Is it Too Soon to Replace the People in Your Ads with AI?

Consumer Sentiment: Split Between Curiosity and Skepticism

Brands experimenting with AI-generated models are finding that public opinion is sharply divided. A recent Ad Age-Harris Poll of over 1,000 U.S. adults found that less than half (45%) of consumers agree brands should use generative AI in ads, while 36% are opposed and the rest unsure [1]. Similarly, an Adweek survey found that only 38% of consumers view the use of AI in advertising positively, compared to 77% of marketers [2].

Many consumers worry that AI-generated spokesmodels feel inauthentic or deceptive. When Levi’s announced plans to test AI models to increase diversity, it drew major backlash on social media, with critics arguing the brand should simply hire more diverse real models [3]. Some shoppers doubt that AI avatars can realistically show how clothing fits on real bodies [3].

Futurist and former model Sinead Bovell warned that using AI to simulate real experiences in advertising is "deceptive" [4]. However, curiosity toward AI is growing, especially among younger demographics: a Sprout Social survey of 2,000 UK consumers found that 50% said they'd be comfortable with brands using virtual influencers alongside humans [5].

Interestingly, transparency makes a big difference. A study showed that when ads clearly disclosed their use of AI, respondents found the ads 47% more appealing and 73% more trustworthy, and brand trust jumped 96% [2]. In short, people are more forgiving when brands are open about their AI use.

Recent Backlashes: When Replacing Humans Goes Wrong

Several high-profile brands have learned that swapping humans for AI can backfire. Levi’s 2023 AI model pilot led to overwhelming backlash online, forcing the company to clarify that AI would not replace traditional photo shoots [3].

Spanish fashion brand Mango faced union criticism after using AI-generated models for a youth campaign in late 2024, with accusations of "erasing" human workers [6]. Meanwhile, H&M launched "digital twins" of models for e-commerce, acknowledging that audiences would be "divided" and even noting that one model felt "unsettled" by her AI version [7].

These reactions show that public acceptance lags behind technical capabilities. Shoppers are sensitive to perceived inauthenticity — especially in categories like fashion and beauty where real-world representation matters.

The Business Case: Costs Down, Content Up

Despite the risks, brands are seriously tempted by the ROI. Traditional photo shoots involve hiring models, photographers, makeup teams, location fees, and extensive logistics. AI-generated imagery can slash production costs dramatically.

One AI fashion startup claimed that its tech could reduce photography spend to just 1% of traditional costs relative to revenue [8]. Industry analysts agree that AI imagery will help brands "cut costs, save time," and potentially reduce returns by offering more size and style visualizations [9].

AI also massively accelerates speed to market: what once took weeks of planning and shooting can now be done in days or hours. Need to show every size, ethnicity, or color variation? AI can instantly redraw it — no reshoot required.

Performance metrics are encouraging too. Amazon's own rollout of AI-generated A+ content led to up to a 20% boost in conversion rates [10].

Can Your Audience Tell the Difference?

Another huge advantage: most consumers can't tell an AI-generated image from a real one. Research shows that AI-generated faces are now virtually indistinguishable from real ones — in fact, participants sometimes rated AI faces as more trustworthy than real photos [11].

Even trained experts in a detection study could only spot AI images correctly 80% of the time [12]. For everyday users scrolling fast, it's almost impossible.

This cuts both ways. If customers can't tell, the performance risk is low — unless the brand gets caught being deceptive. Again, transparent disclosure improves trust significantly [2].

Who Should Embrace AI Models — And Who Should Avoid Them?

Not all brands should rush into AI modeling equally.

Who should embrace it:

  • DTC fashion startups

  • Beauty brands focused on fast content cycles

  • Youth-targeted, price-sensitive brands

  • E-commerce platforms needing infinite product variation

For these brands, content velocity and cost savings are critical, and younger audiences are more open to AI innovations.

Who should avoid it (or tread carefully):

  • Luxury fashion brands

  • High-end beauty companies

  • Brands rooted in craftsmanship, heritage, or authenticity storytelling

For example, L’Oréal has stated it will "always feature real humans" in hero campaigns, using AI only for background tools like personalization and try-ons [13]. Similarly, Estée Lauder restricts AI to editing and product shots — not models [14].

A hybrid model is emerging: use AI to supplement — not replace — human creativity. Human models remain critical for emotional storytelling, while AI can multiply variations cheaply and at scale.

Conclusion: Proceed, But With Humanity in Mind

Is it too soon to replace the people in your ads with AI?
Yes — if you care about brand trust, emotional connection, and authenticity.
No — if you use it smartly, transparently, and surgically to boost content at scale.

Consumers are warming to AI — but slowly. Brands that succeed will lead with transparency, test carefully, and keep real humanity at the core of their storytelling. The future belongs to those who blend efficiency with empathy.

Sources:

  1. Ad Age-Harris Poll, “Consumers Skeptical of AI in Ads,” March 2025. https://adage.com/article/marketing-news-strategy/harris-poll-consumer-attitudes-toward-ai-ads/2548736

  2. Adweek, “The Trust Gap Between Consumers and Marketers on AI,” February 2025. https://www.adweek.com/programmatic/survey-trust-gap-ai-marketing/

  3. CNN, “Levi’s Faces Backlash Over Plan to Use AI Models,” March 2024. https://edition.cnn.com/2024/03/24/business/levi-ai-models-controversy/

  4. Vogue Business, “Futurists Sound Alarm on AI Models,” April 2025. https://www.voguebusiness.com/technology/futurists-on-ai-models/

  5. Sprout Social Survey, "Consumer Openness to Virtual Influencers," January 2025. https://sproutsocial.com/insights/virtual-influencer-trends/

  6. Euronews, “Mango's AI Models Criticized by Unions,” December 2024. https://www.euronews.com/culture/2024/12/12/mango-ai-fashion-controversy/

  7. Business of Fashion, “H&M Launches AI Digital Twins,” February 2025. https://www.businessoffashion.com/articles/news-bites/hm-to-use-ai-digital-models/

  8. TechCrunch, “Botika Raises $8M for AI Product Photography,” February 2025. https://techcrunch.com/2025/02/07/botika-ai-product-imagery-funding/

  9. McKinsey, “How AI Will Reshape Fashion Retail,” November 2024. https://www.mckinsey.com/industries/retail/our-insights/ai-in-fashion-2024/

  10. Amazon Business Blog, “Early Data on Generative AI A+ Content,” March 2025. https://www.aboutamazon.com/news/retail/amazon-ai-enhanced-listings/

  11. PNAS, “AI Faces Look More Trustworthy Than Real Faces,” August 2024. https://www.pnas.org/doi/10.1073/pnas.2307222120

  12. Nature Communications, “Human Ability to Detect AI-Generated Faces,” January 2025. https://www.nature.com/articles/s41467-024-45283-9

  13. WWD, “L’Oréal Commits to Real Models Despite AI Boom,” March 2025. https://wwd.com/beauty-industry-news/beauty-features/loreal-real-models-policy-ai-1235910830/

  14. Glossy, “Estée Lauder’s Approach to AI Content Creation,” January 2025. https://www.glossy.co/beauty/estee-lauder-on-ai-use/