AI is not new to marketing. Anyone running lookalike audiences, relying on automated bidding or optimizing product feeds a decade ago was already using it. The algorithms were doing the work long before we started calling it AI.

What has changed isn’t the technology. It’s the visibility. AI has moved from invisible infrastructure to boardroom agenda. Every leadership conversation seems to arrive at the same question: If AI is doing this much, what is it actually doing for the business?

It’s a fair question. And, if we’re honest, one the industry is still figuring out.

The truth is, we’re all building this in real time.

There is no universal playbook. There isn’t a business close enough to yours that you can simply copy and expect the same outcome. Every organization is experimenting with different technologies, operating models and ways of working. Some are further ahead than others, but nobody has finished the journey.

That’s an honest description of where the industry sits today, not a weakness. The worst response to this moment is to wait for certainty before you move, because there is no certainty coming. The advantage will go to whoever is willing to get it wrong quickly enough to get it right.

We’re measuring the wrong thing.

Much of the conversation today is focused on AI adoption. How many tools have we deployed? How many employees are using them? How much content can we now produce?

Those are interesting metrics, but they don’t tell us whether AI is changing the business. The metric worth tracking is AI maturity. Adoption tells me you’ve started. Maturity tells me AI has become part of how your organization actually makes decisions. The simplest question I now ask leadership teams is this: Can you point to one important business decision that was made differently because of AI? Not faster. Not cheaper. Differently.

Did it change how you measure marketing effectiveness? Did it identify a customer opportunity you would otherwise have missed? Did it stop you producing creative that data suggested wouldn’t perform? Did it alter the way your teams prioritised work or measured success?

If the answer is no, AI is probably improving efficiency around the edges rather than changing how the organization operates. That’s valuable, but it isn’t transformation. Transformation begins when AI starts influencing judgment, not simply productivity.

Speed is the obsession. Foundations are the answer.

Almost every executive conversation I’m part of today revolves around pace. How quickly can we deploy AI? How fast can we automate? How rapidly can we scale? Speed matters, but not more than the thing that makes speed sustainable.

The organizations that will look back on this period as a competitive turning point are the ones doing the less glamorous work today. They’re connecting their data, agreeing on measurement frameworks that finance trusts as much as marketing, redesigning workflows and building governance that makes it clear where AI informs decisions and where humans remain accountable.

I keep coming back to one simple principle. Drop AI onto a weak foundation and it scales the inefficiency you already had. Build the foundation properly and the same technology compounds. That difference shows up in business performance, not in a product demonstration or a conference keynote.

The real test is whether AI changes decisions.

Most organizations are still running AI in pockets, with a content tool in one team, a bidding model in another, and a chatbot somewhere else. Individually, these tools improve productivity. Collectively, they often leave the core business untouched. The more revealing question is whether AI lives inside a connected decision-making system or sits in a growing collection of disconnected experiments. Then look underneath it, because this is where most maturity assessments should begin.

AI is only as good as the data feeding it. If customer, campaign and commercial data remain fragmented across platforms, agencies and internal systems, AI simply becomes better at producing confident answers from incomplete information.

Feed a bidding model nothing but click data and it will optimize relentlessly for the cheapest click instead of the most valuable customer. The dashboard will look healthy right up until commercial performance starts to decline.

That’s worse than having no answer at all, because people trust it.

Maturity is an organizational capability.

The companies creating meaningful outcomes from AI are not necessarily those who started first or spent the most. They’re the ones treating AI as organizational change rather than a technology rollout.

That means new skills, different team structures, modern measurement frameworks and a closer relationship between strategy, execution and commercial outcomes. It means recognizing that AI isn’t simply another marketing tool. It changes how organizations make decisions.

That work isn’t completed in a quarter. It happens one decision at a time, one connected use case at a time, one governance boundary at a time. Eventually, every organization will have access to similar AI technology. Competitive advantage will come from building an organization that learns faster and, therefore, makes better decisions, not simply from having AI.

The companies that win will be the ones that got it wrong quickly enough to get it right, not the ones that never got it wrong at all.

About The Author Of This Article

Amy Crowther is President, Americas at Incubeta

About Incubeta

Incubeta is a global marketing agency empowering ambitious brands to outperform.