A 90-day agent readiness plan for e-commerce teams

Agent readiness can feel like a long list of unrelated fixes. It's easier to run as three phases of about a month each: let AI agents in, help them understand and move around your site, then prove they can finish the jobs that make you money. Here's a plan an e-commerce team can start on Monday.

Before you start

Name one person to own the plan. It doesn't have to be a developer; on most teams it's someone in e-commerce, digital or SEO who can get time from the people who make the changes. Our post on who owns agent readiness shows who usually fixes what.

Then agree what "done" means. We suggest three outcomes by day 90:

• No critical AgentScore findings on your home page and key product pages.
• At least one money journey, such as product to checkout, tested by a real AI agent on a schedule.
• A monthly view of agent traffic and AI referrals that leadership can read.

Notice that none of these is a target score. Scores are useful for tracking progress, but a site that loses ten points to an optional new standard can still serve agents well, and a site that scores well can still fail at the size selector. Aim at the outcomes.

Days 1–30: let agents in and get a baseline

The first month is about Access, because nothing else matters if agents are turned away at the door. It's also when you set the baseline you'll measure against.

Week 1: measure

1. Run AgentScore on your home page and save the report. How AgentScore works explains what's behind each category.
2. Connect a data source, such as your CDN or server logs, so you can see which AI agents visit and how your site answers them. See how to measure agent traffic.
3. List your three most valuable journeys: for most stores, search to product, product to cart, and cart to checkout.

Weeks 2–4: fix Access

AgentScore check	Usually fixed by	Read
robots.txt lets AI assistants and search agents in	SEO or content team	robots.txt for AI agents
Bot protection lets AI agents through	Bot protection or CDN admin	Tell if an AI crawler is real
No CAPTCHA or challenge on arrival	Bot protection or CDN admin	Bot protection and CAPTCHAs
AI agents can open your product, pricing and cart pages	Bot protection or CDN admin	Rate limits for AI agents
llms.txt guide for AI	SEO or content team	How to write an llms.txt file

Make one policy decision this month too: what you'll do about AI training crawlers, as distinct from the assistants that fetch pages for shoppers. Our decision guide walks through it. Settle it early, because it affects robots.txt and bot protection rules at the same time.

Days 31–60: make pages readable and usable

Month two covers Readability and Navigability: whether agents can understand your pages, and whether they can find their way around them. Most of this is developer work, so get it into the sprint plan early in the month.

Readability

• Content loads without JavaScript and Prices are in the page HTML. The highest-value fixes for most stores. See JavaScript-only content and prices AI agents can read.
• Structured data and product pages give price and stock in a form agents can read. See product data AI shopping agents can read.
• Clear page title, description, and headings, image text descriptions and a valid sitemap. Usually SEO and content work. See titles, descriptions and headings, alt text for AI agents and XML sitemaps.
• Policy pages for shipping and returns that an assistant can quote accurately. See shipping, returns and FAQ pages.

Navigability

• Buttons and links have names, form fields are labelled and clickable things are real buttons and links. See buttons, links and forms agents can use. If you have an accessibility audit, start there: much of it overlaps.
• Pop-ups and banners can be dismissed by agents. See cookie banners and pop-ups.
• Main and navigation landmarks and key pages linked from the home page. See link your key pages from the home page.
• Site search and filters that agents can operate. See site search and filters AI agents can use.

Days 61–90: prove agents can finish the job

Month three is about Task completion, the category that carries the most weight. Checks can tell you a page looks usable. Only a real agent can tell you whether it is.

1. Test your money journeys. Set up Ghost Agent tests for the journeys you listed in week one, starting with product to checkout. Each check runs the agent several times, because agents vary, and Ghost Agents stop before paying. See how to test your key journeys with AI agents.
2. Fix where they fail. The usual sticking points are the add-to-cart button, option selectors, checkout fields and a challenge at the cart. The relevant checks are Agents can find and press your add-to-cart or sign-up button, Cart and checkout fields are labelled for agents, and AI agents aren't blocked or shown a CAPTCHA at the cart and checkout. See agent-ready checkout.
3. Review guest checkout. An agent buying for someone can't easily create an account for them. See guest checkout: why AI shopping agents need it.
4. Look ahead. Ask your platform and developers where you stand on MCP and WebMCP and on agentic commerce protocols. These are early and still changing, so they're weighted lightly in AgentScore. A decision and a plan are enough for now.
5. Set up reporting. Track the visits and sales AI assistants send you, alongside agent traffic from your logs. See tracking visits and sales that come from AI assistants.

After day 90

Agent readiness drifts. A new pop-up campaign, a bot protection rule change or a redesigned product page can undo months of work in one release. Keep three habits:

• Rescan after every significant release, and at least monthly.
• Keep Ghost Agent tests running on your money journeys, and add one when you launch a new one.
• Add agent checks to your definition of done: named controls, labelled fields, prices in the HTML, and no new challenge pages on key paths.

Start with a scan. It takes under a minute, and it'll tell you which month of this plan needs the most attention.