When Everyone Has AI, Who Owns Marketing?

After nearly 30 years in marketing, I've learned that getting everyone to tell the same story, reach the right customers, and contribute to revenue is much harder than creating the next campaign.

Years ago, I led marketing for a mid-sized company and served its mergers and acquisitions team. When we acquired another business, my job went well beyond simply announcing the deal.

I brought together marketing teams, technology, systems, and communications. Websites had to reflect the expanded business. Sales needed materials that explained the combined offering. Employees and customers needed to understand what had changed. Events, trade shows, and thought leadership had to support the company's direction.

I reported directly to the CEO, and the deal included a revenue goal. The faster we brought everything together, the sooner sales could pursue new opportunities, and we could start delivering on the investment.

Marketing touched almost every part of the business, including sales, product, technology, operations, finance, communications, and leadership. That experience reinforced something I've believed throughout my career. Marketing works best when someone understands how all the pieces of the business fit together and is accountable for turning them into growth.

We were doing all that long before generative AI. Now AI is changing who can do marketing work, which raises the question of who's responsible for the results.

Everyone can create marketing now

A salesperson can use AI to write prospecting emails and build presentations. A product manager can generate launch messaging. An executive can publish an article. Customer success can draft client communications. Anyone can research competitors, analyze data, or ask AI for a marketing plan.

Some of that work is excellent. Some of it is confidently wrong. Most of it looks pretty good at first glance.

Adobe's 2026 AI and Digital Trends research, based on a global survey of 3,000 executives and practitioners, found that 70% reported improvements in content creation among non-creative teams. That makes perfect sense. AI has made producing content considerably easier.

The problem is that each of those people represents the same company, often with different information, priorities, and ideas about what matters to the customer.

Sales promises something the product team hasn't delivered yet. An executive describes the company differently than the website does. A campaign targets an audience the business doesn’t yet serve. Customer communications contradict what sales have been telling prospects.

Each piece of work can look professional, yet collectively, the company looks very confused.

Someone needs to own the message and make sure the work supports the business. I believe that belongs to marketing leadership, working closely with the other functions that shape the customer experience.

That doesn't mean marketing should approve every email, presentation, or LinkedIn post. Give people the tools. Give them approved messaging, brand standards, customer research, and verified product information. Set clear rules on claims and customer data. Then set them loose.

On an October 15 episode of Exit Five, Jessica Rosenberg described building a library of reusable brand instructions for AI tools, so employees across the company could produce materials that followed established standards. That's a practical response to a problem more companies will face.

Adobe's content management research found that 55% of organizations reported strong AI governance policies, while only 43% said those policies were consistently followed. Having guidelines sitting in a document somewhere is only the beginning. People need to use them.

We've seen this technology problem before

AI is also starting to make marketing decisions, and someone must own those, too.

Gartner's 2026 CMO Spend Survey found that 70% of marketing leaders said their internal processes were too immature to implement and scale AI effectively. Most of the companies surveyed bring in more than $1 billion a year. They have substantial resources, and they're still struggling with the basics.

I've seen this before with CRM, marketing automation, and analytics. A company buys an expensive platform expecting better performance, then has to make decisions. Who owns the data? Does sales agree with the definition of a qualified lead? Are we measuring the right things? Who maintains the system? What happens when the information is wrong? Does anyone know what we're getting for the money?

An expensive platform won't fix an unclear strategy or a broken process, and neither will AI.

AI can act on its own recommendations, and it will do much more. Gartner's 2026 research on marketing automation found that CMOs expect AI-driven automation to grow from 16% of marketing work in 2026 to 36% by 2028.

I'm thrilled! I'd gladly hand over hours of repetitive work to agents that monitor campaign performance, clean up reporting, flag changes in ad spend, and catch problems in CRM data. But I want to know what decisions the agent is making, what information it's using, and when a person needs to step in.

An agent can optimize for clicks that never become qualified opportunities. It can move ad dollars without understanding the economics or what sales is trying to accomplish. I've already watched AI produce a convincing marketing plan that changed the target customer halfway through the document.

Here's how that went down. AI created a polished plan, but the recommendation was wrong. I wrote about that experience in AI Can Produce More Marketing. That Doesn't Make It Good Marketing.

So, before an agent starts moving money or talking to customers, companies need to decide who defines success, who checks the results, and who has the authority to change course.

Your buyers have AI, too

Gartner reported in May 2026 that 45% of surveyed B2B buyers had used generative AI during a recent purchase, mostly to research vendors and products. And 69% preferred to validate AI-generated information with a sales rep.

This is where all that inconsistent messaging starts to hurt. When the website says one thing, an executive's article says another, and a sales deck says a third, AI-powered research can surface those contradictions before a prospect ever speaks with sales.

Everything a company publishes needs to be accurate and consistent wherever buyers find it. The relationship between marketing and sales matters more than ever, because buyers who do their own research still want a knowledgeable person to answer questions, explain differences, and build confidence.

Marketing needs to know what customers are asking, what sales is hearing, what the product can deliver, what competitors are doing, and how the company shows up in the market. That responsibility extends well beyond content.

Why experience matters more now

Bringing all of that together takes someone who has worked across the business.

I've managed websites and technology, built demand generation programs, worked alongside sales, developed content and campaigns, managed agencies and budgets, supported product launches, and helped integrate acquired businesses. I've worked with the people making strategic decisions and the people getting the work done. I'm an experienced marketing generalist, and I consider that one of my greatest strengths.

AI makes that experience more useful because I can move between research, data analysis, positioning, content, technology, and planning far faster than I could a few years ago. I can test ideas, compare alternatives, and dig into reporting. I can now do work I used to hand off to a specialist, like building a quick analysis or pulling together competitive research.

The most important thing I bring is knowing what questions to ask. Does this recommendation make sense for the business? Is that the customer we should be targeting? Can sales use what we've created? Is the budget realistic? Does this claim have evidence to back it up? What happens after someone responds to a call to action (CTA)?

My favorite question is the simplest one. What are we doing all this work for?

I don't see the sense in producing 50 campaigns when five well-planned ones will contribute more to the business. I don't need another dashboard filled with impressive activity metrics that nobody can connect to sales or revenue. And I have no interest in producing more generic AI content just because we can.

That's also why I'm wary of job descriptions that list every AI platform on the market. Employers did the same thing with CRMs, automation platforms, and analytics tools. Those systems change, companies switch platforms, and new ones replace old ones all the time.

I'd rather hire a curious, experienced marketer who can solve problems and learn new technology than someone whose primary qualification is familiarity with the latest set of tools.

The 2026 CMO Survey from Duke University's Fuqua School of Business, with support from Deloitte, found that marketing leaders ranked having the right talent ahead of having the right technology as a driver of future organic revenue growth. I agree.

That doesn't give experienced marketers permission to stop learning. If anything, I feel more responsible for keeping up with AI, understanding what it can do, and questioning where it falls short. I'm still learning, and I expect I always will be.

So, who owns marketing?

More people should contribute. Sales know what prospects are asking. Product understands what's being built. Customer teams hear what clients like and where they're struggling. Finance understands the economics. Technology supports systems and data. Leadership sets the direction. AI gives every one of them more ways to contribute, and I welcome that.

But someone must bring it together. In practice, marketing leadership needs to establish a few things.

• A shared, up-to-date source for messaging, positioning, and approved product claims that people and their AI tools can use.
• Clear rules on what employees and AI tools can communicate about the product, pricing, and customer data.
• Set clear limits for AI agents, including what they can change independently and when a person must approve a decision.
• Performance measures tied to business outcomes, including qualified opportunities, customer retention, and revenue.

Someone needs to understand the customer, connect the company's capabilities to market needs, set the message, question the data, and ensure the work contributes to the company's goals. That takes experienced marketing leadership with a seat at the table and the authority to make decisions.

When I was integrating acquisitions, nobody cared how many marketing assets we produced. The CEO wanted to know whether we were bringing the businesses together, supporting sales, and moving toward the revenue goals behind the investment.

That's still how I look at marketing.

Give everyone access to AI. Give them the tools and the freedom to contribute. Then make sure someone with experience, business knowledge, and authority owns what goes to market and is accountable for the results.