Your next customer brought an agent

Picture a buyer asking their assistant to compare three implementation partners. They care about integration experience, project scope, likely cost and whether the team can meet their deadline.

Now open your website. How many of those answers can they actually find?

“We deliver innovative solutions” has had a good run. It still won’t tell anyone whether you work with their CRM.

Shopify offers a concrete example of where AI-assisted buying is heading. The useful question reaches well beyond online stores.

What is available today

Shopify’s Shop MCP gives developers a connection that compatible AI agents can use to search products, build carts and complete Shop Pay checkout. For that payment flow, the shopper signs in and confirms the total and payment method before the agent completes the purchase.

That does not make every AI shopping experience identical. Shopify’s ChatGPT channel helps people discover products, then sends them to the merchant’s online-store checkout. Eligible stores can offer Shopify-powered direct checkout within Microsoft Copilot to US shoppers.

Shopify is one example of a wider shift. Stripe’s Link also supports consumer-approved purchases through personal AI agents. These are concrete consumer-shopping capabilities, not evidence that an assistant can purchase a bespoke consulting engagement.

Why this matters outside ecommerce

Our take: this is a useful prompt to review the information buyers use to compare you with alternatives, whatever platform runs your website.

For a service business, that might mean explaining what is included in a migration and what the client must provide. For software, it might mean listing supported integrations, plan limits and onboarding requirements.

The buyer still needs a reason to choose you. An assistant does not remove that job. If important answers live only in a salesperson’s explanation or a private proposal, they are not available to someone researching your public website.

We are not predicting when your platform will offer agent checkout. We are suggesting work that helps people evaluate your business now and gives assistants clearer public information to work with when they can access it.

Try this with one offer

Choose a core service or software product and a specific kind of customer. Use the questions your sales team already answers, rather than inventing a list of “AI keywords.”

1. Make fit and scope easy to judge

Could a buyer tell whether you solve their problem? Name the systems you support, the work included and the important exclusions. For an implementation service, separate configuration from migration, custom development and ongoing support. For software, explain which features require a particular plan.

Check that the service page, relevant FAQs and downloadable overview agree. If one promises a full migration and another describes a basic setup, decide which is accurate before adding more copy.

2. Explain cost and timing honestly

Publish pricing where you can. If every engagement needs a quote, explain what determines the price and what information you need to estimate it. A credible starting range can help when you have one; do not invent a number to fill a gap.

The same applies to timing. Describe a typical process and the dependencies that affect it. “Launch in four weeks” needs context if that assumes clean data, available stakeholders and no custom integration.

3. Give the buyer something to verify

Replace broad promises with relevant evidence. A case study should explain the starting problem, what changed and which results you can substantiate. Make the date, scope and important conditions clear.

Keep the next step equally specific. If the button says “Book a consultation,” explain what that conversation covers and what the buyer should bring. Someone comparing providers should not have to guess whether they are requesting a demo, a quote or a sales call.

4. Check the answers against the actual pages

Ask someone unfamiliar with the offer to answer those questions using your public pages. You can also test an assistant with the same public brief and ask for source links. Verify its answers against the originals; a confident summary is not a correctness check.

Separate missing or contradictory information from a tool simply failing to find it. Fix the content problems you can demonstrate, then repeat the check. You do not need to expose private proposals, customer records or internal pricing to do this.

Keep the website useful

This exercise will not guarantee an AI recommendation or establish a revenue lift. Its first result should be a short, specific list of questions your website does not answer well.

Pick the most important gaps, assign an owner and make sure the revised pages agree with what your team actually sells. Keep the design, navigation and human buying experience in the brief too.

Shopify makes the direction easier to picture. You do not have to sell suitcases, use its platform or wait for your own vendor’s announcement to make your website more useful.

Your next customer might send an AI agent. Give them both something better than “innovative solutions.”