchers, practitioners, and the general public.

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Figure 1 Extraverted and introverted ads for an iPhone generated by GPT-3 alongside the response scale used to record effectiveness ratings.CC BY · PubMed Central

Figure 2 Effects (with 95% confidence intervals) of Big Five personality traits on effectiveness ratings for the respective ads.CC BY · PubMed Central

Figure 3 Effects (with 95% confidence intervals) of political ideology and moral foundations on effectiveness ratings for the respective ads.CC BY · PubMed Central

Figure 4 Effects (with 95% confidence intervals) of Big Five personality traits on effectiveness ratings and WTP for the respective ads.CC BY · PubMed Central

Figure 5 Interaction effects (with 95% confidence intervals) of participants and message personality/political ideology on effectiveness ratings and WTP for iPhone ads and political speeches.CC BY · PubMed Central

Figure 6 Standardized regression coefficients with 95% confidence interval for the 33 effects tested in this paper (sorted by effect size).CC BY · PubMed Central

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Attention Is All You Need
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“19 It is not surprising, then, to see this dynamic borne out empirically; personalisa - tion is a key factor in persuasion (see Yeo et al. 2025; Noar et al. 2007), particularly online (see Lustria et al. 2013 ; Matz et al. 2017; Matz et al. 2024 ).”
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Human preferences are susceptible to covertly misaligned AI advice
Sabour, S., Liu, J. M., Liu, S., Yao, C. Z., Cui, S., Zhang, W., Zhang, X., Cao, Y., Bhat, A., Guan, J., et al. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2600684123 · Cited by 2
The Promise of Generative AI for Personalized Persuasion
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Self-citation
Flexible Demand ManipulationPreprint
Dai, Y., & Koh, A. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4724126 · Cited by 1
“This reflects the increasing persuasiveness of new technologies such as artificial intelligence, especially for marketing consumer products (Matz et al., 2024).”
Background
Do Large Language Models Understand Verbal Indicators of Romantic Attraction?Preprint
Matz, S., Peters, H., Eastwick, P. W., Cerf, M., & Finkel, E. J. (2024) · doi:10.31234/osf.io/fqkgn · Cited by 1
Self-citation
Reply to Teeny and Matz: Toward the robust measurement of personalized persuasion with generative AI
Hackenburg, K., & Margetts, H. Z. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2418817121 · Cited by 1

Authors: Matz, S. C., Teeny, J. D., Vaid, S. S., Peters, H., Harari, G. M., & Cerf, M.
Affiliations: Columbia University (US)
Northwestern University (US)
Harvard University (US)
Stanford University (US)
Corresponding author: Matz, S. C.
ORCID: Matz, S. C.
Teeny, J. D.
Vaid, S. S.
Harari, G. M.
Cerf, M.
Venue: Scientific Reports
Publisher: Springer Science and Business Media LLC
Published: 2024-02-26
Volume: 14
Issue: 1
Pages: 4692-4692
ISSN: 2045-2322 (ISSN-L)
DOI: 10.1038/s41598-024-53755-0
PMC: PMC10897294
OpenAlex: W4392153984
Cited by: 315
References: 74
Citations by year: 2026: 133 · 2025: 120 · 2024: 59
FWCI: 222.98
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor)
Locations: Scientific Reports (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
OSF Preprints (OSF Preprints) (submittedVersion)
PsyArXiv (OSF Preprints) (submittedVersion)
PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
Topics: Social Sciences › Psychology › Social Psychology › Psychology of Social Influence
Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
Keywords: personalized persuasion, generative AI, large language models, ChatGPT, message tailoring, psychological profiling, persuasiveness, political appeal, climate action, political ideology, moral foundations, personality traits
MeSH terms: Climate, Language, Morals, Persuasive Communication, Marketing

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The potential of generative AI for personalized persuasion at scale

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