Before You Buy Another AI Tool, Map How Your Team Actually Works

For marketing leaders who have an AI budget and want to know where it should go first.

I’ve spent 25 years in agencies and marketing departments, 15 of them leading teams. The work that stalled rarely stalled for dramatic reasons. It was a brief that kept changing, or an approval that waited for days. That’s where I start any conversation about AI, because those are the hours a tool can actually give back.

The budget, meanwhile, is moving faster than the process. Gartner’s 2026 CMO Spend Survey found that marketing leaders now put an average of 15.3% of their budgets into AI, yet only 30% report mature AI readiness, and 70% say their internal marketing processes aren’t mature enough to implement and scale it (Gartner, May 2026).

What is an AI readiness assessment?

An AI readiness assessment is a short, structured look at how a team works today, used to decide where AI should help first. For a marketing team it covers the workflow (how work moves from brief to report), the people (skills and confidence), the rules (brand, data and review) and the measures you’ll use to know it worked. Tools come last.

McKinsey’s latest State of AI survey shows why the workflow comes first. Nearly three-quarters of the companies getting real financial value from AI say they have fundamentally redesigned workflows around it, compared with about a quarter of everyone else (McKinsey, August 2026).

Tool-first vs workflow-first

	Starting with a tool	Starting with the workflow
Starting point	A tool someone saw in a demo	One real piece of work, from brief to report
What gets faster	One step, usually drafting	The steps where work actually waits
Where work piles up	At the next bottleneck, often approvals	Bottlenecks are dealt with as part of the change
Risk control	Decided case by case, if at all	Agreed before anyone starts
Proof of value	Hard to show without a baseline	Measured against today’s numbers

A new tool dropped into an old process usually speeds up one step and leaves the rest as it was. The work then piles up at the next bottleneck.

What to map in a marketing workflow

Pick one piece of work your team does often, such as a campaign, a monthly content calendar or a product launch, and follow it from start to finish. Do this with the people who do the work. A map drawn by managers alone tends to show how work is supposed to flow, which is rarely how it flows on a busy Tuesday.

Stage	What to record	Where AI could help	What a person keeps
Brief	Time to a signed-off brief, rounds of changes	Turning meeting notes into a first draft	Objective, audience, message
Concept and copy	Drafting time, revision rounds	First drafts and variations	The final idea and the brand voice
Production	Hours per asset, outside spend	Resizing, versions, first cuts	Brand standards and final quality
Review and approvals	Waiting time between rounds	Pre-checks against a brand checklist	Sign-off on claims and risk
Launch and publishing	Manual steps per launch	Scheduling and formatting	Timing and the last check
Reporting	Hours per report	Pulling the data together	What the results mean and what’s next

Waiting time and rework are usually where the surprises are.

Questions that show where AI fits

Once the map is on the wall, these questions help sort the candidates:

• Where does work wait, and why?
• Which tasks repeat every week with small variations?
• Where does quality slip because people are rushed?
• What work goes outside the team today, and what does that cost in time and money?
• Which tasks carry brand, legal or reputational risk if they go wrong?

The first four usually point to good places to try AI. The last one tells you where a person must stay in the loop and what rules the team will need before anyone starts.

How to run the assessment, step by step

1. Choose one workflow that runs every week or month.
2. Follow it with the people who do it, and time each stage, waiting included.
3. Mark where work gets redone, where it waits and what goes outside the team.
4. Flag the steps that carry brand, legal or reputational risk.
5. Pick two or three places to try AI first, and name an owner for each.
6. Note what has to change in the process before any tool will help (often the approval route).
7. Record the baseline: how long each stage takes today.

That last step is easy to skip and hard to recreate afterward. Without it, any claim about time saved is a guess.

Readiness is also about people

A workflow map shows where AI could help. It doesn’t show whether the team is ready to use it. McKinsey’s research on AI in the workplace found that only 1% of leaders describe their companies as mature in AI deployment, and that 41% of employees are more apprehensive about it and will need additional support (McKinsey, January 2025).

So when I map a workflow, I’m also paying attention to who feels confident and who is quietly worried about what changes for them. Both lists matter. The second one decides how the rollout should be paced and how much support people will need.

Common mistakes to avoid

• Mapping the ideal process. Map what happened on the last real campaign, delays included.
• Leaving out the people who do the work. They know where the time goes, and they’ll be the ones using whatever comes next.
• Assessing everything at once. One workflow done well teaches you more than ten done quickly.
• Skipping the baseline. It takes a week to record and is impossible to rebuild later.

Where I can help

This mapping is the first thing I do with a team in a workflow audit, before we talk about tools at all. You come away with a short, prioritized list: where AI belongs in your work, where it doesn’t yet and what to measure. From there, the next steps are usually building AI into the workflow and helping the team use it with confidence.

Final thought

If you do one thing this month, follow a single campaign from brief to report and write down every place it waited. It’s a small exercise, and it tends to change the conversation about which tools you actually need.

Frequently asked questions

Sources

1. Gartner, 2026 CMO Spend Survey, press release, May 11, 2026. Read on gartner.com
2. McKinsey & Company, “The state of AI in 2026: On the road to ROI,” August 25, 2026. Read on mckinsey.com
3. McKinsey & Company, “Superagency in the workplace,” January 28, 2025. Read on mckinsey.com

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