AI readiness isn’t a plugin. It’s the boring (and absolutely essential) work of building websites that are structured, consistent, and dependable enough to be understood by both humans and machines.

I’ve been building and maintaining websites since 2004. That means I’ve lived through every flavor of “the web is changing” cycle: table layouts, Flash, responsive design, the rise of WordPress, mobile-first everything, the long war for performance, accessibility becoming non‑negotiable (as it should be), and SEO evolving from keyword stuffing into a discipline that’s really about clarity and trust.

AI is the next big shift. But the punchline is familiar: the sites that do well aren’t the ones chasing hacks. They’re the ones with strong fundamentals.

What I mean by “AI readiness”

When I say “AI readiness,” I’m talking about building a site so that:

Content reuse: Your content is easy to parse and reuse (without losing meaning).

Unambiguous pages: Your pages are unambiguous (so they don’t get summarized incorrectly).

Consistent structure: Your structure is consistent (so both search engines and AI tools can infer relationships).

Stable foundation: Your technical foundation is stable (so you’re not leaking authority through duplicates, broken redirects, slow pages, or messy metadata).

In practice, “AI readiness” looks a lot like disciplined web development plus disciplined content strategy.

It’s also very aligned with what I already do: performance, accessibility, SEO, information architecture, content modeling, and maintenance.

The projects that taught me this (and keep teaching me)

1) Large WordPress builds: AI doesn’t fix a messy system

A lot of people think of WordPress as “simple.” At scale, it’s not simple — it’s operational. The job isn’t “build a website,” it’s “keep a website running.” That means stable patterns, editor-friendly tooling, and tight control over how content is created and displayed.

On projects like a high‑publishing news organization, I’ve built systems of custom blocks and templates so editors can publish quickly without the site turning into a one-off snowflake every time someone needs a new layout. That’s not just a UX win for humans — it’s also a machine-readability win. Consistent patterns make content more predictable to extract, summarize, and cite.

If your content model is coherent, AI tools have a fighting chance of representing it accurately. If it’s a pile of ad-hoc layouts and mystery fields, you get garbage out.

2) Migrations and redirects: structure is the difference between continuity and chaos

One of the fastest ways to destroy trust (with users and machines) is a migration done without discipline.

I’ve worked on migrations where the real work wasn’t the visual redesign — it was preserving continuity: URL mappings, redirect strategy, canonicalization, and making sure the “meaning” of the site survives the move.

From an AI readiness perspective, migrations matter because AI systems learn from what’s stable and consistent. If every important page changes URL, titles drift, and internal links break, you’re teaching every downstream system that your site is unreliable.

3) SEO and analytics work: AI readiness is measurable

On my SEO engagements, the work is a mix of strategy and housekeeping: site health, indexing, canonical cleanup, and building pages that match real search intent.

For one local service business I support, the year-over-year numbers are a good reminder that fundamentals compound: organic clicks up strongly, visibility climbing, and branded searches sitting at the top where they should. That’s not “AI” yet, but it’s the same underlying story: clarity wins.

If you want to be cited accurately — by Google, by an AI answer engine, by a voice assistant, by whatever comes next — you have to give the web a clean signal.

What I actually do when I’m making a site “AI ready”

This is where I get practical. AI readiness is not a single checklist item, but there are clear patterns.

Clear information architecture

If the navigation, page hierarchy, and internal linking don’t make sense to a new human visitor, they won’t make sense to an AI system either.

I look for:

Missing hubs: Pages that should exist but don’t (missing “hub” pages).

Page cannibalization: Multiple pages competing to say the same thing.

Buried priorities: Important pages that are buried.

Label drift: Inconsistent labels (“Services” vs “What We Do” vs “How We Help”) that create ambiguity.

Content modeling and consistency

When a site has repeatable content — people, locations, programs, events, articles — I model it as structured content, not as a pile of handcrafted pages. That’s how you get consistency without killing flexibility.

In WordPress that often means custom post types, structured fields, and a controlled set of templates or blocks.

Metadata that matches reality

Titles, descriptions, canonical tags, open graph metadata, and structured data should align with the actual content.

I’m especially picky about:

One canonical version: No silent http/https or www/non‑www duplication.

Clean sitemaps: Sitemaps that reflect what you want indexed (and don’t accidentally surface thin pages).

Less SEO noise: Avoiding low-value archives when they don’t serve a real purpose.

Accessibility and performance (still)

This part is non-negotiable. A slow, inaccessible site is a bad user experience and a bad signal.

But it’s also part of AI readiness because:

Crawl reliability: Fast pages get crawled more reliably.

Cleaner markup: Accessible markup is often cleaner markup.

Extractable structure: Clear headings and semantics make content easier to extract without distortion.

The part people skip: AI readiness is about trust

The best way I can say this is: AI is going to summarize you whether you like it or not.

So the question becomes: are you giving it something accurate to summarize?

If you want AI systems (and the humans using them) to understand what you do, you need a site that’s explicit and consistent about:

Identity: What the organization is.

Offer: What services/products exist.

Scope: Where you operate.

Freshness: What’s current vs archival.

Authority: What’s authoritative vs incidental.

That’s not hype. That’s just good web craft — and it’s the kind of work I’ve been doing for a long time.

If you’re wondering where to start

Start with the fundamentals:

Structure: Make your site structurally coherent.

Repeatability: Make your content model repeatable.

Correctness: Make your metadata and technical SEO boring and correct.

Definition of done: Make performance and accessibility part of “done.”

AI readiness isn’t a separate project. It’s what falls out of building the right foundation — and then maintaining it.

If that sounds “unsexy,” good. The unsexy stuff is what holds up under pressure.