What Happened with Colgate’s Viral ‘AI Slop’ Post?
Colgate recently promoted a tropical toothpaste flavour on Instagram using a polished-looking social graphic: floating coconut and watermelon slices against a bright blue sky with product packs front and centre. At a glance, the ad felt like any other safe, conventional promo. But designers and fans quickly zoomed in on the packaging and spotted the telltale signs of AI generation. The text on the toothpaste tubes was warped, with some areas just slightly garbled and others reduced to illegible nonsense characters. Once people noticed, they couldn’t unsee it. Comments flooded in calling the post “hot AI garbage” and accusing the brand of posting unedited “AI slop” while sidelining real graphic designers. Instead of reinforcing innovation, the AI marketing image became a meme about brand design mistakes and a case study in how not to ship unfinished AI visuals.
How to Spot ‘AI Slop’—And Why Audiences Notice Immediately
The Colgate AI slop incident burned because the errors were obvious once you looked closely. Warped typography on the packaging, illegible label text and inconsistent detailing are classic AI art tells. Other common giveaways include extra or deformed fingers, uncanny reflections, impossible shadows, and nonsense text sprinkled across labels or signage. These artifacts signal that an image is synthetic and unpolished—especially damaging when they appear on packaging or products people know well. In marketing, such glitches break the illusion of reality, undercutting trust in both the message and the brand’s attention to quality. Consumers may not know how diffusion models work, but they intuitively recognise when something feels off. When brands publish AI marketing images without thorough review, they communicate that speed and cost-cutting matter more than craft, accuracy and respect for the audience’s intelligence.
The Cost–Quality Tradeoff: Why Cutting Creatives Backfires
AI image tools tempt teams with quick, low-cost visuals. A few prompts and you have a glossy hero shot, without booking a photographer or illustrator. But the Colgate AI slop backlash shows how this shortcut can cheapen brand perception. What looks like efficiency internally can read as laziness or disrespect for creative professionals externally. Once viewers catch obvious artifacts, they question what else the brand is willing to cut corners on. In sectors like oral care, where trust and hygiene are central, that perception is especially risky. When AI marketing images replace human-made assets purely to save time or budget, brands gamble with long-term equity for short-term gains. The real opportunity is not to swap out designers, but to give them another tool—using AI for exploration, not as a wholesale substitute for thoughtful brand design.
A Practical Review Workflow to Avoid AI Art Backfires
To avoid another Colgate-style AI art backlash, teams need a simple but disciplined workflow. Start with deliberate prompting: define product names, angles, lighting and brand colours clearly. Generate multiple variations and shortlist only those that match the brand’s visual language. Next, perform a detail audit at 100–200% zoom: text, hands, labels, reflections, edges and backgrounds. Look for warped characters, duplicated elements, off-kilter perspective and inconsistent lighting. Any promising image should go through manual touch-ups in design software—especially for typography and packaging details. Crucially, involve at least one human designer with authority to approve or kill the asset before it goes live. Treat this sign-off like you would legal approval. Finally, test the image on a small internal audience: if non-designers immediately spot something odd, iterate again. This workflow keeps AI as a helper while preserving craft and accountability.
When to Use AI Art—and the Ethics Brands Can’t Ignore
AI visuals can be powerful when used in the right context. They shine in internal use cases: moodboards, early concepting, rapid storyboards or testing a range of art directions before commissioning real shoots or illustrations. For final, consumer-facing assets—especially product shots, packaging and campaign key visuals—brands should usually invest in bespoke photography or illustration to avoid AI slop and maintain visual integrity. Beyond quality, there are ethical and legal questions: AI systems are trained on massive datasets that may include copyrighted works without clear consent, raising potential infringement risks. Representation bias is another concern; left unchecked, models can default to narrow stereotypes in depicting people and lifestyles. When brands lean heavily on AI image tools, they must develop guidelines covering AI image ethics, disclosure, usage rights and diversity standards. Otherwise, they risk not only ridicule, but reputational and legal exposure.