The numbers show how tight that squeeze is. CMOs now put 15.3% of their marketing budgets into AI, while total marketing budgets barely moved, from 7.7% to 7.8% of company revenue.¹ 

So, our team set out to look past the hype and dug into the research to find what’s working, what isn’t, and how to turn AI into real growth.

Why our spending is outpacing our readiness

The ambition is there… the foundations, not so much. 70% of CMOs say becoming an AI leader is a critical goal for 2026, yet only 30% say their organization has mature AI readiness capabilities.² 

So why the gap between ambition and readiness? In our view, five reasons stand out:

1. The fear of falling behind is moving faster than strategy. AI could reshape how we compete, and how we win and serve customers. None of us wants to be left behind. So we buy new platforms, experiment with agents and automate across departments, but we forget the most important question: which business problem are we trying to solve, and why is AI the right answer?

2. Buying technology is easy. Changing how we work is not. A software subscription can be approved in weeks. Redesigning workflows, connecting customer data, retraining people and aligning marketing with sales and finance can take months. So many of us drop AI into existing processes without rethinking them.

3. We reward what we can see, even when we can’t see the impact. AI makes it easy to create hundreds of creative variations, publish more content and launch campaigns faster. It feels like progress. But content volume, clicks and hours saved are not the same as revenue or profit. If all that extra output doesn’t help us win, we’re simply producing more noise, faster.

4. Disconnected data and silos hold AI back. AI is only as good as the information it works with. Yet customer data often lives in separate CRM, advertising, analytics, e-commerce and service systems. When those systems don’t talk to each other, AI produces incomplete insights and mixed recommendations.

5. We’re underinvesting in the people who turn AI into value. AI can speed up research and content, but it takes people to understand customers and spot the real opportunities. We give priority to technology, while training and change management get whatever budget is left. So teams use AI to do the same tasks a little faster, while the decisions that move the business stay the same.

Where the value gets lost

Here’s the thing: the problem sometimes is not the technology, but how we use it.

88% of organizations use AI regularly, but only 39% see any impact on EBIT.³  Even when companies invest, value often slips away. In marketing, it leaks out in four places:

• Time saved that goes nowhere. One large study found that AI cut the time people spent on email, but didn’t change how much or what kind of work they did.⁴  An hour saved only becomes value when someone decides what else to do with it.

• Pilots that never grow up. Many pilots prove that AI can do a task, then stop there. Without a leader who owns the business result, and a plan to roll it out beyond the first campaign, a promising test stays a test.

• Results we can’t prove. Just because a platform takes credit for a sale doesn’t mean the ad made it happen. A personalized campaign can look brilliant simply because it reached people who were already planning to buy. Without a control group, there’s no way to separate real growth from sales we would have made anyway.

• Costs nobody counted. The license is only the beginning. Integration, data work, human review, model usage and ongoing support all add up. If we only count the savings, the return looks better on paper than it does on the bottom line.

So the fix isn’t just how we work, or what we buy. AI creates value when technology, adoption and strategic alignment work together, and if one is weak, the return suffers. The priority isn’t more AI, but investments that solve real business problems and deliver measurable, incremental value.

What’s actually working

The teams getting real results have one thing in common: they treat AI as a growth multiplier, not a growth strategy. Here’s what they do differently.

• They redesign the whole climb, not just the gear. Leading teams have stopped asking “which tool should we buy?” and started asking how tools and people work together. When they get it right, the payoff is real: 20–30% cost efficiency gains, up to three times higher marketing ROI and campaigns that move ten times faster.²

• They keep humans on the big idea. AI does well with simple, product-focused ads. But when an ad needs emotion and storytelling, people still win. In one large test, human-made ads were 14% more effective in the short term and 17% stronger for the brand over time.⁵  AI ads are “good enough”… and that’s exactly the problem.

• They protect trust. Customers are noticing the flood. Nearly two in three say brands produce too much AI-generated content, and more than four in ten now lean on real people for shopping advice.

• They invest in what’s hard to copy. When everyone can produce content cheaply, the edge moves to what AI can’t fake: real expertise, customer stories, community, a better offer and a better experience.

The 2027 playbook: five moves from experiment to growth

Next year’s goal isn’t more AI, but more profitable growth, with AI used wherever it has proven its value. Here’s how we’d get there.

1. Find the constraint. Start with the business, not the technology. What’s holding back profitable growth: winning customers, converting them, keeping them or protecting margin? Pick the two or three problems that matter most. AI can help here too, by analyzing customer, product and marketing data to pinpoint the real issues.
2. Fix the foundation before you speed it up. AI speeds up whatever it touches, including what’s broken. Before adding a tool, simplify the workflow, connect the data and get marketing, sales and finance on the same plan. Set guardrails early: who approves what, which data can be used and when a human steps in.
3. Prove it small. Choose one high-volume workflow, measure where you’re starting from, and test against a control group. Judge it by revenue, margin or retention.
4. Double down on what works. Only expand what has proven its value. The best candidates are usually high-frequency work, where AI generates the options and people choose based on experience. Be especially careful with autonomous agents, since their running costs are forecast to rise more than fivefold through 2028.⁶  
5. Reinvest the gains, and let go of the rest. Put the time and money AI frees up back into growth: more testing, better products, better customer experiences and stronger skills for your team. And retire the tools and pilots that didn’t pay off. Saying no is part of the strategy, too.

If we were setting a 2027 marketing budget, we’d organize it around three priorities:

• Demand creation: distinctive positioning, human-led creative, expert content and customer advocacy.
• Conversion and retention: stronger offers, better digital experiences and lifecycle marketing.
• Growth infrastructure: AI-enabled workflows, first-party data, experimentation and financial measurement.

AI should power all three. It shouldn’t automatically get the biggest slice just because it’s the newest thing.

Getting ready for what comes next

The next wave is already arriving. AI is moving from assistants that help with tasks to agents that act on their own. More customers will research and buy through AI, so brands must be easy to find, understand and trust. And the technology will keep getting more powerful, and more available to everyone.

When everyone has the same tools, the advantage moves to how well we know our customers, how connected our data and teams are, and how honestly we measure what’s working. That’s why this playbook is more than a 2027 plan.

Companies that do this work now won’t start over with every new tool. They’ll be ready to put it to work on day one, because they’ll already know where it fits.

So the question we want to leave you with isn’t “What can we automate?” but:

What is holding back profitable growth, and where can AI, or simply better marketing, remove that constraint?

Because AI was never really the goal. The goal has always been to serve our customers and give them the best possible experience, every single time. So they keep choosing us.

Make Every Marketing Dollar Count. If you’re wondering whether your marketing investments, AI included, are truly driving growth, we can help.. Let’s assess where you stand, pinpoint the initiatives that will move your business forward, and build a marketing strategy where every tool earns its place.