Written by Brett WiskarView bio ↓
AI isn’t just the topic on everyone’s lips. It’s widely available, poorly understood, creating confusion in every sector, and often being used in actual businesses tackling real problems.
While all that is true we also shouldn’t lose sight of the fact that it is without question, incredibly powerful and capable of changing every business. That said, before businesses get too far into this they need to pause and consider whether the perceived wins achieved through AI are actually making things better.
Many people see its power to create and increase speed as all upside but for those who know how the technology works, and with a broader perspective on the impact in a given sector, the AI opportunity comes bundled with certain risks.
Marketing under pressure
When it comes to marketing there are two levels of thinking;
Businesses with a poor understanding on the value of marketing and how to do it well, see the function as an overhead. This can be caused by the lack of immediate visibility between the actions of the marketing function and when the impact of those actions shows up on the P&L.
More mature businesses that understand marketing – this group knows marketing is how we tell the world what we do, why what we do matters, and how the inherent traits of our product or service deliver value.
In either case large language models like Claude and ChatGPT, enable reduction in the time and visible cost to produce a single piece of marketing collateral. In a world where budgets are tighter, marketing that is faster and more cost effective to execute seems like a no brainer.
But in business very few things that appear to be a no brainer actually are. If only life was that easy.
We’ve entered into an era of AI slop and we all see it on a daily basis. I personally am connected to two people I thought would know better. Each of them publish AI generated garbage (AI Slop) multiple times each week on LinkedIn. It’s clear they, and some of their target audience, can’t tell the difference between the following,
- glaringly obvious AI slop,
- less overt AI slop which in some cases appears borderline competent,
- well produced marketing material reflecting the knowledge and strengths of a business which is, at least partially, AI generated or supported, and
- human planned and written, strategically aligned marketing copy and images.
I kid you not – one of the two people I reference above posts multiple times most days through a subscription based automated platform he proudly showed me recently. Soon after that demonstration, the system published a post to LinkedIn which included an AI generated image of the individual with many physical characteristics of the person which included a signature item of clothing he frequently wears. However the person in the AI generated image was of a different race!!! It generated the image, drafted the headline and copy and automatically posted it to LinkedIn for him all without him being in the loop. He’s since taken that post down but continues with his AI slop based strategy.
No differentiation means no cut through
Contemporary AI tools are evolving rapidly. While most people don’t need to understand the technical detail, there is a consistent concept behind how they all work which helps inform the risks when using them. Large language models are trained on vast amounts of human-written content and learn patterns in how language is used. When you’re prompting them, these systems don’t ‘think’ or form opinions. They generate responses by predicting the most likely next word based on everything they were trained on and the context you have given and some matching between the two.
This isn’t random. It’s probabilistic prediction shaped by enormous amounts of data. The result is output that is highly coherent, often impressive, and usually “good enough.” But here’s the catch. By default, these systems gravitate toward the most common and widely used ways humans express ideas. They lean toward what is familiar, safe, and statistically likely to make sense to the broadest audience.
Which means if you use them naively, like so many businesses currently do, you won’t get bold thinking or sharp differentiation for your brand. You get the most typical version of an idea.
Not because the technology is limited, but because the path of least resistance leads to conventional output.
At scale, that creates a problem. If everyone is using the same tools in the same way, drawing from the same patterns, the result isn’t innovation, it’s convergence. Content starts to sound the same. Messaging becomes interchangeable. Brands lose their edge without realising it. And in marketing, sounding like everyone else is the fastest way to be ignored.
No brand strives to be average
Across industries, businesses are under increasing pressure to deliver faster and more cost-effective outcomes. AI is seen as a perfect tool to respond to this pressure which is why its adoption is accelerating so quickly. Whether it’s an accountant or an engineer using AI-assisted development tools or a marketer generating content, these systems make it incredibly easy to produce work that is fast, coherent, and “good enough.”
But “good enough” is where the risk sits.
Left to default use, AI systems tend to produce output that reflects the most familiar or widely accepted ways of expressing an idea. It sounds professional. It reads well. It feels complete. And that’s exactly the problem.
Without strong direction, context, and editorial judgment, what you get isn’t sharp or distinctive. It’s conventional, it’s safe, and it’s interchangeable with everything else in the market.
At the start of this piece I talked about two types of businesses:
- Those with a limited understanding of marketing and its value
- Those with a mature understanding of how marketing creates differentiation
The first group will use AI to increase output and reduce cost, and they see it as success. They’ll produce more content, faster, and assume they’ve become more effective.
The second group will do something very different. They’ll use AI for efficiency, but reinvest the gains into what actually creates advantage – strategy, positioning, brand thinking, and a clear point of view. They’ll apply taste, judgment, and constraint to shape the output into something that reflects who they are, not just what the model can produce. The difference isn’t the tool.
The Winners and Losers of AI driven marketing
In the short term, many businesses will feel like they’re winning. Output goes up. Costs go down. The marketing machine looks more efficient. But over time, the gap becomes clear.
Businesses relying on AI to produce content will blend into an increasingly crowded, increasingly similar landscape. Their messaging will feel familiar, their brand less distinct, and their ability to command attention will erode. That will make appearing premium and demanding premium spending very difficult.
The winners will look different. They won’t necessarily produce the most content. But what they produce will be recognisably theirs. They will market themselves with a clear point of view, a consistent voice, and strong positioning. In these businesses AI will remove friction, not replace thinking. Importantly, they’ll invest in the capability that matters more in an AI-enabled world. They’ll double down on judgment, taste, and strategic clarity. The ability to decide what should be said, not just generate something that can be said.
That’s where the advantage shifts.
Disruption leads to opportunity
The window we’re in now is a period where the cost of creating content is collapsing. That changes the game. When execution becomes easy, it stops being the differentiator. What rises in value instead is thinking. In marketing this means the clarity of the message, the strength of the perspective, and the discipline to say something meaningful rather than just something polished. We have to reassess our weighting of what matters and update our understanding of marketing accordingly.
For marketers and businesses who understand this, the opportunity is significant. AI can remove friction, accelerate production, and unlock capacity. But the advantage won’t come from using it more. It will come from thinking better. The brands that stand out over the next few years won’t be the ones producing the most content. They’ll be the ones who remain deliberate in what they say, how they say it, and why it matters to the people they’re marketing to.
How to use AI in marketing without damaging your brand
As AI becomes embedded in marketing workflows, the risk isn’t using it – it’s using it without intention. Here are the patterns to watch for, and what to do instead.
Why AI-generated marketing often starts to look the same
When teams rely on AI without clear direction or oversight, outputs tend to converge.
In practice, this shows up as:
- Content that feels generic, interchangeable, and forgettable
- Brand voice that becomes flattened or inconsistent
- Increasing reliance on AI over original thinking
This doesn’t happen because the technology is flawed, it happens because most people use it in the same way, with similar prompts, and minimal refinement. The result is different brands saying similar things in similar ways.
The hidden risk: how AI quietly erodes differentiation
The impact of this isn’t immediate, which is why it’s often missed.
In the short term:
- Output increases
- Costs decrease
- Teams feel more productive
But over time:
- Differentiation declines
- Messaging becomes less distinctive
- Brand recall and trust begin to weaken
It’s not a sudden failure – it’s a gradual loss of edge.
More content does not mean a stronger brand
As AI tools become more powerful and more accessible, the value of execution decreases.
What increases in value is:
- Clear thinking
- Strong positioning
- A defined point of view
This is where the “human premium” shows up.
The advantage shifts to those who bring:
- Judgment – knowing what to say and what not to say
- Taste – recognising what is distinctive versus generic
- Perspective – having something meaningful to contribute
How to use AI effectively in marketing
The strongest businesses don’t reject AI – they use it deliberately.
In practice, that means:
- Using AI for speed, scale, and support
- Not outsourcing core messaging or brand voice to the model
- Applying clear direction, constraints, and editorial oversight
Most importantly, they focus on:
- Strong brand thinking before execution
- A clear and consistent point of view
- Intentional use of AI as a tool, not a substitute for strategy
The brands that stand out won’t be the ones using AI the most. They’ll be the ones still thinking for themselves.
About the author
Brett Wiskar is one of Australia’s leading voices on the intersection of technology, leadership, and human performance. With more than 25 years’ experience in innovation, trend forecasting, and strategic transformation, he works with executive teams across government, education, food and agriculture, FMCG, security, and technology, helping organisations navigate disruption while building workplaces where people can perform sustainably.
