The AI Sequencing Problem: Why Brands Are Automating the Wrong Things

AI has spent the past two years promising to transform marketing. There has been no shortage of predictions about what it will mean for agencies, creative teams and brands, from automated content production and hyper-personalisation to increasingly sophisticated media optimisation. But as AI becomes embedded in the everyday workings of business, a more interesting question is beginning to emerge: what happens when everyone has it?

In Australia, the proportion of businesses using AI rose from just 1% in 2021–22 to 12% in 2024–25. That is still a minority, but the direction of travel is clear. AI is moving quickly from something that might give a business an advantage to something businesses will increasingly be expected to have. For marketers, that changes the nature of the advantage. Access to the technology will not be enough. Nor will the ability to produce more content, more quickly, or generate endless variations of an idea. As the tools become cheaper and more widely available, the real difference will come from knowing where AI creates value, and where it is simply helping people do the wrong thing faster.

The problem with automating marketing too early

Our first instinct with any new technology is usually to apply it to the most time-consuming parts of the process. In marketing, that means content production, adaptation, personalisation and optimisation. The appeal is obvious. If something takes a team three days and a machine can do it in three minutes, why wouldn't you?

The problem is that speed only creates value when the thing being accelerated is valuable in the first place. A brand can now generate hundreds of headlines before it has settled on a compelling proposition. It can personalise communications before it has properly understood its audience. It can optimise a campaign at extraordinary speed while the underlying strategy remains completely undifferentiated.

AI can accelerate almost any process. That does not mean every process deserves accelerating.

Marketing has always had a tendency to confuse activity with progress. More content can look like greater productivity. More campaign variants can look like greater sophistication. More data can look like better decision-making. Generative AI has the potential to amplify all three without necessarily improving the thinking behind them.

AI in marketing is changing the value of human judgement

This is where the conversation needs to move on. The opportunity is not simply to use AI to do more of what marketing teams already do. It is to use it to change the balance between execution and thinking.

For agencies and marketing teams, AI can take some of the weight out of production. Done well, that should create more room for the parts of the job that have always required judgement: understanding people, finding the right problem to solve, challenging the brief, developing a genuinely distinctive idea and making choices when the answer is not obvious.

As production becomes cheaper, judgement becomes more valuable.

That shift matters because the technology itself is rapidly becoming less of a differentiator. If everyone has access to broadly the same underlying models, the model is no longer the moat. The advantage sits elsewhere: in the quality of the questions being asked, the data and experience informing the answers, the cultural understanding behind the work and, ultimately, the judgement to know which answer is worth pursuing.

For marketers, this is one of the most important implications of widespread AI adoption. Competitive advantage will increasingly come not from having access to AI, but from having something distinctive to bring to it.

AI strategy matters more than the number of tools

The same is true of strategy. AI makes ambiguity cheaper to execute, but it does not make ambiguity less dangerous. In fact, it can make the consequences of a fuzzy strategy much bigger. A weak idea can now be turned into hundreds of assets before anyone stops to ask whether the idea was worth pursuing.

The ability to make something quickly is not the same as knowing whether it should be made at all.

This creates a different challenge for marketers. The question is no longer simply what can be automated, but what should be automated. What work genuinely benefits from speed and scale, and what work benefits from more human attention? Where can AI remove friction, and where might it remove something valuable from the process?

These are organisational questions as much as technological ones. The businesses that get the most from AI are unlikely to be those with the longest list of tools. They will be the ones that have worked out how to combine technology with people, data and decision-making in a way that makes the organisation better.

That might mean changing how teams are structured, how briefs are written, how ideas are evaluated or how quickly a business can move from insight to execution. AI strategy, in other words, is not really a technology strategy. It is a question of how an organisation wants to think and work.

When everyone can create, creativity becomes more valuable

There is also a useful creative tension here. If AI makes it easier for everyone to produce competent work, competent work becomes less distinctive. When every brand can create polished imagery, tailored copy and multiple executions at speed, the premium shifts towards the thinking behind the output.

The question becomes less about whether something can be made, and more about whether it should exist.

That has significant implications for agencies and creative teams. The value of creative strategy is not diminished when production becomes easier. It becomes more important. When execution is abundant, the scarce resource is the idea worth executing.

The brands that stand out will not necessarily be those producing the most content or using the most sophisticated AI tools. They will be those with something distinctive to say, a clear understanding of whom they are saying it to and the discipline to resist producing work simply because they can.

The next competitive advantage in AI-powered marketing

That is not an argument against AI. Quite the opposite. It is an argument for taking the technology seriously enough to use it well.

The best teams will not use AI simply to remove people from the process. They will use it to remove unnecessary work from people's jobs, creating more time for the things machines are still poor at and people are still very good at: curiosity, judgement, empathy, taste, imagination and knowing when the obvious answer is not the right one.

AI is likely to become part of the basic infrastructure of marketing. As adoption grows, access to the technology itself will become less meaningful as a source of competitive advantage. The difference will come from what organisations build on top of it: their strategy, their culture, their data, their creative capability and their ability to make good decisions.

So perhaps the next phase of the AI conversation is not about who has the technology. It is about who has worked out what to do with it, and in what order.

Because when everyone has access to the same intelligence, the advantage will belong to the businesses that know where to apply it, where to question it, and when to leave it alone.