Do Shoppers Trust AI-Generated Product Images? We Asked
Stylitics Marketing Team
The Stylitics Marketing Team explores the intersection of AI, retail, and shopper experience, sharing strategies and insights that shape the future of product discovery and visual merchandising.
On-model imagery drives confidence: 76% of shoppers in our study said model photos are the most useful format for purchase decisions.
Accuracy is critical: While 71% couldn’t tell whether an image was real or generated by AI, shoppers quickly lost confidence when details like buttons, wrinkles, or fabric texture looked wrong.
Disclosure builds trust: 59% wanted clear labeling of AI imagery, interpreting disclosure as a sign of honesty and integrity.
Return policies help reduce anxiety: 55% of shoppers said they felt more comfortable buying from AI-generated photos if clear return policies were in place.
For many in retail, this feels like a bold step forward and a signal of how quickly experimentation with AI imagery is moving into live e-commerce environments. But it also raises a critical question: will shoppers actually believe what they see?
To explore this, Stylitics partnered with Aha Studio to survey 411 shoppers across web and social contexts. The results reveal a clear pattern: consumers aren’t rejecting AI imagery outright, but they expect accuracy, honesty, and brand consistency before they’ll buy.
Do Shoppers Trust AI-Generated Images?
Download the full study and gain insight on how 400+ shoppers really feel about AI imagery in fashion ecommerce.
Product photography has always been central to fashion e-commerce. Shoppers rely on on-model photos, flat lays, and packshots to answer two core questions:
Information: “Will this actually work on my body?”
Inspiration: “How will this clothing item fit into my life and reflect my style?”
The study confirms that on-model photography remains the most influential format. A full 76% of shoppers said model photos were the most helpful for purchase decisions. Whether captured with human models, AI-generated models, or virtual models, the ability to show drape, proportion, and real-world styling is essential.
For retailers, this creates both opportunity and challenge. Early tests suggest AI-powered imagery could provide new ways to expand coverage and experiment with styling variety. But every generated image also carries risk: a mismatched button, an unnatural model pose, or skin that looks “too airbrushed” can quickly erode shopper confidence.
Perception vs. Reality: Can Shoppers Tell the Difference?
One of the most telling findings came from side-by-side tests. When shown a real photo and an AI-generated reference image of the same product, 71% of shoppers said the images looked the same or had only small differences.
This indicates that when quality is high, many shoppers don’t focus on whether an image is “real” or AI-generated—they pay attention to execution details such as:
“The buttons on the AI version were the wrong color.”
“The vest had no wrinkles, which looked unnatural.”
“The AI model’s face was too airbrushed.”
In other words, execution matters more than the medium. High-quality visuals, whether AI-generated or photographed, can build confidence, while poor execution in either format risks breaking shopper trust.
Emotional Response: Shoppers Are Split, Not Hostile
When told explicitly that they were viewing AI-generated models and scenes, shoppers showed a wide range of emotions:
60% felt neutral or positive. 36% said it was “interesting but not a big deal,” and 24% reacted with “Cool! That’s smart.”
31% reacted negatively. Concerns centered on authenticity and realism.
8% had already guessed it was AI.
Breaking this down further:
Men were more receptive (30% positive, 25% negative).
Women were more skeptical (20% positive, 35% negative).
These differences suggest that responses to AI imagery vary by audience. For some shoppers, AI visuals may inspire curiosity or feel efficient; for others, they raise questions about product accuracy and fit.
Shopper Concerns in Their Own Words
The study revealed three distinct shopper personas when it comes to AI-powered visual creation:
The Enthusiast: “This saves time and money. Extremely effective!”
The Pragmatist: “As long as the clothes are accurately represented, I don’t mind.”
The Skeptic: “I want to see clothes on real people. AI makes things look too perfect.”
Key worries included:
AI “idealizing” fit in unrealistic ways.
Inaccurate colors, fabric textures, or design details.
Feeling misled, which shoppers linked to higher return rates.
Overall, most shoppers base their trust on execution quality: they’re less concerned about whether an image is AI or real, and more concerned with whether it’s accurate. That said, a portion of shoppers remain skeptical of AI imagery regardless of execution, which underscores the need for accuracy, transparency, and brand alignment.
The Return Policy Effect: Reducing Perceived Risk
Trust is not just about the image itself—it’s about what happens after purchase.
The study found that 55% of shoppers said they would feel more comfortable buying from AI-generated product photos if a clear return policy was in place. This suggests that policies and guarantees play a significant role in shaping shopper comfort with new types of visuals. Flexible return options can signal confidence and reduce perceived risk, particularly when shoppers are evaluating AI-generated backgrounds, styled scenes, or virtual try-on features that may not always perfectly match reality.
Transparency Builds Brand Equity
Shoppers consistently expressed one request: tell me if an image is AI-generated.
59% wanted clear labeling, either as a direct label like “Virtual Model” or a small note/disclaimer.
26% were fine with minimal disclosure, but not none at all.
Only 15% opposed AI outright, preferring brands not use it at all.
Quotes from participants reveal why disclosure matters:
“It makes the brand feel more honest.”
“Adds a level of trust for the website and the brand.”
“I feel less cheated if it’s disclosed.”
These results suggest that clear, visible labeling can help strengthen shopper trust. When disclosure is handled consistently, it may even become a positive brand signal, demonstrating innovation while maintaining honesty.
Strategic Roadmap: Exploring Phased Adoption of AI Imagery
Stylitics’ research points to a phased way retailers may consider exploring AI-powered fashion imagery over time:
Phase 1: Establish a Visual Baseline
Research consistently shows shoppers prefer on-model photos over other formats. The first priority for retailers is ensuring PDPs have strong on-model coverage. AI imagery is being tested as a possible complement to human photography in filling gaps, but accuracy and brand alignment remain essential.
Phase 2: Experiment with Inspiration
At the inspirational stage of the funnel, shoppers are more permissive of AI. Early tests suggest potential in using AI to explore style variations, contextual backgrounds, and multiple outfit combinations, formats that spark imagination while carrying lower accuracy risk than fit-focused imagery.
Phase 3: Master Fit Accuracy
The most technically demanding challenge is showing size, fit, and body diversity accurately. Future applications may explore 360-degree rotations and diverse body types, but this requires rigorous quality control and remains an area of ongoing testing rather than solved capability.
Implications for Marketing Content and Ad Performance
The potential role of AI imagery extends beyond PDPs. Some retailers are beginning to test AI-powered visual content in areas such as:
Social media campaigns with virtual models wearing new drops.
Ad creatives built from a library of templates with drag-and-drop editors.
Email marketing content showcasing seasonal clothing collections with generated images.
Batch jobs to update hundreds of SKUs with new AI backgrounds.
Early signals suggest that consistency is key. AI imagery that aligns with brand rules and aesthetic standards may improve performance across channels, while inconsistent visuals risk creating friction.
Beyond Fashion: Expanding Use Cases
While this study focused on apparel, the lessons may extend across other verticals. Potential applications being explored include:
Jewelry: AI-generated packshot images with consistent lighting and polish.
Home décor: Virtual backgrounds or staged scenes to show furniture in aspirational settings.
Footwear and accessories: 3D models or virtual try-on experiences that help shoppers visualize complete looks.
Across these categories, the opportunity is similar: to narrow the confidence gap by providing visuals that are realistic, inspiring, and aligned with brand standards.
Conclusion: Trust Hinges on Quality, Transparency, and Utility
So, do shoppers trust AI-generated fashion product photos? Our research suggests many are open to them, if key conditions are met:
Execution quality: Shoppers lose confidence quickly when product details are inaccurate.
Transparency: Clear labeling helps build brand integrity and trust.
Risk reduction: Flexible return policies help reassure hesitant buyers.
The future of AI-powered fashion imagery is not about replacing human creativity. It’s about combining AI tools with brand expertise to create richer, more versatile, and more confidence-inspiring content.
Stylitics’ research indicates that phased approaches, starting with inspiration, then testing accuracy-focused applications, may offer a safer path forward. Shopper sentiment is not uniform, but the evidence shows trust is most likely to be earned when imagery is accurate, transparent, and aligned with brand standards.
FAQ
Many shoppers are open to AI imagery if it is accurate and high-quality. Our research shows trust depends more on realism and detail than on whether an image is AI or real.
In our survey, 71% said AI and real images looked the same or had only small differences. While many can’t distinguish at a glance, they quickly notice inaccuracies in details like fabric, buttons, or proportions.
60% reacted neutrally or positively, while 31% expressed skepticism. Sentiment is mixed, with some shoppers curious and others concerned about authenticity and fit.
Research suggests that clear disclosure and flexible return policies help reduce shopper anxiety. 59% of participants wanted AI labeling, and 55% said they felt more comfortable if returns were easy.
