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Sponsored by Markup AI

You & I have been going deep on AEO/GEO all year.
So obviously, I thought of you when I saw this.

🚨Markup AI is about to drop new AI Visibility Agents.
And they're offering us early access. (I already put my name down.)

The agents scan your content for the 4 signals AI uses to decide whether to cite you:
1. Snippet readiness
2. Source authority
3. Data freshness
4. Fluff-free 🚫

Maybe my favorite part: the agents run right inside Google Docs.

You'd be 1 of the first to get access.
With a direct line to Markup AI's team.
So you can get cited before your competitors.

Get on the list for AEO Agents

SPARKNOTES FROM THE POD

HOW TO IMPLEMENT AI IN YOUR MARKETING ORG

Christine Royston's resume reads like a tech company hall of fame. Udemy. Bitly. Dropbox. Salesforce.

Now she's CMO at Wrike. A 20-year-old work management platform helping teams collaborate better.

Which means she's seen EVERY type of workflow mess you can imagine.

Broken approval chains. Unnecessary handoffs. Projects that take 3 weeks when they should take 3 days.

And now everyone's throwing AI at these problems. Hoping it'll magically fix everything.

Spoiler: It won't.

Christine's approach is different. She doesn't start with AI. She starts with a question that most CMOs skip entirely: "Have you set clear expectations with your team on how you're expecting them to use AI?"

We're in the honeymoon phase of AI right now. Finance teams are giving marketing a pass. "Sure, test some tools. Figure it out. Experiment."

But that grace period is almost over.

Soon, the CFO is going to walk into your office and ask: "We're spending $50K on AI tools. What's the ROI?"

And if you shrug, that budget disappears.

Christine's building the measurement system NOW. Before anyone asks. Because she knows the question is coming.

Listen to the full episode here where Christine breaks down why AI amplifies broken workflows, how to budget for usage-based pricing, and why expertise matters more than ever.

1️⃣. Fix Your Broken Workflows Before Adding AI To Them.

Christine's Take: "You don't want to put AI on a workflow that has too many approvals, that is going back and forth between multiple teams with unnecessary handoffs. So you sort of have to optimize the core first. Is the way we're doing work today the most efficient? And then look at how can AI automate that even more."

Blog post workflow: Draft ➡️ Manager review ➡️ Legal review ➡️ Brand review ➡️ Executive review v Final edits ➡️ Publish. Takes 14 days.

Someone decides to use AI to speed this up.

So AI writes the draft. Now it takes... 13.5 days.

You saved half a day. And paid for an AI tool.

The problem wasn't the drafting. The problem was the 5 approval steps.

AI automated the WRONG part.

Christine's rule: Optimize the workflow FIRST. Then add AI.

Map out every step. Find the bottlenecks. Cut the unnecessary approvals. Remove the handoffs that exist because "we've always done it this way."

Get the workflow down to the essential steps.

THEN use AI to automate the remaining manual work.

That's when you actually see velocity improvements.

Takeaway: Pick 1 workflow that drives you crazy (content approval, campaign launches, lead follow-up). 

Write down every single step. Circle the 1’s that add ZERO value but slow everything down. 

Schedule a meeting with stakeholders. Show them the workflow. 

Ask: "Do we really need this approval step?" Remove 30-50% of the steps. 

THEN identify where AI can help with the remaining manual work. Implement AI on the clean workflow. Measure time savings. You'll see actual velocity gains instead of tiny incremental improvements.

Want to see how AI agents actually work in marketing workflows? 

Christine's team at Wrike put together a guide on implementing AI agents without breaking your processes. Get the ebook here.

2️⃣. Curiosity Is Your Hiring Superpower. Technical Skills Can Be Taught.

Christine's Take: "Something that hasn't changed is you're always hiring for curiosity. You want marketers to be always asking the why, always looking at how can they do things a little bit differently for better results. And I think that that is super important to leverage AI."

AI changed a lot about marketing. But it didn't change what makes a great hire.

Christine still looks for the same thing: CURIOSITY.

People who ask "why are we doing it this way?" People who look at a process and think "there's got to be a better way."

Because those people will actually ADOPT AI. Not because their manager forced them to. Because they're curious about what it can do.

Technical skills? Trainable. Prompt engineering? Learnable. Tool knowledge? Gets you up to speed in a week.

But curiosity? Either you have it or you don't.

Christine also asks in interviews: "Are you using AI at home? Testing tools? Experimenting with prompts?"

If your company blocks AI at work (some still do for security reasons), are you exploring it in your personal life?

That's the signal.

And when she needed someone to lead AI transformation internally, she didn't hire externally. She promoted from within. Found someone with marketing expertise, technical skills, and AI curiosity.

That internal hire understood the workflows, knew the team, and had the credibility to drive change.

Takeaway: Add 1 interview question: "Tell me about the last time you changed how you did something at work because you found a better way." 

Curious people will have a story ready. 

For your current team: Look at who's shipping work faster without sacrificing quality. They're already using AI. 

Pull them aside: "I noticed you're crushing it lately. What's working?" 

Then ask: "Would you be open to showing the team your workflow in our next meeting? 10 minutes max."

Don't create a new role. Don't add responsibilities. Just give them a platform to share what they're already doing. Pay them a bonus or give them a title bump if they want it. But don't make it "extra work on top of your real job."

3️⃣. Your Team Won't Use AI Until You Tell Them How.

Christine's Take: "Have you set clear expectations with your team on how you're expecting them to leverage technology in general? How are you expecting them to use AI? And looking at when you're making these decisions, how are you going to measure success?"

Right now, your team is sitting at their desks wondering: "Am I allowed to use AI? Which tool should I use? Will my manager think I'm cheating if I use it?"

So they wait. Or they use it secretly and don't tell anyone.

That's adoption paralysis.

Christine fixes this by setting expectations UPFRONT.

Here's how we use AI on this team. Here's what we're measuring (velocity, impact, quality). Here's which tools we have access to. Here's what success looks like.

That simple clarity unlocks everything.

People stop waiting for permission. They start sharing workflows. They ask questions. They experiment openly.

Because you've made it SAFE to use AI.

Without that clarity, AI adoption stays stuck at 10%. With it, you hit 80% in a month.

Takeaway: Call a team meeting this week. 

Say exactly this: "Here's how we're using AI: First drafts, research, data analysis, formatting. Here's what we're NOT using it for: 

Final customer-facing content without review, strategic decisions. 

Here's how we'll measure success: Time saved per week, quality of output, volume of work completed. Here's which tools we have: [List them]. 

Here's my expectation: Everyone tests AI on at least one task this week. We'll share what worked in our next meeting." Then actually do that meeting. Make it a standing agenda item. Normalize the experimentation. Within a month, adoption will skyrocket.

4️⃣. Budget For AI Like A Program. Not Like A Tool.

Christine's Take: "It's not a seat based pricing model. It's not something that I can say, I know I'm going to spend this much on it this year, especially in the phase that we are where people are starting to figure out the power of it and how much we're spending on the usage now is probably going to increase significantly in the future."

Here's why your finance team is about to freak out about AI costs.

Traditional SaaS: $100/seat/month. 50 seats. $5,000/month. Easy to forecast.

AI tools: Usage-based pricing. The better your team gets at using it, the MORE they use it. Costs go UP as you get better.

That breaks the traditional budgeting model.

Christine treats AI like PROGRAM spend. Not tool spend.

If she invests $2,000 in AI this month and it drives $20,000 in impact (faster campaigns, better content, more output), she increases the budget next month.

It's ROI-driven. Not seat-driven.

But that requires different conversations with finance. You need buffers. You need quarterly check-ins. You need to track usage AND impact.

Right now, she buckets AI under "tools." But she knows it'll need its own line item soon. Because the spend is growing. And it should grow if the ROI is there.

Takeaway: Track your AI spend RIGHT NOW. Pull the last 3 months: ChatGPT subscriptions, Claude API costs, Jasper licenses, whatever you're using. 

Calculate what it produced: Content pieces written, campaigns launched, reports generated, hours saved. 

Build a simple spreadsheet: AI Cost | Output Created | Estimated Value | ROI. Schedule 30 minutes with your finance partner. 

Show them the ROI. Say: "We're spending $X. Getting $Y in return. This will grow as adoption increases. 

Can we create a dedicated AI line item with quarterly buffers?" Frame it as an investment with measurable return. Not as a cost center.

5️⃣. AI Scales Expertise. It Doesn't Replace It.

Christine's Take: "I think the most important thing for me is I never want to lose my own personal expertise. I want to make sure that I understand what makes a great marketer a great marketer and that my ability to understand how to use the tools is going to be just as important as using them in general. So I think that's why I am feeling like there's always going to be a place in the world for fantastic marketers."

Christine's not worried about AI taking her job.

She's worried about losing her EXPERTISE while relying on AI.

Because AI is a multiplier. It amplifies what you already know.

Great marketer + AI = Unstoppable.

Mediocre marketer + AI = Still mediocre. Just faster.

The differentiator isn't the tool. It's the EXPERTISE you bring to the tool.

You need to know what great marketing looks like. What resonates with your audience. What drives results. What's on-brand vs off-brand.

AI can't tell you that. It can execute faster. But it can't judge quality. It can't develop strategy. It can't know your customer like you do.

That's YOUR job.

So Christine's focus: Keep building expertise. Keep sharpening judgment. Keep learning what makes great marketing work.

THEN use AI to scale that expertise to 10X output.

The marketers who'll struggle? The ones who stop developing expertise because "AI can do it."

AI can't. It can only execute what YOU tell it to do.

Takeaway: Pick your deepest area of expertise (messaging, positioning, campaign strategy, audience research).

 Block 1 hour per week to sharpen it.

 Read case studies in your space.

 Analyze what worked and why. Study your competitors' best campaigns. Build judgment that can't be automated.

 Document your expertise: "Here's what makes great [X] in our industry." Use that as your AI briefing doc. 

When you prompt AI, you're feeding it YOUR expertise. The better your expertise, the better AI's output. That's the competitive advantage. Not the tool. The brain using the tool.

Sponsored by Wrike

I’ve said it before. Guess I’ll say it again: 
AI without structure just speeds up the mess.

Which is scary, because I see a LOT of brands just handing employees the keys to an enterprise AI plan and telling them to go nuts.

This guide shows you how to build ORGANIZATIONAL intelligence on top of AI.
With a 3-part workflow framework.
Makes my Marketing Ops heart happy.

Get Smarter Workflows

IN A MEME

Ok! I have been to Pequod’s once. I don’t think we can go back because Ari tripped on the stairs there. PTSD.

Your friend,

Daniel