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Most marketers I speak with can cite references, know the latest tools, and stay up to date with the latest vendor reports. What they can’t tell me is where their own team is on the AI journey. They know they’ve made progress…but where are they on this journey?
The signals most marketers track (number of AI licenses, tool adoption rate, hours saved per week) are real, but they describe the business, not the position of your team. How can a leader express progress when the budget conversation is in two weeks?
Most budget discussions start with sectoral references. So let’s look at what they really tell us before moving on to the audit.
State of Salesforce Marketing 2026 found that 75% of marketers use some form of AI, and only 16% of them run anything truly agent-like. Supermetrics 2026 Marketing Data Report estimates full workflow adoption at 6%. The state of the Adobe marketg in an AI-driven world found that only 7% achieved business results, and eight out of ten marketing teams missed an opportunity last quarter because they couldn’t respond quickly enough.
The latest entry came earlier this month from Carnegie Mellon and Accenture, who published their AI Adoption Maturity Model on June 8. Drawing on surveys of nearly 600 practitioners, they reported that 95% of organizations are not realizing any ROI on AI, and only 8% have scaled AI at the enterprise level.
These numbers provide useful context for the market as a whole. They don’t answer the question you’re asking before the next budget cycle: where is your own team?
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Walking around the AI field
Most AI marketing dashboards currently in circulation (Jasper, Salesforce, NinjaCat, the new SEI/Accenture version) compress maturity into a one-dimensional score. A sheet music works well for a board deck. It’s a finer tool for budget planning because it tells you your altitude without telling you what’s stopping you from taking the next step. For this reason, work from a field map with seven steps.
Here’s what each waypoint looks like on a marketing team, with a diagnostic question that tests if you’re there:
Zone of confusion
Adoption is scattered. A memo came out. Some licenses have been purchased. Nothing structural has changed.
- Diagnostic: Can anyone on the team express, in one sentence, what AI is used for in marketing here?
First victories
A handful of people have discovered something truly useful (a brief build flow, a content scoring loop, faster competitive analysis), and they can show it to you.
- Diagnostic: What are three recurring tasks where AI has measurably reduced completion time over the past 90 days?
AI Bifurcation
The team broke up. Experienced users outperformed holdouts in a way that’s hard to explain by skill alone.
- Diagnostic: If you ranked your team based on “AI-assisted weekly production,” would the top and bottom be in the same league?
Localized progress
The discrete functions (content, operations, demand generation, brand) have each understood AI in their own lanes, while the handoffs between them still seem ancient.
- Diagnostic: When a campaign moves from strategy to execution, where does AI stop and human input begin?
Coordinated progress
Transfers work. Shared use cases are documented. There is a named AI lead or enablement center holding it all together, and cross-functional campaigns now move faster, not just the individual tasks within them.
- Diagnostic: Is there anyone other than the CMO who is responsible for marketing AI adoption?
Work redesign
The roles have changed on paper. The content strategist job description reads differently than it did a year ago, as does the marketing operations manager job description. The flowchart reflects what the AI has changed, not just what you bought.
- Diagnostic: When was the last time a marketing job description was rewritten because of AI?
A hyperadaptive future
Marketing functions as a value stream that constantly senses and adapts. Very few teams are still there. If so, you already know it.
Sit with this list for a minute. When was the last time your leadership team had clear visibility into where each marketing function fit in? Many marketers I work with answer “never” to this question. Which is okay to admit. This simply means that the audit has not yet been performed.
What do you do with the results?
Two patterns emerge when marketers examine the map of the land.
The first is that teams rarely stay at a single waypoint. Content may be in its early stages of success while marketing operations are achieving localized progress and the brand is still working in the zone of confusion. The AI bifurcation waypoint is the same phenomenon appearing at the individual level rather than the functional level. All of this matters when you think about what you’d like to fund next year.
The second is that most teams are a waypoint or two behind where the marketer thought they were. This gap is not really about attention or care, but generally comes down to what is being measured. License counts and adoption rates measure what has been tried. Whether something is stuck is another question.
When thinking about next year’s funding, consider these three questions:
- What is the highest waypoint a marketer has reached? (This sets the ground from which they can continue to climb.)
- What is the lowest waypoint and what would it take to move them up a notch? (It is a good place for investment.)
- Is the gap between the highest and lowest levels increasing or decreasing? (This is your bifurcation reading.)
Teams that go into planning with answers to these three questions will spend their AI budget very differently than teams that come in with a generic baseline number.
Consider completing this audit before your next planning meeting. You may discover that your biggest investment opportunity in AI isn’t where you hoped.
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