How to scale your campaigns with AI, without the slop.

We like AI. It can make creative development faster, open up ideas that would previously have taken days to explore and make more variations possible. It can reduce costs and help businesses do more with the budgets they already have.

Because using AI well and using AI to make more content are two very different things. Yes, AI makes it easier than ever to produce something that looks finished. But that doesn’t mean it deserves to be published.

The problem isn’t AI. It’s when efficiency becomes the objective

There’s a temptation with any new technology to focus on the output. How much AI-generated creative can we make? How quickly can we make it? How cheaply can we make it?

Useful questions, but they aren’t the questions that make creative work effective. It would be far better to start with, “What are we making, and why?”

AI slop is what happens when the ability to produce content becomes more important than having something genuine worth saying. It’s the generic social post, the interchangeable image, the copy that sounds polished but could belong to any company.

It’s content that exists because the tool made it easy to create, rather than because the audience needed to see it.

And AI is very good at scaling that kind of work. You can now make ten mediocre ideas almost as easily as one decent one. But that doesn’t make the mediocre ideas more valuable, it just makes them cheaper.

Consumers aren’t rejecting AI. They’re questioning how it’s used

There’s a growing body of research showing that public attitudes towards AI are more nuanced than the headlines suggest.

Kantar’s latest research found that more than half of consumers now feel positive about generative AI, but that confidence falls when it comes to AI-generated advertising. Ads where GenAI was used more seamlessly performed better for branded cut-through, while distracting or unnatural uses performed worse.

That distinction matters.

People don’t necessarily care if AI helped create something behind the scenes. They’re much less comfortable when the technology becomes obvious in the finished work, particularly when the result feels artificial, unconvincing or misleading.

That’s where the quality of the creative matters. If people notice the AI before they notice the idea, story or brand, the technology can become a distraction rather than an advantage.

For AI-generated advertising, Coca-Cola’s 2025 Christmas campaign is a useful example. The campaign was produced in 30 days using generative AI, with five AI specialists working through more than 70,000 generated clips. But much of the discussion around it focused on the output itself, including criticism of visual inconsistencies and an artificial feel.

That’s an awkward place for a brand to end up. Instead of talking about the campaign, people are focusing on how it was made.

Good branding still takes care

This is where the argument becomes particularly important for us. A good brand isn’t just a logo and a colour palette, but the result of hundreds of decisions about how something should look, sound and feel.

It’s the typeface that feels right. The photography style, the tone of voice, the amount of space on a page, the way a campaign moves and the level of detail. Even the things you deliberately leave out.

Those decisions take strategy, experience and, let’s face it, human judgement.

AI can help you explore within that world, but it doesn’t automatically understand the world. Give an AI model a brand and ask it to create something ‘on brand’, and you’ll probably get a reasonable approximation.

The point isn’t ‘don’t use AI’. It’s ‘use it without losing control of the creative’. It still needs clear rules, references and creative direction.

AI is genuinely useful for the parts that slow us down

There’s a lot of creative work that simply doesn’t need to be done the hard way anymore. When it comes to creative brand campaigns, AI can remove repetitive production work and make it easier to explore possibilities.

We can explore visual routes quickly, generate options, create adaptations and resize and repurpose work. We can produce multiple versions for different audiences, test ideas earlier and speed up repetitive production tasks. We can then analyse creative performance and use those learnings to improve what comes next.

There’s a real commercial benefit to that efficiency.

If a piece of technology allows us to do something in an hour that used to take a day, why wouldn’t we use it? If it means we can test four routes instead of one, that’s valuable. If it makes smaller or more frequent campaigns financially viable, that creates opportunities that didn’t exist before.

There’s no virtue in spending more time or money on something simply because that’s how it was done in the past. The point is to use the efficiency intelligently.

If AI saves five hours of production time, the response shouldn’t automatically be to create five more pieces of content. It might be to spend those five hours making the idea even sharper and stronger.

Judgement is the bit we don’t want to automate

Use AI to remove friction, not judgement. Use it to explore further, produce faster, make more iterations and reduce the cost of the repetitive parts of the process.

But keep people involved in the decisions that actually matter. That’s the middle ground we think brands should be looking for.

What should the brand say? What should it feel like? Which idea is worth pursuing? Which version is distinctive? Does it actually sound like us? Is it useful to the audience? Is it building the brand, or simply filling another content slot?

Those are creative decisions that still need people who understand the business, the audience and the brand well enough to make them. And they need people prepared to look at something generated in ten seconds and say, “That isn’t good enough.”

The opportunity is better creative, not more

It’s tempting to make the debate binary. Either you embrace AI and automate everything, or you reject it and protect the traditional creative process.

We don’t think either position makes much sense. The opportunity is to combine the best of both. Use technology to make creative more accessible, more responsive and more efficient. Then protect the parts that give it meaning, including strategy, ideas, craft, originality and care.

That’s a much more useful role for AI in marketing. Technology helping good creative people do more, learn faster and spend more of their time on the things that actually make the work good.

The goal of scaling a campaign shouldn’t be to make more content, but to make better work.