When “good enough” becomes a corporate brand risk

Scroll through social media for long enough and you’ll know AI slop when you see it. The suspiciously glossy lighting, the overenthusiastic colour grading, the strangely perfect people and those little details that look convincing until you stop and look properly.

The term has become so commonplace that Merriam-Webster named “slop” its 2025 Word of the Year, defining it as low-quality digital content produced, usually in quantity, using artificial intelligence.

For a while, it was easy to think of AI slop as largely a social-media phenomenon. But generative AI has quickly moved into mainstream corporate marketing, advertising and content production. That changes the conversation considerably.

THE HOT TAKE: The biggest problem with AI slop is not always that it looks bad. Sometimes the real danger is that it looks good enough that nobody notices it is wrong.

THE CORPORATE PROBLEM: AI can produce an asset in seconds. A brand can spend decades building the reputation attached to it.

THE OPPORTUNITY: AI can be an incredibly useful creative tool, but human judgement, brand knowledge and quality control remain essential.

The World Federation of Advertisers found in 2026 that 78% of global brands surveyed were already using AI-generated or AI-enhanced content in consumer-facing marketing. Among those brands, 87% were using it for product imagery, 80% for marketing copy and 77% for background visuals. At the same time, 82% believed transparency around AI was essential for protecting brand reputation and 79% said it was important for maintaining consumer trust.

AI is no longer sitting somewhere on the experimental fringes of the marketing department. It is firmly inside the corporate creative supply chain.

And that means the slop matters.

When AI becomes a brand credibility problem

There is a tendency to think of AI mistakes as the amusing stuff: six fingers, strange teeth, nonsensical text or objects melting into one another.

Those are almost the easy ones because somebody usually notices.

The more interesting risk comes from content that is almost right.

We encountered exactly this at Brandesign when an AI-generated visual was supplied for work relating to a major motoring brand. At first glance, the image looked convincing. On closer inspection, however, its representation of Cape Town contained obvious geographical inaccuracies, including two Lion’s Heads and an incorrectly orientated landscape.

We caught it before going into market, but it demonstrates the point perfectly.

Had nobody noticed, consumers would not have blamed the AI platform that generated the image. They would have associated the mistake with the brand whose name appeared alongside it.

That is the reputational challenge of AI-generated creative. The technology is becoming exceptionally good at producing something that looks plausible, while plausibility and accuracy are not the same thing.

A small mistake in an internal concept is relatively harmless. Put the same mistake into a national campaign for an established corporate brand and the stakes change dramatically.

The sea of creative sameness

Accuracy is only part of the problem. There is also the growing sameness of AI-generated creative.

In June 2026, WFA research into creative excellence found that 58% of respondents were concerned about creative homogeneity and a “sea of creative sameness” as AI adoption increases.

Perhaps more tellingly, only 11% of the organisations surveyed had an agreed vision or gameplan for using AI to drive creative excellence, while 57% said they were looking to their agencies to help work it out. 

This gets to the heart of AI slop.

Ask an image generator to “create a premium corporate campaign visual” and it will happily give you something polished. The difficulty is that thousands of other people are asking very similar questions of very similar tools.

Without strong creative direction, brand understanding and human refinement, perfectly acceptable can very quickly become perfectly forgettable.

AI is not the problem

This is where the conversation needs some balance.

There is increasingly good evidence that AI-generated advertising can actually work very well.

A 2026 Columbia Business School study analysed more than 16 billion ad impressions and 116 million clicks across thousands of advertisers. Researchers found that ads containing AI-generated imagery could outperform ads using human-generated imagery on click-through rate.

There was, however, an important catch.

The advantage existed only when the AI-generated imagery did not look AI-generated.

That might be the curious case of AI slop summed up in one finding.

The problem is not necessarily AI. The problem is obvious, generic or poorly considered AI.

Used intelligently, generative AI can help creative teams develop concepts, visualise ideas, generate variations, extend imagery, support production and dramatically accelerate certain parts of the creative process.

The distinction is between AI-generated and AI-directed work.

One involves pressing a button. The other still requires judgement.

A little less slop, a little more scrutiny

For corporate marketing teams, the conversation therefore needs to extend beyond prompting and into creative governance.

1. Treat AI output as a draft

One of AI’s greatest tricks is making unfinished work look finished.

A generated image can arrive beautifully lit, colour graded and apparently ready for use in seconds. That polish should not be mistaken for accuracy. Product details, people, locations, signage, typography, reflections and other contextual elements still need to be checked.

2. Put subject knowledge back into the process

Someone who understands the product, location, audience or industry should review the work.

AI does not know when something feels wrong in the way an experienced human does. Local knowledge, technical expertise and brand familiarity are precisely the things most likely to catch plausible mistakes.

3. Know where the content came from

Corporate creative rarely travels directly from one person to publication. Assets move between internal teams, agencies, production partners, suppliers and regional offices.

Knowing where AI was used, what was generated and what has already been verified makes proper quality control considerably easier.

This is becoming increasingly important as brands themselves acknowledge uncertainty around AI governance. WFA reported in 2024 that 80% of multinational brands were concerned about how creative and media agencies were using generative AI on their behalf, with potential reputational damage among the major concerns.

4. Ask whether it is creating a false impression

The underlying advertising rules have not disappeared because the technology has changed.

South Africa’s Advertising Regulatory Board guidance on AI makes the distinction particularly well. AI itself is not inherently misleading. The issue arises when it is used to create a misleading impression about the advertised product or service.

In other words, the technology may be new. The responsibility is not.

5. Don’t use AI simply because you can

Sometimes AI is the right tool. Sometimes photography, illustration, stock imagery or traditional production will produce a better result.

The idea should determine the tool, rather than the tool determining the idea.

That distinction alone can eliminate a surprising amount of slop.

And what about small businesses?

There is still another side to this conversation.

For smaller businesses with limited budgets and no dedicated creative team, generative AI can be enormously empowering. Adobe research found that 85% of the small-business owners it surveyed were already using generative AI, with social-media content the most common AI-assisted task.

For a start-up, home business or entrepreneur, these tools can provide access to marketing capabilities that might otherwise simply be unaffordable. There is genuine value in that, and it would be unfair to judge a small business using AI to create an Instagram post by exactly the same standard as a multinational producing a national advertising campaign.

Scale changes the expectation.

The greater the audience, investment and brand equity involved, the greater the responsibility to scrutinise what goes into market.

AI democratises execution. It does not democratise accountability.

The more powerful the tool, the more important the judgement

As AI gets better, creating something polished will continue to become easier.

That does not necessarily make designers, writers, strategists, photographers and creative directors less relevant. It arguably shifts where their value lies.

When almost anyone can generate a polished visual, the differentiator becomes knowing what should be created, whether it is accurate, whether it fits the brand and whether it is worth publishing at all.

AI can generate the work.

Human judgement still decides whether it deserves to carry the brand’s name.

Making AI work for your brand

At Brandesign, we see AI as part of the creative toolkit, not a replacement for creative thinking. Used well, it can accelerate ideas, production and execution. Used without the right direction and scrutiny, it can create problems just as quickly.

Our role is to bring the strategy, creative direction, brand understanding and human quality control around the technology, helping organisations benefit from AI without allowing convenience to compromise credibility.

If your organisation is exploring how AI fits into its marketing and creative workflow, talk to Brandesign. We can help make sure the end result feels like your brand, not just like AI.