Gartner's 2026 CMO Spend Survey just dropped a number that deserves a lot more attention than it's getting.
Seventy percent of CMOs say becoming an AI leader is a critical goal this year. Only 30% have the organizational maturity to actually do it.
That gap is not a technology problem. It is not a budget problem. CMOs are already spending an average of 15.3% of their marketing budgets on AI. The money is moving. The tools are being purchased.
The problem is everything underneath the tools. And almost nobody is talking about it.
Let's be honest about something. You were not going to see a lot of CMOs raise their hand and say they don't want to lead in AI. We wanted to lead in ABM. We wanted to lead in demand gen. We wanted to lead in the customer experience.
Declaring intent is not the same as building capability. And right now, most marketing organizations are confusing the two.
The Gartner report flags four building blocks for AI readiness: data foundations, process maturity, governance, and talent. Most marketing organizations are behind on all four. After working with marketing teams since 2007, we have never met a single organization that had its data truly handled. Not one. The best we have ever given anyone is a B.
If AI runs on data, bad data does not slow you down. It automates your failures at scale.
1. Data foundations nobody wants to fund
Data is not sexy. It is the plumbing. It is the grind. Nobody wants to talk about it in a board meeting. But if you want to lead in AI, you need to ask a simple question first: what data do we have, what could we find, and what would we do with it if we had it?
Start with the questions good data would answer. Then build backward. That flips the conversation from a tactical cost to a strategic investment, which is the only frame that gets budget approved.
2. Process maturity most teams have never mapped
Marketing leaders underestimate how many processes are running across their departments every day. Not the big ones like campaign briefs and lead scoring. The hundreds of smaller workflows that nobody has ever written down.
You cannot automate what you have not mapped. You cannot scale what you have not designed. Before buying another AI tool, spend two days with your team documenting how marketing actually works. You will find more than you expect.
3. Talent built for a world AI is dismantling
The execution layer of marketing is going away. AI is taking it. That means the talent model built around execution people needs to change, and it needs to change now.
Marketing ops needs to become a data function, not just a technology function. That requires data scientists, or at minimum, people who treat data quality as their primary responsibility. Most marketing ops teams are not built that way. Most companies are not investing to get them there.
4. Governance nobody has defined
Seventy percent of CMOs want to lead in AI. Seventy percent also acknowledge their internal processes are not mature enough to implement and scale it. You cannot govern what you have not defined. Governance is not a compliance exercise. It is the framework that determines how AI gets used, who owns it, and how you measure whether it is working.
The report covers data, process, governance, and talent. We would add two more.
Mindset. Most marketing organizations are still approaching AI the way they approached every previous technology wave: go get it, declare victory, move on. AI is not a campaign tool or a content shortcut. It is a fundamental reimagining of how the work of marketing gets done. Leaders who treat it like another martech purchase will get another martech result.
Identity. This one is harder to talk about but it matters more. When the execution layer disappears, who are you as a marketer? When AI handles the work that defined your role, what is your role?
Marketing organizations need to answer that question before they can build toward it. And most have not started.
We ran the Revenue Marketing Index last year. After 16 years of tracking this, only 16% of companies have reached the Revenue Marketing stage: repeatable, predictable, and scalable.
That number matters here. AI can automate and scale a repeatable process. It cannot create one for you. If you are in the 84% still operating in the earlier stages, buying AI tools is not going to close the gap. It is going to expose it faster.
You have to build the foundation before you can scale what sits on top of it.
The marketing organizations that are actually AI-ready are not spending more. They are spending smarter. The Gartner data shows they allocate 21.3% of their budgets to AI versus the 15.3% average, but more importantly, they are pairing that investment with data infrastructure, process discipline, and organizational change.
They asked the harder question first: how does marketing need to work differently in an AI world? Then they built toward it.
The human plus AI equation is not about replacement. It is about elevation. A few years ago, the world chess championships changed the format. Now it is grandmaster plus AI against grandmaster plus AI. Together, they produce strategies no human or machine could develop alone. That is the model. The human becomes more important, not less. But only if the human has built the right foundation to work with.
You cannot lead in AI if you are built on bad data, undefined processes, and a talent model designed for a world that no longer exists.
The CMOs who figure that out first are not going to look like the CMOs we know today. The title itself may be wrong. The role is moving toward something closer to Chief Growth Officer, with AI as the operating system underneath it.
That is not a threat. It is the opportunity. But you have to stop buying tools and start building foundations.
The 30% who are ready are already doing it. The other 70% are running out of time to catch up.
Jeff Pedowitz and Dr. Debbie Qaqish discuss the 70/30 AI readiness gap and what it means for marketing leadership on this week's episode of Revenue Marketing Raw. Listen wherever you get your podcasts.
The Pedowitz Group | pedowitzgroup.com