Summary of Findings

Consumer information processing

The speed at which Artificial Intelligence (AI) works has reshaped the way consumers process information. Personalized recommendations and dynamic ad targeting ensure consumers are constantly receiving “right message, right moment, right place” communication (Yao, n.d. -a). This approach enhances engagement and efficiency; however, it does risk information overload. As consumers encounter more AI-generated content, skepticism rises, prompting them to scrutinize sources more carefully. In some cases, like with Whataburger’s response to Taylor Swift’s engagement seeming too on the nose for TikTok creator @rachelissan, consumers may assume authentic messages are AI-generated (Issan, 2025). This new need to process whether the content is human or AI-generated may lead to AI and information fatigue.

Content generation

AI can generate content at a scale that surpasses that of humans. Tools like Jasper can create “produce blogs, social media posts, web copy, sales emails, ads, and other types of consumer-facing content” (Davenport & Mittal, 2022). This repaid production is not without error, though, as outputs often require human refinement to correct mistakes, cultural missteps, or repetitive phrasing (O’Brien, 2023). A hybrid model where the AI handles efficiency-driven tasks while marketers focus on originality currently proves to be the most effective approach (George, 2025). Through this model, marketers ensure higher speeds of content creation without losing authenticity.

Authenticity

Briefly discussed above, authenticity is a major challenge when using AI in marketing. In the Pepperdine Journal of Communication Research, Elizabeth Burrow (2025) writes, “Authentic ads evoke a positive emotion, which evokes brand warmth, leading to a positive attitude towards the brand and increased intentions to engage.” However, when that brand’s content feels generic or manipulated, it is logical for a consumer to lose trust in the company. To combat these negative feelings, transparency must come into the equation. Without disclosure, audiences may feel deceived and have a permanent negative opinion of the brand. Ethical considerations, including bias amplification and data privacy, add complexity to authenticity concerns (Bale et al., 2023). The hybrid model above can help counteract these challenges and preserve credibility by combining AI support with human oversight.

Brand trust

Brand trust depends on maintaining consistency, transparency, and responsiveness. As skepticism around AI grows, consumers may even doubt authentic campaigns, as seen with Whataburger (Issan, 2025). However, there are brands whose use of AI reinforced consistent voice and values. For example, Heinz utilized AI to show that AI has been trained on their bottle as the common image of ketchup (Heinz, 2022). Brands sustain trust with consumers when they apply AI responsibly, disclose their use, and engage directly with consumers to clarify doubts.

Strategic Recommendations

The role of AI-generated content and human-created content in marketing communication.

Through the hybrid model, AI-generated content is most effective for efficiency-driven functions such as initial drafting of social media captions, repurposing existing content to fit different platforms, and testing variations of advertisements. Human-created content remains essential for storytelling, emotional resonance, and cultural awareness (Basiura, 2024). With AI’s current abilities, it is wise for marketers to adopt this hybrid model that allows for accelerated production but maintains originality and authenticity. This balance maximizes scalability without compromising connection.

The balance between personalized content and mass communication strategies.

AI enables precision targeting and personalization, strengthening engagement and loyalty. Even with this ability, personalization alone cannot achieve broad market visibility. Mass communications strategies, such as brand-wide campaigns, remain crucial for building recognition and cultural presence. Combining personalized engagement with large-scale campaigns ensures both width and depth. For example, Starbucks uses nationwide campaigns to establish awareness, then has an app that uses AI-driven tools that personalize marketing content for the user, such as drink “recommendations when the client is approaching their local store” (0tcarvalho, 2020).

Strategies for maintaining credibility and trust with AI-generated content.

Brands can preserve credibility through three key practices. First, brands should adopt clear disclosure policies, signaling when AI is involved in creation. Research shows that transparency fosters accountability and reduces consumer suspicion (Burrow, 2025). Second, content should undergo rigorous fact-checking and human review to correct errors and filter out bias (O’Brien, 2023). Third, marketers should emphasize hybrid models to keep a human voice present in final outputs. These strategies ensure AI-generated content supports rather than undermines brand reputation.

Ethical considerations of using AI-generated content in marketing.

AI marketing raises ethical concerns around transparency, bias, privacy, and copyright. Without disclosure, consumers lack agency to evaluate whether content is authentic (Burrow, 2025). Bias in training data can perpetuate stereotypes, potentially damaging brand image (Qureshi, 2023). Additionally, data privacy remains a pressing issue, as personalization depends on sensitive consumer information (Bale et al., 2023). To act responsibly, brands should create internal ethical guidelines governing AI use, invest in explainable AI systems, and commit to safeguarding consumer data. These measures prevent reputational damage and align marketing practices with consumer expectations of fairness and honesty.

Strategies for adapting and strengthening brand trust in the evolving marketing ecosystem.

By integrating transparency, consistency, and human engagement into their AI strategies, brands can strengthen trust between themselves and the consumer. When they see clear labeling of AI-generated content, the company reassures consumers that they value honesty. Whataburger is a great example of my final point. Through direct customer engagement, commenting on the TikTok post and clarifying where the image was from (Issan, 2025), consumers see that real people stand behind the brand. This responsiveness converts skepticism into opportunities for connection. Brands that adopt these practices not only protect credibility but also differentiate themselves in a marketplace where consumer doubt is high.

References

Bale, A. S., Dhumale, R. B., Beri, N., Lourens, M., Varma, R. A., Kumar, V., Sanamdikar, S., & Savadatti, M. B. (2023, August 28). The Impact of Generative Content on Individuals Privacy and Ethical Concerns. International Journal of Intelligent Systems and Applications in Engineering, 12(1s), 697–703. https://doi.org/10.18201/ijisae.2024.3503

Basiura, L. (2024, September 16). AI vs. humans: Who will win the content creation game?. Marketing Insider Group. https://marketinginsidergroup.com/artificial-intelligence/ai-vs-humans-who-will-win-the-content-creation-game/

Burrow, E. (2025). AI-generated versus human-generated: Creative content in advertising. Pepperdine Journal of Communication Research, 13(1), Article 8. https://digitalcommons.pepperdine.edu/pjcr/vol13/iss1/8

Davenport, T. H., & Mittal, N. (2022, November 14). How generative AI is changing creative work. Harvard Business Review. https://hbr.org/2022/11/how-generative-ai-is-changing-creative-work

George, M. (2025, February 4). Ai Vs human-driven marketing: Why a hybrid approach works best? -growth-onomics. Growth-onomics. https://growth-onomics.com/ai-vs-human-driven-marketing-why-a-hybrid-approach-works-best/

Heinz A.I. Ketchup: Just like humans, A.I. prefers Heinz. Campaigns of the World. (2022, August 17). https://campaignsoftheworld.com/digital-campaigns/heinz-a-i-ketchup/

Issan, R. [@rachelissan]. (2025, August 28). The Cringiest to Cutest Brand Reactions to Taylor’s Engagement [Video]. TikTok. https://www.tiktok.com/@rachelissan/video/7543408539704757518

O’Brien, M. (2023, August 1.) Chatbots sometimes make things up. Is AI’s hallucination problem fixable? AP News. https://apnews.com/article/artificial-intelligence-hallucination-chatbots-chatgpt-falsehoods-ac4672c5b06e6f91050aa46ee731bcf4

Qureshi, S. (2023). Cycles of development in systems of survival with artificial intelligence: aformative research agenda. Information Technology for Development, 29(2–3), 171–183. https://doi.org/10.1080/02681102.2023.2236424

Yao, M. (n.d. -a). Programmatic Media Buying and Addressable Marketing in the Attention Economy [MOOC 1]. Coursera. https://www.coursera.org/learn/digital-marketing-strategy-media-and-ai/lecture/tP9JZ/programmatic-media-buying-and-addressable-marketing-in-the-attention-economy

0tcarvalho. (2020, April 23). 10 brands that are successfully using artificial intelligence. VisionSpace. https://visionspace.com/10-brands-that-are-successfully-using-artificial-intelligence/