Beware of bright shiny things.
There’s an understandable urgency among most marketers today. In large companies, where the average tenure of a Chief Marketing Officer keeps shrinking, it’s not enough to just keep pace — you have to win. In smaller companies, where the marketing hat may be just one of many worn by the owner/CEO, market share bought on the cheap is essential: grow or die.
Stop Looking for the Silver Bullet
It isn’t surprising to see marketers of every size and industry rushing to bolt AI onto everything they touch — the chatbot, the “AI-powered” ad campaign, the auto-generated blog post, the personalization engine nobody asked for. Not that innovation is a bad idea. Innovation is crucial to finding what actually works for your prospects and your brand. But the problem arises when the motive isn’t testing a new tool, but a desperate search for the silver bullet. Or, in most cases, a bullet made of cheaper ore. The problem arises when we fall in love with bright shiny things.
When we drive our marketing into AI purely to be an early adopter — or because people (some of whom have appointed themselves “AI experts” overnight) keep pushing in that direction — we’re chasing innovation for innovation’s sake. Do you suffer from “bright shiny thing syndrome”?
Ask yourself:
- Are you deploying an AI chatbot without knowing what problem it’s actually solving for the customer?
- Do you think an AI-generated ad is going to replace the judgment of your creative team?
- Would you like to hand your brand voice over to a tool trained on the average of everything on the internet?
- Are you spending more time talking about how you’re “using AI” than proving it moved a single metric that matters?
AI, like every wave before it, is not for everybody, in every application. Managed properly, it’s still labor intensive — someone has to prompt it, check it, and catch what it gets wrong. As has been true of every “revolution” in marketing before this one: it takes time, judgment, and a point of view. And it’s entirely possible your product or service is best marketed by a human who knows your customer, not a model that doesn’t.
But relax — there’s no rule that says you have to lead with AI to compete. You’ll do just fine if your marketing embraces the technology only where it actually earns its place.
Test and Learn
There is no AI train leaving the station without you on it. There are people who know a great deal about applying AI well — you may find them a real asset. But if someone tells you they’re an “AI marketing expert,” ask what they were an expert in eighteen months ago. The tools are new. The principle isn’t: connecting with people to earn their attention and their trust is the same job it’s always been.
So, with respect to the new tools, and understanding that companies want results now, may we humbly substitute “Test and Learn” for “Wait and See” — and for “Deploy and Hope”?
“Wait and See” is an open admission that you’re willing to let others do the learning for you. It’s a defeatist, risk-averse surrender. “Deploy and Hope” is worse — it’s moving fast without checking whether anyone wanted what you built. “Test and Learn” is trial and error: an openness to try, paired with a recognition that not everything will work, and a plan for finding out before your customer tells you the hard way.
Most importantly, “Test and Learn” is about metrics — and if there’s one thing The Miller Group believes in, it’s establishing performance metrics before you scale anything. It’s worth asking: are marketers measuring whether AI-assisted work actually improves sales, retention, margin, or trust? Or are they measuring “we shipped it faster”? Speed isn’t a marketing objective. It never was.
You Can’t Win ‘Em All, All the Time
Coca-Cola released a second consecutive AI-generated holiday ad after its first drew heavy criticism, and viewers again described it as soulless and lacking the emotional warmth of the brand’s earlier, human-made work. McDonald’s ran into the same wall in the Netherlands, where an AI-generated holiday advertisement was pulled after audiences called the imagery unnatural and emotionally hollow. Meta’s own automated ad platform started swapping out brands’ top-performing, human-approved creative for AI-generated alternatives without permission — and some of what went live included distorted, unusable visuals that never should have reached a real customer. And an AI companion startup’s subway advertising campaign in New York was vandalized and mocked by commuters, becoming a public symbol of resistance to AI overreach.
The pattern in every one of these isn’t that AI failed as a tool. It’s that a human decision-maker let the tool make a call it had no business making alone — replacing judgment instead of supporting it.
So, in the midst of all the pressure to do something, or when the boss walks in waving an article about the latest AI launch, take a deep breath and avoid the temptation to rush out and do something. Anything. Instead, remind yourself how the buying process for your product or service actually works today, and figure out where — if anywhere — AI can serve that process without replacing the parts only a human can do. Remind everyone around you that judgment still matters, and unless AI is making the work demonstrably better for the customer, don’t reach for it just because it’s there.
And avoid falling in love with bright shiny things. Maybe it’s better to just take some tarnish remover to the old tried and true.
This article is written from the personal perspective of Bill Williams. The opinions and views expressed are solely of the author and do not necessarily reflect those of The Miller Group Advertising.
