How to Create AI Agent-Ready Content in Three Steps

Wise gets around 12.8 times more AI traffic than Revolut. Starling gets around 4.8 times more than Monzo. Neither of those results is about budget or brand size.

They are about AI agent-ready content: content structured so that AI agents can discover it, read it, parse it and actually use it to complete a task.

Charlie Marchant, CEO of Exposure Ninja, was recently invited to speak at BT and EE’s London headquarters in front of the biggest audience they had ever had for a panel to talk about agentic search.

Here are the three shifts that matter most.

Follow Charlie Explains AI Search on LinkedIn to stay up to date on the latest in AI Search.

What AI Agent-Ready Content Actually Means

Traditional web pages were built for human eyes and for browsers, with the goal of ranking at the top of Google and Bing.

Charlie Marchant explains that AI agent-ready content is “ the way we structure our content on our websites and online to format it so that AI agents can easily discover it, read it, parse it, and use it to complete the tasks that they are working on.”

Charlie Marchant is clear that this is not a second content operation running alongside your existing one: “This doesn’t mean creating a whole different set of content specifically for agents. This is about what we do with the content that we’ve got and that we’re producing to make sure it works for both humans and AI agents.”

“Now AI is touching more areas of the business than just marketing. Suddenly, stakeholders across procurement, finance, legal are interested in what’s happening with AI, how we get our business’ content surfaced in AI answers, how we get recommended in ChatGPT and Gemini, Perplexity, and other platforms, and what we do about AI agents.” Charlie Marchant, CEO of Exposure Ninja

3 Steps To Build AI Agent-Ready Content 

Build a Cityscape of Content

Most content libraries are flat. Individual blog posts, published consistently, that never add up to a position on anything.

The alternative is a cityscape of content. Core topic pillars act as the landmarks: “the obvious, tall, unmistakable, longer pieces of content that define your position and define key subject areas for your business.”

Around each landmark sit connected clusters that mirror query fan-out, the process AI platforms use to research an answer. As Charlie Marchant explains, “when you type a prompt into AI, they are fanning out that query into multiple, sometimes even hundreds of different queries that they’re running in the background.”

That means follow-up questions, comparison content, edge cases, case studies and scenarios. If your site answers the landmark question and nothing else, you are visible for one query in a chain of dozens and invisible for the rest of the buying journey.

You do not have to guess what that cluster content should be. People Also Ask data shows the adjacent questions. Sales and customer calls show the language your customers actually use, rather than the language your industry uses about itself.

“It’s very rare when we search that we ask just one question and then stop. Usually, we ask something, we ask something else. It creates a snowball. We’re then doing comparisons, and we’re then checking information. We might check reviews about a business and so on. And an agent’s doing the same thing, but it’s trying to do it faster and more thoroughly. If your site can answer that big landmark question, but then nothing else, you kind of dropped out of the process.” Charlie Marchant, CEO of Exposure Ninja

Remove the Need to Infer

This was the point Charlie Marchant pushed hardest on at the BT and EE panel: prices, specifications, eligibility limitations, stock availability and next steps should all be explicit, current and presented consistently across pages.

When an agent has to infer, one of two things happens, and both cost you revenue:

1. It guesses, which Charlie Marchant calls “really risky” because the guess will not necessarily be right about your business.
2. Or “the agent actually just doesn’t use us at all. It goes and finds a different source because it can find better content that’s more clearly written.”

The strongest AI agent-ready content has two layers working together:

1. The Decision Layer: The decision layer gives an agent everything it needs to assess whether you meet the user’s need: “What does it do? Who does it suit? What does it cost? What are the limitations?” Stating limitations feels counterintuitive to most marketing teams, but it’s also what makes you recommendable.
2. The Action Layer: The action layer is the dependable route to the next step, and specificity is the whole game here. “Contact us is a really vague action. It doesn’t describe anything. When we contact, what’s going to happen? Whereas, for example, if we’re using request a home broadband quote, it clearly describes the action. It describes who it’s for. It describes what you’re going to get.”

Pages with both layers are the ones agents can safely put in front of a user.

Brand Size Does Not Guarantee AI Visibility

This is the finding that surprises boardrooms most, and the one large brands least want to hear.

“In our research at Exposure Ninja, we have found that many smaller brands can consistently outperform larger competitors in AI visibility, not because they’re smaller, but because their content is deeper, it’s clearer, and the answers have a better shape,” explains Charlie Marchant.

Hence these results: Wise gets around 12.8 times more AI traffic than Revolut, and Starling gets around 4.8 times more than Monzo. Challenger brands winning AI visibility in a category where the competitors have far more budget.

“These small brands, they’re not beating giants by accident. In most cases, these are brands who have spent a lot of time, many years, building out educational question-led content, answering real customer questions, while their competitors may have just been writing more brand-style copy.” Charlie Marchant, CEO of Exposure Ninja

If you are the market leader, the cost of waiting is the real risk: “the longer it’s left, the more expensive it becomes to catch up because it’s not an overnight change.”

The Three Takeaways

• Build a cityscape of landmark content pieces and connected topical clusters.
• Remove the need to infer by giving every page that matters a clear decision layer and action layer.
• Stop assuming brand size will carry you, because AI visibility is clearly not carrying some of the largest brands out there.

The future of content is not writing for humans or agents over one another. It is making sure the answer is there, the evidence backs it up, and the next step is obvious.

If your content is not getting picked up in AI answers, our AI Search Optimisation specialists can show you where the gaps are and what to fix first. Book a consultation call, and we will walk you through it.