Marketers still write for humans who skim. AI engines “read” differently. They look for patterns, structure, and evidence they can safely summarise. If your pages are stylish but vague, the model will skip them. Not because it hates stories, but because it can't extract meaning with confidence.

The focus isn't tricking the algorithm, but making your expertise machine-readable without losing your voice.

What does AI look for when it scans a page?

AI engines don’t experience a page the way a person does. They parse it. That means your words are evaluated for:

  1. Structure. Clear hierarchy with H1, H2, H3 used logically. Each section should have a single job and a descriptive heading.
  2. Consistency. Terms are defined the same way throughout. Labels match the copy. No bait-and-switch headings.
  3. Evidence. Specifics beat slogans. Named features, integrations, prices, jurisdictions, dates, job titles, and attributed stats.
  4. Extractability. Short, self-contained explanations that can be quoted safely.
  5. Coverage. The “why,” the “how,” and the “what next.” Not just benefits, but trade-offs and fit.

If those signals are missing, the model can't reliably paraphrase you. So it finds a source that it can.

Why over-styled pages get ignored

Pages designed as brand theatre often lead with a vibe: a big visual, a clever H1, and 150 words of mood before anything concrete appears. Humans sometimes tolerate it. AI does not. The model needs to map concepts to questions quickly. Fluffy intros, vague headings, and metaphor-heavy subheads break the signal chain.

Example: a financial services page titled “Let’s talk cover.” There is no semantic hint about what the page explains. Is it business insurance types? Claims process? Broker support? An AI engine can't infer that safely. Contrast that with “Types of business insurance explained.” The intent is explicit. The model can route a “which insurance do I need for a café in NSW” style query to this page, and it can quote a section confidently.

Think less “storytelling blog,” more “structured clarity.” You can still tell stories. Just make them support a clearly labelled section that answers a question in plain English.

If you’re wondering why this shift happened, I unpack how AI changed the funnel in my earlier piece.

What “machine-readable clarity” looks like on a real page

Use this pattern across articles, product pages, and help content.

1. A precise H1 that matches the page’s job
Bad: “Let’s talk cover”
Better: “Types of business insurance explained”

2. A short lead that defines scope in one sentence
“Here’s how common business policies work in Australia, when each applies, and how to choose based on risk, size, and industry.”

3. Explanatory H2s framed as questions

  • What does public liability insurance cover
  • Who needs professional indemnity insurance
  • How do you compare business insurance quotes

Each H2 gets a direct, two to four sentence answer before any narrative.

4. Scannable bullets with specifics

  • Typical claim examples
  • What is and isn’t covered
  • Industry fit (retail, hospitality, trades)
  • Cost drivers (turnover, staff, location)

5. Attributed stats and definitions
If you cite a number, attribute it. If you use a term of art, define it once in plain English. Models weight clarity and attribution.

6. A “what to do next” block
One paragraph that connects the explanation to an action, without sales rubbish.

This is what I like to call respectful writing. You remove friction for both readers and AI by making the meaning obvious.

Headlines and subheads that get cited

Headlines that try to be clever often hide intent. Replace them with labels that explain the value of the section.

Vague: “Get set up for success”
Clear: “How to set up payroll in Xero step by step”

Vague: “Why it matters”
Clear: “Why multi-factor authentication reduces account takeover risk”

Vague: “Think bigger”
Clear: “When to move from shared hosting to a dedicated server”

Clear labels make your outline a semantic map. That is what AI summaries follow.

The anatomy of a paragraph AI will quote

A quotable paragraph is self-contained, specific, and balanced.

  • Start with the point. “Public liability insurance covers claims of injury or property damage caused by your business on your premises or at a customer site.”
  • Add context. “Retailers and trades are the most common buyers because customer foot traffic and site work increase risk.”
  • Name a boundary. “It does not cover injuries to your employees, which sit under workers compensation.”
  • Offer a next step. “If you host events, ask for coverage that includes temporary venues.”

Four sentences. One idea. Enough detail to stand alone. Easy for a model to lift.

Make relationships explicit

AI does better with statements than implications. If your product integrates with a known platform, name it. If your service is only available in certain states, list them. If your guarantee applies for 30 days, say “30 days.” The more precise the relationship, the more confidently a model can match your page to a specific question.

Examples of relationships worth stating explicitly:

  • Integrations (Xero, Slack, HubSpot, Shopify)
  • Regions and rules (Australia, NSW, GDPR)
  • User types and roles (HR managers, brokers, principals, founders)
  • Limits and thresholds (10 seats, 50 GB, 24/7 phone support)
  • Versions and dates (v2.3 released March 2025)

Formatting that helps AI and humans

This is craft, not decoration.

  • One idea per section. Do not bury key claims in long stories.
  • H2s for new topics, H3s for parts of a topic. Resist the temptation to skip levels.
  • Bullets for lists of like things. Keep bullet labels parallel so they parse cleanly.
  • Short sentences. Aim for one thought per line of reasoning.
  • Alt text that states function. “Diagram: request flows from web app to API gateway to database.”
  • Figure captions that explain. Give the model a sentence it can quote.

Why your “voice” still matters

Plain English is not plain sounding. You can be precise and still sound like you. Voice comes from choices: which examples you use, which trade-offs you acknowledge, which phrases you avoid, and how directly you guide the reader. You do not need to write like a manual. You need to make meaning unmissable.

What AEO actually does here

AEO is the bridge between your expertise and the way AI summarises it for real people. It is not a new set of hacks. It is a standard for how clearly you explain yourself.

  • It aligns page purpose to real questions.
  • It enforces structure so each answer has a home.
  • It pushes for specifics, attribution, and fit.
  • It makes your content safe to quote.

When AI cannot identify your expertise, it will not quote you. When it can, you do not just “rank.” You become the answer.

Quick before-and-after

Before
H1: Let’s talk cover
Lead: Insurance is complicated, but we’re here to help.
H2: Get set up for success
Copy: We’ve helped thousands of businesses find the right policy. You’ll be amazed how easy it is.

After
H1: Types of business insurance explained
Lead: Here’s how common business policies work in Australia, when each applies, and how to choose based on risk, size, and industry.
H2: What does public liability insurance cover
Copy: Public liability covers claims of injury or property damage caused by your business on your premises or at a customer site. Retailers and trades buy it most often because customer foot traffic and site work increase risk. It does not cover injuries to your employees. For that, use workers compensation. If you host events, ask for coverage that includes temporary venues.

The second version is not just clearer. It is usable by an AI engine without guesswork.

Common blockers inside teams

  • “But our headline has to be creative.” Make the headline clear. Be creative in your examples and visuals.
  • “We don’t have stats.” Then use specific examples and cite authoritative definitions. Specificity is the point.
  • “Legal will not let us name trade-offs.” Work with legal to state boundaries rather than promises. Models reward honesty.
  • “We already wrote it all in a PDF.” Put core explanations on the page. AI is less likely to parse a PDF well.
  • “That sounds too simple.” Simple is not simplistic. Simple is what lets a complex idea be quoted correctly.

What to change this week

  • Rename vague pages and sections so the purpose is obvious.
  • Add one sentence at the top of key pages that defines scope.
  • Rewrite three headings as questions and answer each in four sentences.
  • Replace generic bullets with specifics: names, numbers, examples.
  • Add a “what to do next” paragraph to your top five pages.

These small changes compound. They also make your analytics cleaner, because readers stop bouncing to find the missing piece you hid behind a flourish.

The takeaway

AI does not skip your content because it prefers competitors. It skips content that hides its meaning. Make your expertise easy to see, and both people and machines will.

If you are not sure how AI currently sees your site, our AEO Scorecard shows you.

FAQs

What does AI look for on a web page
Clear headings, concise explanations, specific details, and attributed evidence that can be quoted safely.

Why do some pages get ignored by AI
Vague headlines, fluffy intros, and unclear structure make it hard to extract meaning, so models prefer clearer sources.

How do I make my content more machine-readable
Use precise H1s and H2s, answer questions directly, add specifics and attribution, and finish sections with a next step.

Does this kill storytelling
No. Storytelling still works when it supports clearly labelled sections that answer questions in plain English.

About the author

Alice Xerri is the founder of AX Content, a Melbourne-based content consultancy helping businesses build from the ground up, one piece of content at a time.

She works with brands across finance, tech, and professional services to turn complex ideas into clear, confident content that drives growth.

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