<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2d1 20170631//EN" "JATS-journalpublishing1.dtd">
<ArticleSet>
<Article>
<Journal>
<PublisherName>theaimsjournal</PublisherName>
<JournalTitle>Allana Management Journal of Research, Pune</JournalTitle>
<PISSN> 2581 - 3137 (</PISSN>
<EISSN>) 2231 - 0290 (Print)</EISSN>
<Volume-Issue>Volume 15, Issue 2</Volume-Issue>
<PartNumber/>
<IssueTopic>Multidisciplinary</IssueTopic>
<IssueLanguage>English</IssueLanguage>
<Season>July 2025 - Dec 2025</Season>
<SpecialIssue>N</SpecialIssue>
<SupplementaryIssue>N</SupplementaryIssue>
<IssueOA>Y</IssueOA>
<PubDate>
<Year>2025</Year>
<Month>12</Month>
<Day>25</Day>
</PubDate>
<ArticleType>Marketing Management</ArticleType>
<ArticleTitle>EVALUATING THE IMPACT OF GENERATIVE AI TOOLS ON CONSUMER TRUST AND BRAND PERCEPTION: AN EMPIRICAL VALIDATION</ArticleTitle>
<SubTitle/>
<ArticleLanguage>English</ArticleLanguage>
<ArticleOA>Y</ArticleOA>
<FirstPage>70</FirstPage>
<LastPage>79</LastPage>
<AuthorList>
<Author>
<FirstName/>
<LastName>Hamsa</LastName>
<AuthorLanguage>English</AuthorLanguage>
<Affiliation/>
<CorrespondingAuthor>N</CorrespondingAuthor>
<ORCID/>
</Author>
</AuthorList>
<DOI>https://doi.org/10.62223/AMJR.2025.150208</DOI>
<Abstract>Generative Artificial Intelligence (GenAI) is transforming modern marketing by enabling brands to create scalable, personalized content across multiple digital formats. However, its growing use raises important concerns regarding consumer trust, authenticity, privacy, and brand reputation.
Purpose: The rapid adoption of Generative Artificial Intelligence (GenAI) in marketing has enabled brands to produce large-scale, highly personalized content across text, image, audio, and video formats. While GenAI offers significant operational and creative advantages, it also raises critical concerns regarding consumer trust, brand authenticity, privacy, and reputation. This study examines the impact of AI-generated marketing content on consumer trust and brand perception.
Research Design/Methodology/Approach: The study employs a mixed-method research design combining a Systematic Literature Review (SLR) with a quantitative pre- and post-exposure survey. The SLR identifies key constructs influencing consumer trust in AI-generated marketing. Primary data were collected from student and consumer panel respondents exposed to both AI-generated and human-created marketing content. Statistical analysis includes paired t-tests to measure changes in trust and perception scores, and chi-square tests to assess shifts in consumer attitudes.
Findings: The literature review identifies five critical elements shaping consumer trust in AI-generated marketing content: perceived usefulness, authenticity, privacy concerns, transparency, and brand trust. Empirical findings reveal that while GenAI content is perceived as efficient and informative, it often scores lower on authenticity and privacy assurance compared to human-created content. Exposure to AI-generated marketing leads to measurable changes in consumer trust levels and brand perception, particularly when transparency about AI usage is absent.
Research Limitations/Implications: The study relies on controlled exposure settings and self-reported responses, which may not fully capture real-world consumer behaviour. The sample composition may limit generalizability across industries and demographic segments.
Originality/Value: This research integrates systematic literature insights with empirical evidence to advance understanding of how GenAI influences consumer trust in marketing. It identifies key areas for future controlled studies and offers practical implications for responsible and transparent AI adoption in branding strategies.</Abstract>
<AbstractLanguage>English</AbstractLanguage>
<Keywords>Generative Artificial Intelligence, Consumer Trust, Brand Reputation, Marketing Content, Authenticity, Privacy, Systematic Literature Review.</Keywords>
<URLs>
<Abstract>https://theaimsjournal.org/ubijournal-v1copy/journals/abstract.php?article_id=16064&title=EVALUATING THE IMPACT OF GENERATIVE AI TOOLS ON CONSUMER TRUST AND BRAND PERCEPTION: AN EMPIRICAL VALIDATION</Abstract>
</URLs>
<References>
<ReferencesarticleTitle>References</ReferencesarticleTitle>
<ReferencesfirstPage>16</ReferencesfirstPage>
<ReferenceslastPage>19</ReferenceslastPage>
<References>Armstrong, J. (2024, June 25). Consumer trust: Will AI erode authenticity in marketing? Quirks.
https://www.quirks.com/articles/consumer-trust-will-ai-erode-authenticity-in-marketing
Buder, M., et al. (2024). Consumer attitudes toward AI-generated marketing content. Nuremberg Institute for Market Decisions (NIM).
https://www.nim.org/en/publications/detail/transparency-without-trust
Business Insider. (2025, October). Aerie’s promise not to use AI in ads is its most popular Instagram post in a year. Business Insider.
https://www.businessinsider.com/aerie-against-ai-in-ads-most-liked-instagram-post-2025-10
Cavender, E. (2025, May). Most influencers use AI to create content but consumers are skeptical. Adweek.
https://www.adweek.com/commerce/most-influencers-use-ai-to-create-content-but-consumers-are-skeptical/
Chen, Y. (2024). Exploring the effect of deepfake-based advertising on consumer attitudes. Working Paper, Texas Aand;M International University.
https://www.tamiu.edu/cswht/documents/wp-2024-001-chen.pdf
Click Consult. (2024). New research on customer perception of AI in marketing.
https://www.click.co.uk/insights/new-research-on-customer-perception-of-ai-in-marketing/
Column Five Media. (2024). New study: 82.1% of consumers can spot AI-generated content.
https://www.columnfivemedia.com/new-study-82-1-of-americans-can-spot-ai-generated-content/
Customer Experience Dive. (2024). Influencers sway consumers but authenticity loses some clout, study finds.
https://www.customerexperiencedive.com/news/influencer-creator-generative-ai-marketing-report/714367/
DALIM ES. (2025, June 18). How to preserve visual trust in an AI-driven marketing world. DALIM Blog.
https://www.dalim.com/dalim-software-blog/how-to-preserve-visual-trust-in-an-ai-driven-marketing-world
De, S., and; Vats, A. (2025, March 12). Unmask it! AI-generated product review detection in Dravidian languages. arXiv.
https://arxiv.org/abs/2503.09289
Haleem, A. (2022). Artificial intelligence (AI) applications for marketing. ScienceDirect.
https://www.sciencedirect.com/science/article/pii/S2666603022000136
Hardcastle, K. (2025). Understanding customer responses to AI-driven personalization. Journal of Advertising Research, 65(2), 1–18.
https://doi.org/10.1080/00913367.2025.2460985
Huschens, M., Briesch, M., Sobania, D., and; Rothlauf, F. (2023). Do you trust ChatGPT? – Perceived credibility of human and AI-generated content. arXiv.
https://arxiv.org/abs/2309.02524
Kostrz, K. (2024). The effect of perceived authenticity on consumers’ willingness to buy AI-generated products (Bachelor’s thesis, Erasmus University Rotterdam).
https://thesis.eur.nl/pub/73259/Thesis-Kostrz-560566.pdf
Lifewire. (2024, August 30). AI is making it impossible to trust product and app reviews. Lifewire.
https://www.lifewire.com/ai-making-it-hard-to-trust-reviews-8704543
Mukherjee, A. (2024, March 17). Safeguarding marketing research: The generation, identification, and mitigation of AI-fabricated disinformation. arXiv.
https://arxiv.org/abs/2403.14706
Nature Communications. (2025). Impact of artificial intelligence on branding: A bibliometric review and global research agenda. Nature Communications.
https://doi.org/10.1038/s41599-025-04488-6
Ndash Blog. (2023). Innovation vs. integrity: The impact of AI on brand authenticity and consumer trust.
https://www.ndash.com/blog/innovation-vs-integrity-the-impact-of-ai-on-brand-authenticity-and-consumer-trust
New York Post. (2025, April 26). Majority of Americans trust what’s online less than ever before: Poll. New York Post.
https://nypost.com/2025/04/26/lifestyle/majority-of-americans-trust-whats-online-less-than-ever-before/
NYIT News. (2024). Are messages from robots trustworthy? NYIT News.
https://www.nyit.edu/news/articles/do-customers-perceive-ai-written-communications-as-less-authentic/
Park, K. (2024). Beyond the code: The impact of AI algorithm transparency on trust. Information Systems Journal, 34(4), 421–445.
https://doi.org/10.1016/j.isj.2024.04.001
Reinwald, P. (2024, April). Digital tools, including AI, alter consumer trust and purchasing decisions. Phys.org.
https://phys.org/news/2024-04-digital-tools-ai-consumer-decisions.html
Reuters. (2025, July 11). UN report urges stronger measures to detect AI-driven deepfakes. Reuters.
https://www.reuters.com/business/un-report-urges-stronger-measures-detect-ai-driven-deepfakes-2025-07-11/
Ribeiro, A. (2025). The impact of artificial intelligence on consumer behavior: A systematic literature review. Electronic Commerce Research, 25(1), 45–72.
https://doi.org/10.1007/s10660-025-10063-7
TechTarget. (2024, February 29). AI washing explained: Everything you need to know. TechTarget.
https://www.techtarget.com/search/ai/definition/ai-washing
Teepapal, T. (2025). AI-driven personalization: Unraveling consumer responses. Journal of Interactive Marketing, 62, 101–118.
https://doi.org/10.1016/j.intmar.2025.03.004
Whittaker, L. (2025). Examining consumer appraisals of deepfake advertising. Journal of Advertising, 54(3), 233–250.
https://doi.org/10.1080/00218499.2025.2498830
Wikipedia. (2023). Algorithm aversion. In Wikipedia.
https://en.wikipedia.org/wiki/Algorithm_aversion
Wikipedia. (2024). AI washing. In Wikipedia.
https://en.wikipedia.org/wiki/AI_washing
Zhang, L. (2025). The impact of generative AI images on consumer attitudes. Business and; Management, 15(10), 395.
https://doi.org/10.3390/bm15100395</References>
</References>
</Journal>
</Article>
</ArticleSet>