The Effect of Generative AI Content on Consumer Trust and Brand Perception

Background to the Study

The emergence of generative AI tools capable of producing human-like text, photorealistic images, and increasingly convincing video has introduced a transformative capability into marketing content production. Brands now routinely deploy generative AI to draft advertising copy, generate product imagery, produce social media captions, and even create video advertisements, substantially reducing the time and cost historically associated with content creation. This capability promises marketers unprecedented scale and speed in content production, enabling continuous, highly personalised brand communication across digital channels.

However, the same generative capabilities that enable efficient content production also raise fundamental questions about authenticity, transparency, and trust. Unlike earlier forms of AI-assisted marketing, such as recommendation engines or targeting algorithms, generative AI directly creates the content that consumers see, read, and evaluate, placing AI in the role of an ostensible communicator rather than merely a background optimisation tool. Consumers are increasingly exposed to AI-generated brand content without always being aware that it was AI-generated, a condition that recent research suggests can significantly shape their evaluative responses once AI involvement becomes known or suspected — a dynamic our related piece on AI transparency and consumer trust in brands explores from the disclosure side specifically.

Consumer trust, understood as a consumer's willingness to rely on and be vulnerable to a brand's communication based on positive expectations of its honesty and competence, and brand perception, encompassing the broader cognitive and affective associations consumers hold about a brand, are both foundational to long-term brand equity and customer relationships. The introduction of generative AI into brand content creation introduces a novel variable into the formation of both constructs: consumers must now, often implicitly, evaluate not only the content of a brand's communication but also its provenance, human or machine, and the brand's transparency regarding that provenance. Regulators are taking notice too — in the United States, the FTC's Guides Concerning the Use of Endorsements and Testimonials in Advertising now explicitly address AI-generated endorsement content, while in Nigeria, brands across e-commerce, financial services, and fast-moving consumer goods sectors have begun experimenting with generative AI tools for advertising copy, product visuals, and customer-facing chatbot content, even as public discourse around AI-generated misinformation and synthetic media grows increasingly prominent globally.

Statement of the Problem

Despite the rapid and growing adoption of generative AI tools for marketing content production, it remains unclear how the presence, and particularly the disclosure or non-disclosure, of generative AI content affects consumer trust and brand perception. Many brands have begun incorporating generative AI into advertising copy, product imagery, and social media content without a clear empirical understanding of whether, and under what conditions, such use strengthens or undermines the very consumer relationships that marketing communication is intended to build.

This uncertainty is compounded by growing public concern regarding synthetic media, deepfakes, and AI-generated misinformation, which may prime consumers toward heightened scepticism when they encounter, or suspect they have encountered, AI-generated brand content. At the same time, research on human perception of AI-generated content suggests that consumers are often unable to reliably distinguish AI-generated from human-created content, raising the further question of how brand trust and perception are shaped not only by actual AI content use but by consumers' beliefs, whether accurate or mistaken, about such use. Existing literature on generative AI in marketing has predominantly examined the technical capabilities and creative-output quality of generative tools, with comparatively limited empirical attention paid to the downstream consumer-trust and brand-perception consequences of generative AI content use, particularly within emerging market contexts. It is this gap that the present study seeks to address.

Aim and Objectives

The aim of this study is to examine the effect of generative AI content on consumer trust and brand perception among selected online consumers. The specific objectives are to:

1. Assess the extent of consumer awareness and recognition of generative AI content in brand marketing.

2. Determine the effect of generative AI content use on consumer trust.

3. Examine the influence of AI-content disclosure on brand perception.

4. Evaluate the moderating role of perceived content authenticity on the relationship between generative AI content use and brand perception.

Research Questions

1. What is the extent of consumer awareness and recognition of generative AI content in brand marketing?

2. What effect does generative AI content use have on consumer trust?

3. What influence does AI-content disclosure have on brand perception?

4. What moderating role does perceived content authenticity play in the relationship between generative AI content use and brand perception?

Significance of the Study

This study holds significance for multiple stakeholders. For marketing practitioners and brand managers, the findings provide empirical guidance on whether and how to disclose generative AI content use, and on the conditions under which such use strengthens rather than undermines consumer trust, thereby informing more effective and reputationally safer content strategy decisions. For content creators and creative agencies, the study offers insight into how the balance between AI-generated efficiency and perceived authenticity should be managed in brand content production.

For policymakers and regulators, particularly those concerned with truth-in-advertising and consumer protection in the digital sphere, the study provides context-specific evidence on how generative AI content disclosure affects consumer outcomes, which may inform future regulatory guidance on AI-content labelling. For the academic community, it extends existing theory on source credibility and trust to the specific context of generative AI content within an emerging market. Students or professionals working on comparable AI-marketing or trust research may find it worth refining their own methodology with ScholarNestHub's research coaching support.

Scope of the Study

The study is focused on examining the effect of generative AI content on consumer trust and brand perception among online consumers who have had exposure to brand marketing content, including advertising copy, product imagery, and social media content, that may have been produced using generative AI tools. The conceptual scope is restricted to the constructs of generative AI content awareness, AI-content disclosure, perceived content authenticity, consumer trust, and brand perception.

Operational Definition of Terms

Generative AI

Artificial intelligence systems capable of producing new content, including text, images, audio, or video, in response to prompts, based on patterns learned from large training datasets.

Generative AI Content

Marketing content, including advertising copy, product descriptions, images, or video, produced using generative AI tools rather than created entirely by human authors.

Consumer Trust

A consumer's willingness to rely on and be vulnerable to a brand's communication based on positive expectations of its honesty, competence, and integrity.

Brand Perception

The overall cognitive and affective associations, impressions, and evaluations a consumer holds about a brand.

Brand Authenticity

The extent to which a brand is perceived by consumers as genuine, honest, and true to its stated values and identity.

AI-Content Disclosure

The practice of a brand explicitly informing consumers that a given piece of content was created, in whole or in part, using generative AI tools — a practice increasingly expected by regulators such as Nigeria's Advertising Regulatory Council of Nigeria, which oversees advertising and marketing communication compliance, including digital and AI-assisted content, across the country.

Synthetic Media

Media content, including images, audio, or video, that has been generated or manipulated using AI, encompassing both benign creative applications and deceptive uses such as deepfakes.

Conclusion

The most important number in this study isn't about whether AI was used — it's about what happened once consumers found out. Undisclosed generative AI content eroded trust; disclosed AI content, especially when it came across as authentic rather than a substitute for genuine brand voice, actually strengthened brand perception. That's a genuinely useful distinction for any brand currently debating whether to label AI-assisted content: the technology itself isn't the reputational risk. Hiding it is. Readers researching related marketing, AI, or consumer trust questions can find further comparative material in our marketing project topics library.

Frequently Asked Questions

1. Does using generative AI in marketing automatically damage consumer trust?

Not automatically — the study found that undisclosed generative AI content use has a significant negative effect on consumer trust, but disclosed use paired with perceived authenticity can actually strengthen brand perception.

2. Can consumers reliably tell AI-generated content apart from human-created content?

The study found consumer awareness and recognition of generative AI content to be only moderate, with many consumers reporting difficulty reliably distinguishing the two.

3. Why does AI-content disclosure improve brand perception?

Disclosure was found to have a statistically significant positive influence on brand perception, likely because it signals honesty and transparency rather than an attempt to pass AI-generated content off as fully human-created.

4. What is perceived content authenticity, and why does it matter so much?

It refers to how genuine and true-to-brand consumers perceive a piece of content to be, and the study found it significantly moderates the relationship between generative AI content use and brand perception — authentic-feeling AI use causes far less reputational damage than AI use perceived as deceptive.

5. What regulatory guidance exists around AI-generated advertising content?

In the United States, the FTC's Endorsement Guides explicitly address AI-generated endorsement content, while in Nigeria, the Advertising Regulatory Council of Nigeria oversees compliance for advertising and marketing communication, including digital and AI-assisted content.

6. What research design and sample were used in this study?

A descriptive survey design was used, with data collected from 384 online consumers determined using the Cochran formula for infinite populations, analysed with descriptive and inferential statistics in SPSS version 26.

7. Should brands avoid using generative AI in marketing content altogether?

No — the study frames generative AI content as a double-edged strategic tool that can strengthen or undermine trust depending on transparency and authenticity, rather than recommending brands avoid it entirely.

8. What did the study recommend for brands using generative AI content?

It recommended adopting clear AI-content disclosure practices, maintaining rigorous human oversight of AI-generated brand content, and avoiding uses of generative AI that could be perceived as deceptive or inauthentic.

9. Is this issue specific to developed markets, or does it apply to emerging markets like Nigeria too?

The study specifically examined this question within an emerging market context, addressing a gap in existing literature that has predominantly focused on the technical capabilities of generative tools rather than downstream consumer-trust effects.

10. What is the single biggest takeaway for a brand manager considering generative AI content?

That disclosure and authenticity, not the mere use of AI, are what determine whether generative AI content strengthens or damages consumer trust and brand perception.