We asked AI to write our marketing. Here’s what happened.

AI in marketing is a hot topic at the moment. It’s writing blogs, generating social media content, building email sequences and helping businesses churn out more content than ever before. If LinkedIn is to be believed, we’ve all got an AI assistant quietly doing half our jobs while we sit back and watch the leads roll in.

The reality is slightly different. AI is undoubtedly changing marketing. We use it ourselves. It saves time, speeds up research, helps generate ideas and makes plenty of day-to-day tasks easier.

But there’s a question that tends to get skipped in the rush to adopt it: if AI can produce the content, who’s deciding what the content should say? Because that’s the part that matters most, and it’s the part AI can’t answer for you.

What we found when we put it to work

We’ve tested AI across different areas of our marketing to understand where it adds value and where it quietly makes things worse.

AI is fast, and it’s fluent. Ask it to produce a first draft, summarise a brief, or generate five subject line options, and it will do all those things in seconds. For the tasks where the shape of the output is already clear, where you know what you want and you just need something to work from, it’s genuinely helpful.

Marketing campaign automation built around AI, for example, can take repetitive execution off your plate and free up time for the thinking that drives results.

Where it starts to fall short is the moment the brief gets harder. When the question isn’t ‘write me a blog about X’ but ‘what should we be saying right now, to which audience, and why’ – that’s where you feel the absence. AI will give you an answer, and it will sound reasonable, but it’s drawing on patterns rather than understanding. It doesn’t know your business, your customers, or the commercial context you’re operating in. It’s working from the outside in.

The strategy gap AI can’t close

Most businesses aren’t struggling because they can’t produce enough content. They’re struggling because they’re not sure what’s working, what isn’t, and where they should be focusing time. More output doesn’t solve that problem. It can make it harder to see because the activity level goes up while the clarity stays the same.

AI in marketing works best when it’s given something real to work with – a clear brief, a defined audience, a message that’s already been thought through by someone who understands the business. When those things are in place, AI can execute quickly. When they’re not, it fills the gap with something plausible – and plausible isn’t always right.

Where the human part still matters

There are things that no amount of AI capability can change. Understanding a customer’s needs – not just what they say they need, but what’s underneath it. Knowing when the market has shifted, and your messaging needs to shift with it. Deciding where the biggest commercial opportunity sits and what it’s worth committing to. Reading a room, challenging an assumption, making a judgement call when the data points in two directions at once – these aren’t soft skills that will eventually get automated away.

They’re the core of what makes marketing work commercially, and they require someone with genuine knowledge of the business, the audience, and the context.

AI is a tool in the service of that thinking, but it’s not a replacement for it.

The businesses that will get the most out of AI are the ones that use it to go faster on the execution while investing more in the thinking that guides it. The ones that use it to replace the thinking altogether will produce more content. Whether that content does anything is a different question.

So, how should you use AI in marketing?

Practically, use it for the tasks where speed and volume matter, and the direction is already set.

Research, drafting, repurposing, testing variations, marketing campaign automation – these are areas where AI earns its place, and the time savings are real.

Be more cautious with the parts that shape what you say and who you say it to. Your positioning, your messaging, your understanding of what your customers care about – these need human attention, not because AI can’t produce something, but because something isn’t always good enough. The output of AI is only as strong as the thinking you put in front of it.

Used well, knowing how to use AI in marketing means your team spends less time on execution and more time on the decisions that move things forward. But it starts with being clear about what you’re trying to achieve, and that part is still yours to do.

If you’re not sure whether your marketing strategy is making the most of AI or if you need that human touch, we’d like to talk.

Start the Koobr conversation.