Shiny things and snake oil: A guide to smart AI adoption in marketing

Ah, artificial intelligence in marketing – an arena where the bright-eyed and bushy-tailed are increasingly wandering into with dreams of effortless conquest, only to stumble into a veritable minefield of their own making. So, let’s save you the heartache, dear reader, and like me writing this article listening to TLC, ensure you have ‘No Scrubs’ on the way to AI glory.

Trap #1: Worshipping at the Altar of Shiny Things

The first misstep – oh, so painfully common – is the blind infatuation with the latest AI tools, especially from the big boy Marketing Clouds. Marketers are magpies by nature, drawn to the glitter of novelty. But let me tell you, half of these tools are little more than snake oil wrapped in a veneer of jargon. Before you pour your budget into the next “cutting-edge” platform, ask yourself: does it solve a real business problem, or is it just a glorified bells-and-whistles machine? Use cases are paramount.

Trap #2: Data Delusion

Here’s a bitter pill we know from hard experience working in this world: your data is probably rubbish. Yes, I said it. AI thrives on at least some quality data, and most organisations are swimming in an ocean of fragmented, inaccurate, and utterly useless information. Don’t expect miracles from a machine learning model if your data looks like it’s been compiled by a committee of drunken interns. However, don’t let it totally paralyse you either – you use data for reporting and analysis now so it’ can’t all be tosh. Therefore, identify what you need for your most valuable use cases, and build from there.

Trap #3: Setting It and Forgetting It

AI isn’t a magic wand. It’s not some enchanted servant that will tirelessly optimise your campaigns while you sip martinis on a yacht. The reality? AI needs nurturing, supervision, and regular refinement. If you think you can set it up once and let it run indefinitely, you’ll find yourself running an expensive experiment in futility faster than you can say "customer churn." Be prepared to test and learn, and slowly include it into your existing processes.

Trap #4: Misunderstanding the Human Element

Ah, the irony! In our rush to automate everything, we forget that marketing is still, at its heart, a deeply human endeavour. AI can crunch numbers and predict trends, yes, but it cannot feel. It cannot empathise. The moment you neglect the emotional resonance of your brand in favour of cold, clinical automation, you’ve lost the plot entirely. People buy stories, not algorithms, and even internal change processes need to be delivered in a human way.

Trap #5: Chasing ROI Unicorns

Let’s be frank: AI isn’t cheap. And yet, too many brands dive in expecting an immediate return on investment. It’s a long game, my friend, not a quick fix. AI requires patience, iteration, and a willingness to experiment – and yes, fail – before you see measurable success. As a provider of an AI product, don’t expect us to be able to tell you the ROI with certainty – it’s just too new. Therefore, if you’re not prepared to play the long game, don’t play at all.

Jerry Springer’s Final Thoughts

AI in marketing has obvious immense potential – it’s why we’ve built our own platform called Pythia, and why the big guys like WPP and Publicis are spending hundreds of millions of dollars trying to figure out how to make it work. But, it’s not for the faint-hearted or the ill-prepared. Avoid these traps, and you might just make something of it. Fall into them, and you’ll find yourself poorer, none the wiser, and with a marketing department muttering your name under their breath, and gently humming ‘Don’t Go Chasing Waterfalls’…