Is Your Marketing Org Built for AI?

Summary

AI is changing how marketing work gets done, but many marketing organizations are still structured around outdated roles, workflows, and assumptions. This post explores the signs that your org structure may be holding your team back and how CMOs can rethink roles and capabilities to build a more adaptable marketing organization.

By Brenna Lofquist, Senior Consultant at Heinz Marketing

In most cases, CMOs didn’t design the marketing organization they’re leading today. They inherited it. The teams, roles, reporting structures, processes, and responsibilities were usually built incrementally over time, often long before AI became part of the conversation. The organization evolved as the company grew, new channels emerged, technology was added, and new priorities came down from leadership.

That doesn’t necessarily mean the structure is wrong. It means it was designed around a different set of assumptions. Marketing used to move at a different pace. Teams were more specialized (some still are). Campaigns followed relatively predictable processes. Technology was often added to support individual functions rather than to orchestrate end-to-end workflow.

AI is changing those assumptions. It’s making it possible to automate work that once required significant human effort, compressing timelines, changing the skills required for certain roles, and blurring the lines between functions. However, simply adding AI tools doesn’t automatically make the organization more effective. In some cases, it can actually make existing problems more visible.

If five teams and three approval steps are required to launch a campaign, AI can help each team work faster but the campaign can still take weeks to launch.

The question CMOs need to ask isn’t, “How should we restructure marketing for AI?” It’s a more fundamental question: Which assumptions behind our current organization no longer hold?

Your Org Chart May Be Telling You How Marketing Used to Work

The traditional marketing organization was built around functional specialization. Content had its team. Demand generation had its team. Product marketing had its team. Marketing operations managed the technology and data. Events, digital, communications, and sales enablement often had their own responsibilities and processes.

There was a good reason for this structure. As marketing became more sophisticated, specialization allowed organizations to build deeper expertise and manage increasingly complex channels. But the work itself isn’t nearly as linear anymore.

A single campaign might require product marketing to define the audience and message, content to develop the assets, demand generation to build the campaign, marketing operations to manage the technology and data, paid media to activate it, sales to follow up, and analytics to determine whether it worked.

AI adds another layer. Some of the work that once belonged exclusively to one function can now be automated, augmented, or shared across several functions. The result is an interesting disconnect: the org chart still reflects functional ownership, while the work increasingly happens across functions.

That doesn’t mean every company needs to abandon functional teams or reorganize around AI. It does mean CMOs should pay attention when the way work actually happens no longer resembles the way the organization is structured.

The problem isn’t necessarily the org chart itself. It’s the gap between how the organization is designed and how work actually gets done.

Five Signs Your Marketing Structure is Holding You Back

Sign #1: Work gets stuck in handoffs

If a campaign has to move through five different teams before it can launch, the problem may not be that any one team is inefficient. The problem may be the handoffs.

Every handoff introduces the possibility of delay, miscommunication, rework, or competing priorities. And when no one owns the entire workflow, it’s easy for everyone to be responsible for their individual piece while no one is responsible for the outcome.

AI doesn’t automatically solve this.

You can generate content faster, build campaigns faster, and analyze results faster, but if the work still has to move through the same sequence of people and approvals, the overall process may not move much faster.

Ask yourself: Where does work routinely wait for someone else?

Sign #2: Everyone owns an activity, but nobody owns the outcome

Marketing organizations often have clear ownership of individual activities: Someone owns campaigns, someone owns content, someone owns marketing operations, etc.

But what happens between those activities?

Who owns the transition from MQL to pipeline? Who is accountable for making sure content actually supports campaign performance? Who owns the process from audience insight through activation and measurement?

These gray areas can become especially problematic as AI makes individual tasks easier to execute.

When execution becomes faster, coordination and decision-making become more important, not less.

If accountability ends at the completion of an activity, you can end up with a marketing organization that’s highly productive but not necessarily effective.

Ask yourself: Where do responsibility and accountability separate?

Sign #3: Your job descriptions don’t match reality

AI is changing what marketers spend their time doing. A role that once required someone to spend hours researching, drafting, analyzing, formatting, or building may now involve directing those activities, reviewing outputs, making decisions, and connecting the work to broader business objectives.

But the job description may still describe the old job. This creates a strange situation where the organization is technically staffed for the work it used to do rather than the work it actually needs today.

It can also make hiring more difficult. Instead of defining a realistic combination of capabilities, organizations sometimes try to find one person who can be a strategist, data analyst, AI expert, technologist, content creator, and campaign operator all at once.

That’s less a talent problem than a role-design problem.

Ask yourself: If you rewrote every marketing job description based solely on what that person actually does today, how different would it look?

Sign #4: You’ve added AI without changing the workflow

This may be one of the clearest warning signs. A team adopts an AI tool to generate content. Another uses AI for research. Marketing operations adds automation. Someone starts experimenting with AI agents.

Everyone becomes more productive, but the underlying workflow doesn’t change. The same approvals remain. The same handoffs remain. The same systems don’t talk to each other. The same person still has to review the work before it moves to the next team.

You’ve essentially made the individual steps faster without changing the process. That’s not necessarily a bad thing. AI can absolutely create meaningful productivity gains without a major organizational change.

But if the goal is transformational improvement, the question should be: Are we using AI to do the old work faster, or are we using it to rethink how the work gets done?

Sign #5: The organization moves slower than the market

Perhaps the simplest test is speed.

How long does it take your team to turn an idea into a campaign? How many meetings are required? How many people need to review it? How many systems need to be updated? How many times does the work get handed from one person to another?

Now consider how quickly your buyers are consuming information, changing priorities, and interacting with your competitors. If your organization needs several weeks to respond to something the market changes in several days, you may have an organizational problem, not a talent problem.

And adding more people isn’t necessarily the answer. Sometimes the constraint isn’t capacity. It’s the structure through which the capacity has to work.

Question the Assumptions Behind Your Org Structure

Most marketing organizations weren’t designed all at once. They’re the result of years of incremental decisions.

Each decision may have made perfect sense at the time. The problem is that those decisions don’t always get revisited when the business changes. AI gives CMOs a reason to question some of those assumptions.

Instead of immediately asking whether a particular role should exist, ask:

• Are we still solving the problem this team was created to solve?
• Does this work still require the same level of specialization?
• Are we organized around how our customers buy, or around our internal functions?
• Have we added responsibilities to roles without reconsidering what should come off their plates?
• Are there responsibilities that exist primarily because “that’s how we’ve always done it”?

The answer won’t always be to eliminate a team or consolidate roles. In many cases, the existing structure may still make sense. However, organizations should be able to explain why.

The goal isn’t to create an organization that looks radically different because AI is changing everything. It’s to make sure the structure reflects the business you’re actually running, not the one you were running five years ago.

Redesign Roles Around Capabilities, Not Just Titles

If the organization is changing, roles need to change with it.

AI is shifting many marketers away from hands-on execution and toward directing, evaluating, and applying AI-enabled work. Some roles may need broader capabilities, while others may become more specialized.

Rather than trying to hire an “AI marketer” who can do everything, ask: What capabilities does the organization actually need, and where should they live?

The goal isn’t to eliminate roles because AI can perform some of their tasks. It’s to make sure people are spending their time where human expertise creates the most value.

The Goal Isn’t an “AI-First” Org. It’s an Adaptable One

There’s no single marketing org chart for the AI era. The right structure will depend on the company’s size, GTM model, marketing maturity, technology, and talent.

What matters is whether the organization can adapt as the work changes. CMOs don’t necessarily need to rebuild their marketing organization because of AI. However, they do need to question whether the assumptions that shaped it still hold.

The question isn’t “What should our AI org chart look like?”

It’s “Does our marketing organization still make sense for the way marketing works today?”

If the answer is no, AI may not be the reason to redesign it. It may simply be the thing that makes the need impossible to ignore.

Wondering what needs to change in your marketing organization for the AI era? Email us for a complimentary brainstorm session!