When information doesn't equal impact
Why the real value of strategy lies in decision-making, not data collection.
As AI continues to reshape the marketing landscape, businesses are under increasing pressure to move faster, work smarter and prove greater value from every campaign. But while AI can process information at scale, strategy is about far more than collecting data – it’s about making the right decisions from it.
Charlie McKenber, our Senior Campaign Strategist, explores where AI can genuinely add value to strategy work, where its limitations still exist, and why human judgement remains the defining factor in creating impactful marketing strategies.
Strategy work is a directive art. Our job is to take the best, most useful snippets of data from everything we consume and provide a single-minded path of travel.
“We’re not going to do X or Y, we’re going to do Z – and here’s why.”
So, naturally, AI presents an incredible opportunity, especially around research and synthetic testing. But that doesn’t mean we should take shortcuts with the important bits. Because when you’re looking to generate as much value as possible from a heavily scrutinised budget, setting off in the right direction is more important than ever. And trusting AI to make that call would be foolhardy to say the least.
So, where’s the opportunity, and where are the traps?
AI is a great gatherer, not a gap-spotter
We all know AI is brilliant at sequencing information. It can root through lengthy research reports and data sets far more quickly than any human possibly can.
For a lot of desktop research, AI is now the obvious first move. We use it, and anyone who says they don’t is probably lying, or behind.
But here’s what that process produces: information. A lot of it.
Which makes it near impossible for the LLM to know what to prioritise. The fuller the context window gets, the worse the problem, as it starts to focus on what’s recent more than what’s important.
Instead, the best results come from finding a thread, and helping a curious mind run with it to find the truly game-changing insight.
AI is great at quant, but bad at qual
If you’re looking for patterns in a mass numerical data set: give it to an LLM, hands down.
But if you’re looking for the kind of nuanced insights that come from human buying behaviours: you need a person.
Someone who can talk to customers and stakeholders, interrogate the brief, and separate what people actually want from what they’ve asked for.
For a Marketing Director managing a global product launch across multiple markets that isn’t just a nice-to-have. You’re unlikely to use the same messaging for lapsed customers in Frankfurt as for cold leads in Singapore, for example.
The necessary context doesn’t exist in a database or show up in a competitor analysis. It lives in the gap between what a company says about itself and what its customers experience – and you only find that by asking the right questions.
If you're looking for the kind of nuanced insights that come from human buying behaviours: you need a person.
AI is too eager to please, and a bad editor
Because these models are such sycophants, they jump to conclusions half-baked, without really interrogating them or building an answer from evidence.
AI wants to give you something strategy-shaped, so it races to a polished, seemingly convincing answer that looks shiny but doesn’t change anything. Often based on flimsy assumptions and driven by the law of averages away from the interesting fringes.
Whereas real strategy is subtractive, not additive.
The job is to cut – brief, market, audience truths, competitor gaps, category trends – until what’s left is the thing that will gain traction.
AI doesn’t cut well. It adds and hedges. It changes its ‘mind’ with every pass. It gives you the world on a plate, not a carefully curated tasting menu.
Ultimately, it comes down to value added
Good strategists have always been like magpies – gathering what’s useful and pulling out the most powerful ideas.
Clearly, AI has a role to play in many of those steps: gathering research, distilling findings, playing off theses and chasing the thread of genuine insight.
But don’t mistake information for impact. The value of strategy isn’t in the volume of what you know, it’s in the precision of what you do with it.
And that’s what delivers real business value.
The strategist’s job was never to be the smartest person in the room. It was always to find the one thing that everyone else was too close to see and make it impossible to ignore.
That part hasn’t changed.