Think Before Trend-Jacking Marketing in 2026: AI Ads Are Cheap. Credibility Is Not.

Jul 3
10 min read

AI is now embedded in advertising and marketing trends. It helps brands move faster than previous teams ever could on their own. But is it damaging reputation?

"When the power of love overcomes the love of power, the world will know peace." - Jimi Hendrix

But for many brands, especially brands built on trust, taste, performance, sustainability, wellness, or cultural credibility, AI has also created a new kind of brand risk: The ad may be too efficient.

Even if it's timely, funny, relevant culturally -- the comment section may still hate it.

That is the tension brands need to understand about marketing trends in 2026. AI is not automatically bad for advertising. In fact, it is becoming extremely useful behind the scenes. But when AI becomes the visible face of the brand, especially in categories where authenticity matters, it can make the work feel cheaper, lazier, more synthetic, and less trustworthy.

Consumers are already signaling that discomfort. One 2026 consumer sentiment survey cited by Business Insider found that 39% of U.S. consumers had a negative view of AI-generated advertising, 36% were neutral, and only 18% felt positively about it. That is not a small creative preference. That is a credibility problem.

It's Not Really AI Backlash. It's Broken Trust.

The brands most vulnerable to AI backlash are often the brands that have spent years building emotional equity around realness.

Outdoor brands. Wellness brands. Beauty brands. active lifestyle brands. Apparel brands. Food brands. Creator-led brands. Mission-driven brands. Anything where the customer wants to believe there is a real person, real product, real community, or real value system behind the campaign.

That is why the recent outdoor-brand AI controversies hit a nerve:

Via Fast Company:

There was viral criticism around Patagonia imagery, with an Instagram post alleging AI artifacts in model/product visuals and calling out the tension between Patagonia’s & REI's authenticity-driven brand and synthetic-looking creative. Because that example appears to be social commentary rather than a fully verified mainstream report, brands should treat it less as a legal case study and more as a warning signal: the internet is now trained to inspect brand imagery for signs of AI, and when a beloved trust-based brand appears to use it clumsily, people notice.

In June 2026, REI faced backlash after a Meta ad appeared to show a bike with distorted, impossible features, including what looked like two sets of handlebars. Reddit users accused the co-op of using “AI slop,” and the criticism centered on a deeper contradiction: REI had built a reputation around care, expertise, and environmental values, while the ad looked careless and synthetic. REI later said Meta had auto-enrolled the company into an AI personalization feature that altered a vendor image inaccurately, and REI apologized and opted out of the tool.

That detail matters.

The brand may not have intended to run an AI-looking ad. But the customer does not grade the backend workflow. The customer sees the output. And if the output looks fake, the brand feels fake.

The Empire State Building "trend-jacking" AI-generated Ads Show How Fast “Clever” Becomes “Slop" for 2026 Marketing Teams

Another recent example is the wave of brands using AI-generated versions of the Russian rooftopping couple who scaled the Empire State Building.

In July 2026, Angela Nikolau and Ivan Kuznetsov, also known as Beerkus, were arrested after allegedly climbing the Empire State Building spire, unfurling a banner, and kissing at the top. The stunt immediately went viral and sparked debate around spectacle, danger, fame, and copycat culture:

Brands quickly jumped on the moment. Industry coverage listed companies including YesMadam, PVR, Nykaa, Airtel, Kelvinator, DoorDash, Acer, Fast&Up India, Cisco, Tarte Cosmetics, and Samsung among those posting creative executions tied to the viral visual.

The problem is not that brands reacted to culture. Reactive marketing has always existed.

The problem is that AI now makes trend-jacking almost too easy. A viral image hits the internet, and within hours brands can generate their own version, drop in the product, add a caption, and post. But when everyone can do that, the output starts to feel automatic. Instead of looking culturally sharp, it can look opportunistic, lazy, and unearned.

Public comments around the trend included variations of “AI slop copy,” “lazy AI slop,” and “stop flooding the internet with AI slop.” The exact criticism varied by post, but the sentiment was consistent: people were not just reacting to the creative. They were reacting to the feeling that brands had automated their way into a cultural moment they had not earned.

This is the new risk of AI advertising: It does not just create bad ads, but rather it creates ads that reveal how little a brand understands the room.

An example of how to do this better, in our Stellar Action opinion: jump on a trend, but put in real effort to truly make it your own. Give it an authentic, human touch. Don't crowd the space with the same message every other brand is promoting with the same visuals. It's forgettable, at best.

We Believe: AI is Most Useful When Not Constantly, Blatantly Customer-facing

We don't believe AI is harmful for brands necessarily. We use it here at Stellar Action constantly. We used it right now to help us write and format this blog, pull reference URLs, etc. But the strategic concept came from us, and is edited to fit our worldview perfectly.

The mistake is using AI as a shortcut for taste, credibility, and lived context.

AI is extremely useful when it functions as the backstage operator of a marketing system. It can help teams move faster, test more ideas, identify patterns, and reduce the friction between strategy and execution. Google’s Performance Max, the ad-buying platform brands use on Google, for example, uses AI across bidding, budget optimization, audiences, creative, and attribution. Meta has also been expanding AI ad tools across creative generation, business assistance, and attribution, including reported improvements in incremental conversion measurement.

That is where AI belongs for many brands: in the infrastructure layer. You can use it to:

Analyze why one creator video outperformed another.
Organize UGC by angle, audience, objection, product benefit, and funnel stage.
Help performance teams spot patterns faster.
Identify which paid creator assets deserve more budget.

Plus many more use cases we've defined for our own clients. But be careful using it as the face of the campaign -- because in creator commerce, the face is the strategy.

The Result? Creator Commerce Becomes MORE Valuable as AI Content Becomes Sloppier & Cheaper

The more AI content floods the feed, the more valuable real human context becomes.

That is the biggest creator commerce opportunity right now.

Brands should not look at AI as a replacement for creators. They should look at AI as the operating system that helps them get more performance out of creator relationships.

The strongest creator commerce systems will use AI to support human-led testing. Creators make the actual content. AI helps organize, analyze, and iterate from what performs.

That distinction matters.

A creator filming a product after using it in a real routine has context. They know the language of their audience. They understand what sounds fake. They know what objections show up in the comments. They can show timing, frustration, delight, and social proof in a way that AI-generated creative often misses. It's that uncanny, slightly "off" vibe that's hard to articulate.

AI can help multiply the number of testable angles. But the raw material should still come from human usage, creator intuition, and actual customer responses.

In other words, the best use of AI is not “make me an ad.”

Instead, it's: “Show me why this ad worked, what we should test next, which creators are driving the strongest signal, and how we can turn this into a repeatable revenue system.”

Why AI Discernment Matters: The Peptide Category

Peptides are a useful example because the category sits at the intersection of wellness, performance, beauty, longevity, and health claims. That means creator commerce can be powerful, but credibility and compliance matter even more.

MAKE Wellness is one example of a peptide/wellness brand with clear creator and affiliate infrastructure. The brand’s own site and hub content reference affiliate pathways, customer pathways, and TikTok creator participation, and a recent MAKE Wellness post says TikTok Shop creators can participate without becoming a MAKE affiliate while qualified affiliates may also benefit from a bonus pool generated by unaffiliated creators.

That kind of structure is exactly where AI can help.

A peptide brand does not need AI-generated fake transformations, fake testimonials, or synthetic “doctor-style” content that erodes trust. It needs a system for creator education, claim discipline, performance testing, and content iteration.

AI can help a peptide brand map customer objections: What is a peptide? How do I use this? Is it safe? What does it do? Is this legitimate? Why is everyone suddenly talking about it?

AI can help turn those objections into creator brief angles.

AI can help organize creator content by audience segment: longevity-curious consumers, active women, beauty and skin-care buyers, recovery-focused athletes, wellness optimizers, or people already familiar with supplements.

AI can help flag risky claims before a creator script goes live.

AI can help compare creator videos against conversion metrics and isolate which angles produce clicks, add-to-carts, or purchases.

But the persuasive layer should still come from real people, real routines, and carefully controlled claims. That is especially important because peptides are under increasing scrutiny. Reuters reported in 2026 that FDA reviewers found little evidence supporting the compounding of several peptide ingredients and noted that many peptides had gained popularity through wellness influencer endorsements despite limited human evidence for safety and efficacy.

That is the point: in trust-sensitive categories, AI should make the marketing system smarter, not make the brand look less real.

Where AI Functions Best for Marketing in 2026

AI is strongest when it improves the backend of marketing without weakening the frontend of trust. The best use cases are:

1. Research and insight mining

AI can summarize customer reviews, comments, Reddit threads, competitor ads, creator posts, support tickets, and sales call notes. This helps brands find language customers actually use.

2. Brainstorming and creative direction

AI is useful for generating starting points: hooks, content angles, objections, audience segments, offer tests, creator brief structures, landing page ideas, and campaign themes. But it should not be treated as the final taste-maker.

A 2026 meta-analysis on generative AI and creativity found that humans collaborating with AI tend to outperform unaided humans, but AI can also reduce diversity in creative output. That is the tradeoff: AI can make teams faster, but without human taste, it can make everyone sound the same.

3. Creative testing systems

AI can help structure a testing matrix across hooks, creators, claims, formats, CTAs, and funnel stages. It can also help identify when a winning concept should be iterated instead of replaced.

This is where many brands get it wrong. They keep chasing new creative instead of extracting more signal from proven creative.

If a creator ad is already converting, the next move is not necessarily to ask AI for a brand-new concept. The next move is to iterate the winner: new hook, new opening visual, new testimonial cut, new offer frame, new landing page, new whitelisted version, new audience, new creator in the same persona cluster.

4. Performance analysis

AI can help teams understand which creative variables are driving performance. That includes creator type, first-frame structure, product demo style, proof point, objection handling, offer language, and audience fit.

5. Media buying and platform optimization

AI is increasingly embedded into paid media platforms. Google and Meta both position AI as core to campaign optimization, audience discovery, creative variation, attribution, and budget allocation.

Used carefully, platform AI can help brands scale faster. Used blindly, it can also reduce visibility and control. Gartner has warned that AI-driven paid media can make marketers more dependent on platform black boxes and make it harder to confidently measure and defend investments.

6. Creator enablement

AI can help creators move faster without replacing their voice. It can help generate outline options, organize talking points, resize content, create captions, summarize product education, and suggest follow-up edits based on performance. The key is that AI should support the creator’s natural language, not flatten it into brand-safe sameness.

7. Compliance and brand safety

For wellness, beauty, supplements, peptides, performance products, finance, or children’s products, AI can help flag risky claims, missing disclosures, unsupported promises, and inconsistencies before content goes live. That may become one of AI’s most valuable marketing roles: not making the ad, but preventing the ad from becoming a liability. Sidenote: It's crucial to keep AI hallucinations in mind -- it's a robot. It can make mistakes.

Where Brands Should Use AI Caution

Brands should be especially cautious using AI for:

Synthetic people.
Fake UGC or endorsements.
Fake product demos.
Fake transformations.
Health, wellness, or performance claims.
Mission-driven storytelling.

The more a brand depends on credibility, the less it should let obviously AI-generated creative carry the message. This does not mean every AI-assisted ad will fail. Coca-Cola, for example, has continued experimenting with AI-generated creative despite holiday season criticism, and some testing has shown that AI ads can perform well on traditional attention or brand metrics.

But even there, criticism focused on visible inconsistencies and a sense that the work felt uncanny or emotionally hollow.

That is the strategic distinction brands need to make:

An AI ad can test well with audiences.

It can still make the brand feel worse none-the-less.

The Future is Not AI Versus Creators. It's AI + Creator Commerce

The winning brands will not be the ones that reject AI entirely. They will be the ones that know where AI belongs in their system.

AI belongs in the research layer, the testing layer, the analytics layer, the briefing layer, the media optimization layer, and the operational layer.

Creators belong in the trust layer.

Customers do not want to feel like they are being sold to by a machine pretending to be a person. They want proof. They want context. They want taste. They want to see how the product actually fits into someone’s life.

That is why creator commerce becomes more important, not less, in the AI era: as AI content gets cheaper, real creator signal gets more valuable. As brands flood the feed with AI-generated sameness, the brands that win will be the ones that use AI quietly in the background while putting real people, real communities, and real performance signals at the center of the growth system.

The best AI marketing strategy is not to make the brand look artificially creative.

It is to make the brand’s human team smarter, faster, and more accountable to revenue.

Ready for take-off? Let's do it.

At Stellar Action, we specialize in creator commerce and performance marketing in the modern era for lifestyle and active sport brands. We focus on turning creators into scalable sales channels by combining influencer partnerships, affiliate infrastructure, and conversion-focused content. We bridge the gap between culture and commerce, helping brands turn creator content into measurable growth. Our key offer is our Creator Commerce Engine, which powers brand revenue growth through affiliate creator flywheels, social commerce infrastructure, and killer action sport content.

Let’s make something that absolutely rips (your sales goals to shreds!)

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