AI in Advertising vs. Marketing: How Context Changes Everything

‍When AI shows up in emotional advertising, audiences notice. When it powers personalization and scale, they barely do. Why context matters more than the technology.

The conversation around AI in advertising has become increasingly polarized. Headlines warn about “AI slop,” and critics highlight the repetitive look of AI-generated visuals across digital platforms. When a few high-profile campaigns stumble, the reaction is quick and the takeaway often sounds the same: audiences just don’t like AI in advertising.

But it’s not that simple.

Over the past two years, brands experimenting with AI-assisted creative have faced some very public pushback. When Coca-Cola released AI-supported holiday advertising, some viewers felt the imagery looked uncanny and overly polished. A McDonald’s holiday campaign was pulled after people criticized it for feeling artificial and emotionally flat. A 2025  Guess campaign featuring AI-generated models sparked debate after it appeared in Vogue.  The criticism wasn’t really about the brands themselves. It was about how AI showed up in moments that were meant to feel warm, nostalgic and emotionally genuine.

More recently, brands have started to take a more explicit stance. In March 2025, Aerie featured Pamela Anderson in a campaign reinforcing its commitment to real, unretouched imagery and announced it would not use AI-generated bodies. The move reflects growing sensitivity around authenticity in emotionally charged categories like identity and representation.

At the same time, AI has quietly become part of many other areas of marketing. Brands use it to create product image variations, localize creative for different regions, adapt campaigns for seasonal moments and personalize digital content at scale. In these spaces, resistance is minimal. Most people barely notice.

That contrast is telling. The tension isn’t about AI alone; it’s about context.

Advertising and marketing often get grouped together, but audiences experience them in very different ways.

Advertising carries emotional weight. Audiences expect intention and care behind the craft, and when that feels missing, they notice.

Generative imagery is now easier to spot; faces may appear too perfect and environments overly polished, creating work that feels emotionally flat. None of these details automatically make creative ineffective, but they can interrupt the emotional flow that strong storytelling depends on.

Research helps explain why this reaction happens. Studies from organizations such as Edelman and Kantar continue to show that authenticity and credibility are central to brand trust. Advertising that connects emotionally still outperforms work optimized purely for efficiency or scale. When synthetic visuals become the focus, the story can lose its impact.

That sensitivity is also beginning to show up in regulation. In New York, new legislation requires advertisers to disclose when synthetic performers are used in ads, reflecting growing concern around transparency as AI-generated content becomes more widespread.

Expectations change in other parts of the marketing ecosystem. Think about where people encounter marketing most often: e-commerce platforms, product pages, performance ads and localized digital campaigns. In these moments, audiences aren’t looking for emotional narratives. They want useful information. 

Here, AI can genuinely improve the experience.

In her work leading large-scale content and commerce programs for major brands and retailers, Sylvie Lamont, Chief Creative Officer at SJC, sees this distinction clearly.

“When it comes to volume in e-commerce, AI has made it possible to personalize and get intimate with people’s preferences, wants or needs,” she says. “Customer data is driving AI, and communication no longer needs to be generic.”

AI helps creative teams quickly adapt assets across regions, languages and seasonal moments. Instead of one standardized asset, brands can develop variations that feel more relevant to the setting in which they appear. This is where many brands are focusing their AI efforts today—using it to scale content and improve relevance across channels while maintaining a consistent creative standard.

The expectations in these interactions are different. People are focused on usefulness, not brand mythology. AI-generated product variations or localized messaging don’t disrupt the experience because practicality comes first.

Marketing helps people decide. Advertising helps people feel.

Positioning AI and authenticity as opposites oversimplifies what’s happening. The conversation is often framed as a choice between efficiency and creativity, as if one must come at the expense of the other.

In practice, the strongest work tends to sit somewhere in between.

Lamont describes authenticity as something shaped by human judgment rather than tools.

“Authenticity in creative right now means human-driven critical thinking,” she says. “Whether it's through traditional craft or creative prompts, developing unique concepts and content with AI tools, creative must be human-driven and true.”

Early excitement around AI’s capabilities has given way to more discerning audiences who can quickly recognize synthetic content.

“I'm starting to see signals that audiences are becoming more sensitive to AI-generated creative,” Lamont explains. “When AI first hit the market, the possibilities were new and exciting. But hallucinations and fakes became very prominent, creating a sense of distrust. Authenticity is increasingly essential.”

For brands, the question is less about whether to use AI and more about how to apply it thoughtfully.

Many creative teams are now exploring hybrid approaches that combine real-world production with AI-assisted enhancements. As Lamont recently noted in a conversation on AI and authenticity, the most effective work often preserves realism while using AI to extend environments, adapt assets or scale production.

This kind of approach is becoming more common. Brands are using AI in their creative process to simplify production, easily adapt executions and scale assets. The goal is to maintain authentic human storytelling, not to create entirely synthetic campaigns.

When used this way, AI supports the work instead of overshadowing it.

Audience expectations also differ across content environments. Journalism, for example, operates under stricter standards of transparency and human oversight. Credibility depends on visible editorial judgment, and audiences understand why that matters.

Marketing and advertising operate under their own expectations. When those expectations are met, the technology behind the creative rarely becomes the focus.

For marketers and business leaders, the key takeaway is to focus less on adopting every new tool and more on applying thoughtful judgment, such as evaluating when AI enhances authenticity and when human creativity should take the lead.

Consumers are not broadly opposed to AI. In many cases, they don't even notice it. When someone receives a flyer tailored to their region and language, that's AI at work. It just feels like relevant content. What people actually respond to is whether AI's use feels appropriate for the moment and the message.

“The biggest opportunity is to use AI for personalization and scale,” Lamont says. “AI tools leverage brand and consumer data to customize content and create true intimacy with brands, allowing consumers to fully engage and connect.”

To shape the future of brand creativity, marketers should develop clear guidelines for integrating AI, prioritize authenticity and continually assess when technology supports or detracts from human-driven storytelling.

Ultimately, the debate around AI and authenticity may have less to do with the technology itself and more to do with context and how and where it shows up in the stories brands choose to tell.

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Survi Sahni is a fourth-year journalism student at Toronto Metropolitan University who researched and wrote this article during her internship with Canadian Business.

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