Can Retail Branding Survive the AI Era?

It took a Vogue ad to remind us: AI is everywhere, especially in retail. The backlash reignited debates around brand authenticity and creative control. So, can retail branding survive the AI era without losing the human touch that makes it resonate?
Side view of a mannequin wearing a denim dress, gradually dissolving into scattered digital pixels against a black background.

By Vana Antonopoulou, Director of Content & Community, RLC Global Forum 

 

A few weeks ago, a low-profile story sent quiet ripples through industry circles. In its August 2025 issue, Vogue US ran a Guess ad built entirely on AI-generated visuals, right down to the unmistakably computer-generated model, created by algorithm. The disclosure sat in the fine print, but the signal was clear: artificial intelligence has entered the conversation. And it’s not going away. 

The backlash—at least among creative professionals—was immediate. Behind the scenes, stylists, photographers, casting directors, and, yes, even models began to question whether this marked the beginning of an aesthetic unraveling. 

For brands that have spent decades curating every visual cue, AI introduces a new variable: content that’s fast, low-cost and often stripped of the human texture that gives a brand its emotional weight. And it raises a deeper question. Can retail branding survive the AI era if the visuals it presents no longer come from the worlds its customers actually live in?  

The illusion of perfection  

There’s a reason fashion photography has always chased imperfection: contrast, asymmetry, mood. AI-generated visuals, on the other hand, offer controlled polish, sharp lighting, symmetrical faces, seamless backdrops. The result? Commercially slick but creatively homogenous.  

This goes beyond an aesthetic theory. In discussions around AI imagery, critics warn of a “template-driven style,” where every image blends into the next. Getty Images, in their 2024 report “Building Trust in the Age of AI”, found that nearly 90% of consumers globally want transparency when images are AI-created, highlighting that uniform, impeccably polished visuals can stir skepticism and erode trust. Creativity remains indispensable in connecting with consumers, especially amid growing distrust and visual saturation; in fact, 76% agree: “It’s getting to the point where I can’t tell if an image is real.” 

According to VisualGPS research, people define “authentic” as real or the real thing, followed by true or truthful, with 87% of respondents saying it’s important that an image feels authentic. 

Supporting that, the study “Human vs. AI: The Battle for Authenticity in Fashion Design and Consumer Response”, published on ScienceDirect, found that consumers consistently rate human-designed fashion more favorably than AI-generated alternatives, often perceiving AI outputs as lacking in brand essence or emotional connection. 

In other words, the actual risk isn’t that AI visuals look fake. It’s that they look like everyone else’s. For brands built on storytelling and visual distinctiveness, that sameness is a real vulnerability. 

As Dr. Rebecca Swift, Getty Images’ Global Head of Creative Content, put it: “Businesses across all industries are asking the question, ‘Should we be engaging with AI-generated content—and if so, how?’”  

Using AI without losing the plot 

Dr. Swift’s question is far from theoretical. In fact, the question isn’t whether AI belongs in your creative toolkit. It’s when to leave it out. And for those still asking can retail branding survive the AI era, the answer may depend less on whether AI is used, and more on when it shouldn’t be. 

AI is a tool, not a strategy. And choosing when to use it starts with one thing: intent. Not every campaign needs a rendered face or a machine-made backdrop. Sometimes the most strategic choice is the most human one. 

Recent research and creative standards point to a few things worth keeping in mind when deciding whether AI-generated content serves the work: 

  • Start with the message, not the method – The format should follow the story you’re trying to tell, not the other way around. 
  • If you’re asking for trust, show something real – Campaigns tied to credibility—think health, finance, travel—tend to perform better with imagery that feels lived-in, not generated. 
  • Don’t fake authenticity – When AI is used to depict people or real products, audiences notice—and not always in a good way. Transparency matters. 
  • Don’t outsource the creative leap – AI can remix what already exists. But it can’t respond to a mood, a shift in culture, or what your audience needs right now. 
  • Use the safe stuff, not the sketchy stuff If you’re using AI commercially, make sure the content is rights-cleared and legally sound. What feels like a shortcut can turn into a liability. 

With great power comes great responsibility, as they say. Used well, AI gives creative teams speed and options. Used blindly, it risks producing campaigns that feel generic, disconnected, or—worse—misaligned with what the audience actually cares about.  

Can AI pass the brand test? 

The Vogue x Guess campaign didn’t go unnoticed. In fact, it left people unsettled. Not because AI was used, but because something about the result felt off. It looked like fashion, but it didn’t quite feel like it. It worked in drawing attention, but not in the way anyone expected. 

To me, this has nothing to do with ethics, at least not yet. It’s about timing, judgment, and control. It’s about how far brands and creatives are willing to let AI into the process and whether they understand what’s at stake when they do. 

So, can retail branding survive the AI era? Yes—but only if brands stop treating AI as a creative autopilot. It can assist, accelerate, even inspire, but it cannot replace human taste or intent. At the end of the day, AI doesn’t erode brand identity. Complacency does. 

The Vogue moment was a stress test. And the backlash proved something important: people are still paying attention. That matters, because attention is leverage. If consumers notice when a brand gets it wrong, they’ll notice when a brand gets it right. And that kind of awareness is something no algorithm can manufacture. 

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