Everyone’s Talking About AI
Not in theory, and not in the “7 prompts to replace your social media team” – in real practice. CMOs are being asked to move faster, do more with less, and figure out where AI actually fits inside their marketing engine.
And most teams are doing what you’d expect:
- They’re testing new tools,
- Layering in custom agents,
- And paying for more subscriptions.
Just really trying to find something that sticks – and is as easy to use as promised.
The good news, some real progress is happening. But under the surface, there’s a lingering, growing (or should I say widening?) problem.
Most websites have been built in layers over time.
Pages added. Content rewritten. Sections bolted on for campaigns, products, or leadership requests. What you end up with isn't a system. It's a collection of decisions - and AI doesn't know what to do with that.
Welcome to the Messy Middle
What we’re seeing across marketing teams isn’t a lack of effort. The teams at some of our most forward-thinking clients have that in spades, but there’s underlying mismatch.
On one side: What AI promises – speed, efficiency, scale. And on the other: Your actual marketing system – your website, your content, your data, your workflows, that thing you’ve been adding onto everyday, often for years, without consequence.
The problem is, they don’t line up perfectly.
You probably see it in the day-to-day. Some common symptoms…
- You’re paying for multiple AI tools doing similar things, with no clear system behind them
- Content is generated faster, but still bottlenecked in review and approval
- Inconsistent outputs depending on who’s using what platform
- Data that doesn’t fully connect, so decisions still rely on gut over confidence
It’s not that anything is completely broken, but nothing is working the way it should.
Why? Because of the messy middle. It’s that very real gap between AI ambition and reality.
AI Can’t Fix a Broken System, But it Will Expose It
AI is only as effective as the system it sits on top of. If your foundation is fragmented, AI doesn’t solve it, it amplifies it. Remember “garbage in, garbage out”? Well the same principle applies.
And right now, most marketing systems weren’t built for how AI needs to operate.
Especially your website.
Your Website IS the System
In most cases, and for almost all of our clients, the website is still the single source of truth. It doesn’t matter if it was written for prospects, customers, job candidates, investors, or SEO:
- Your messaging
- Your offerings
- Your value statements
- Your content
- Your knowledge
- Your structure
It’s what they all use.
And if you haven’t noticed the rapid decline of your web traffic, it’s increasingly what AI tools rely on to generate anything meaningful about you.
But here’s the messy reality: Most websites have been built in layers over time. Pages added. Content rewritten. Sections bolted on for campaigns, products, or leadership requests.
What you end up with isn’t a system. It’s a collection of [often unconnected] decisions.
And well, AI… it just doesn’t know what to do with that.
Before You Layer on AI, Clean the House
It’s an easy analogy to follow, just think of it as a remodel.
You wouldn’t add on top of the clutter. You’d clean it out first (ideally throw it out, we don’t need any more storage facilities), making sure the floors were spotless, walls ready for paint, and windows clear of cobwebs.
The same principle applies to your website.
Before you layer AI into your marketing, you need a clean, structured foundation:
- Clear, consistent messaging
- Defined content hierarchy
- Organized, accessible knowledge
- Connected and trustworthy data
- A technical platform that performs
You need a system that those tools can actually work with.
What AI Readiness Actually Looks Like
Who hasn’t wanted to run before they walk? It’s certainly more exciting – but also fraught with injuries. So we’ve strapped on our parenting helmet, and started helping teams assess and minimize the gap, before they fall in.
At a high level, AI readiness for your website comes down to five areas:
- Messaging – Is your positioning clear and consistent enough for AI to interpret and reuse?
- Content Structure – Is your content organized in a way that can be surfaced, reused, and expanded?
- User Experience & Conversions – Does your site guide users (and AI-assisted journeys) toward meaningful, measurable outcomes?
- Data Integrity – Can you trust what’s happening, and can AI access in a format it understands?
- Technical Foundation – Is your platform fast, structured, and accessible to both users and machines?
You’re not aiming for perfection, but the closer you get, the better the results will be. Any other way, you’re just throwing AI on top of a system that can’t support it.
The Shift You Need to Make
The teams that will get this right aren’t the ones chasing every shiny new tool. I have no doubt that they will see some short-term wins (“Hey CEO – look what we did!”), but the long-term consequences will be messy and expensive.
It’s the teams that pause to take a beat and fix the system, who will realize the greatest gains.
- AI outputs will become more consistent
- Workflows will actually speed up
- Data will start to align
- Tools will begin to complement each other instead of compete
That’s when AI ambition starts to be realized – efficiency, lower costs, faster outputs – not just more noise.
Start With the System
If any of this feels familiar, take that beat, because you’re not behind, you’re in the same messy middle as most of your colleagues, but you now have a plan to clean it up.
Close the gap. Everything else gets easier.
AI Readiness FAQs
What is AI readiness?
AI readiness is whether your website, data, tools, and workflows are structured well enough for AI to actually work the way you expect it to.
If those pieces are connected, AI can improve speed and efficiency. If they’re not, it tends to create more noise than value.
What is the “messy middle” in AI adoption?
The messy middle is where most teams are right now.
They’ve started using AI tools, but their underlying systems haven’t caught up. It’s the gap between what AI promises and what your current setup can actually support.
Why isn’t AI delivering ROI for many teams?
In most cases, it’s not the tools — it’s the system underneath them.
AI depends on clean data, clear content, and connected workflows. Without that, results are inconsistent and hard to measure.
How do I know if my team is stuck in the messy middle?
A few signs tend to show up:
- multiple tools being used for the same job
- inconsistent outputs from AI tools
- unclear or unreliable attribution
- workflows that are still mostly manual
Nothing is completely broken, but nothing feels fully dialed in either.
What actually needs to be in place for AI to work?
It usually comes down to a few core areas:
- structured website and content
- clean, connected data
- a streamlined tool stack
- defined workflows
- consistent use of AI across the team
What’s the first step toward becoming AI-ready?
Step back and look at your system as a whole:
- How your site is structured?
- How your data flows?
- How your tools connect.
- How your team actually gets work done.
That’s usually where the gaps become obvious.