Marketing leaders are pouring money into AI. Whether they are ready to use it is a different question entirely.

Gartner released its 2026 CMO Spend Survey today at the Gartner Marketing Symposium in London, and the headline finding is a paradox that will feel familiar to anyone who has watched enterprise technology adoption up close. CMOs are allocating an average of 15.3% of their total marketing budgets to AI initiatives. Seventy percent say becoming an AI leader is a critical goal for 2026. And yet only 30% report having mature or fully developed AI capabilities.

That gap — between ambition and readiness — is the central challenge for marketing organisations this year, and it has real consequences for the returns they are getting on those investments.

The Numbers Behind the Gap

Gartner surveyed 401 CMOs and senior marketing leaders across North America, the UK, and Europe between January and March 2026. The vast majority led organisations with annual revenues above $1 billion.

A few figures stand out:

• CMOs allocate 15.3% of marketing budgets to AI on average. Among organisations that have actually built mature AI capabilities, that figure rises to 21.3% — suggesting the more confident you are, the more you invest, and the more you invest, the more confident you become.
• 70% of CMOs say becoming an AI leader is a critical goal for 2026. The same 70% acknowledge their internal processes are not yet mature enough to implement and scale AI effectively.
• 80% of CMOs say staff fear and anxiety is a barrier to AI experimentation. That is not a technology problem. That is a culture and capability problem.
• 56% say they lack the budget needed to deliver their 2026 strategy. 54% report insufficient resources.
• Overall marketing budgets remain effectively flat at 7.8% of company revenue, up only marginally from 7.7% in 2025.

The automation picture adds more urgency. Gartner separately found that marketing leaders expect AI-driven automation of marketing work to more than double — from 16% today to 36% by 2028. If that trajectory holds, organisations that are not building capability now are heading for a significant competitive gap within two years.

The AI Competency Trap

Gartner described a pattern they call the “AI competency trap,” and it is worth understanding because it explains why so many organisations are stuck.

The trap goes like this: a marketing team gets early wins with AI — productivity gains, faster content production, better campaign targeting. Success breeds confidence. They scale those same use cases. But returns start to diminish. The tools that unlocked value at a small scale stop delivering at larger scale. The team is now too committed to those approaches to step back and reimagine the operating model.

Gartner outlines three stages of AI maturity for marketing:

AI Curious — Teams are piloting tools, focused on individual productivity and efficiency gains. Most of the spending is happening here.

AI Competent — Teams are scaling multiple use cases, but they start hitting the limits of simple productivity framing. Costs grow, conformity sets in, and returns flatten.

AI Confident — CMOs are integrating human judgment with AI to reshape how decisions get made, how the brand connects with customers, and how the marketing function actually operates. Only a minority of organisations are here.

The survey suggests most CMOs are stuck between Curious and Competent — spending on AI without the organisational readiness to move into the Confident tier.

What This Means for Business Leaders

If you lead a marketing team, a business unit, or an organisation going through this, the survey findings point to a few uncomfortable conclusions.

Spending does not equal capability. Buying more tools does not close the readiness gap. The 70% who want to be AI leaders but lack the process maturity to get there are not being held back by a lack of budget. They are being held back by a lack of foundations — data quality, process design, and team capability.

Fear is a real blocker. When 80% of CMOs identify staff anxiety as a barrier to AI experimentation, that is a signal about how AI is being introduced, not just adopted. People resist what they do not understand. Organisations that invest in building genuine AI literacy across their teams — not just buying tools and hoping adoption follows — are the ones building toward that AI Confident tier.

The automation gap is coming. Marketing automation at 36% of work by 2028 is not a hypothetical. It is a forecast from organisations that are actively deploying these capabilities. If you are sitting at 16% today and not actively building toward that future state, you are not behind yet — but you will be.

The data foundation matters more than the AI. The CMOs allocating 21.3% of budgets to AI — the ones who actually have the maturity to use it — did not get there by buying AI tools first. They built the data and process foundations that make AI useful. The tools are only as good as what feeds them.

The EDNA Take

At Enterprise DNA, we have watched this pattern play out across hundreds of organisations. The businesses that get the most from AI are not always the ones that spend the most on it. They are the ones that invested earlier in data literacy, process thinking, and the kind of analytical culture that knows how to ask the right questions and interpret the answers.

The Gartner survey confirms what we have seen repeatedly: readiness is the constraint, not access to technology.

If your team is in that AI Curious phase — experimenting with tools but not yet seeing the returns you expected — the path forward is not more tools. It is building the capability to use the tools you already have at a level that actually changes outcomes.

That means data fluency across the team, not just for the analysts. It means understanding what questions AI can and cannot reliably answer. And it means building the operational infrastructure — clean data, documented processes, clear ownership — that lets AI systems actually deliver.

For organisations looking to move beyond Curious and Competent into genuinely Confident AI use, that foundation-building work is where the return actually lives.

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Enterprise DNA helps business teams build the data literacy and AI fluency needed to move from AI experimentation to AI advantage. Explore our learning platform or book a conversation with our team about where your organisation sits on this curve.