Name the operation rather than the ambition
An AI service page becomes useful when a buyer can tell what happens to an input. Replace a broad promise such as “automate your business” with a description of the actual operation: classify incoming requests, draft a response, summarize approved documents or suggest a next action. Each operation has a different boundary and needs different evidence.
Prepare a capability record before writing the page. For each service, list its input, output, supported conditions, current delivery status and the person responsible for checking the result. Separate a working feature from a planned integration or a demonstration. A roadmap item should not appear beside live capabilities without a visible qualification.
Show where a person makes the decision
Describe the handoff between the system and the reviewer. Does the service produce a draft, place it in a queue, or execute an action after approval? State who can approve and what happens when approval is withheld. “Human oversight” is too vague if the buyer cannot identify the point where a person can stop or change an action.
Explain the fallback for unsuitable inputs and uncertain outputs. For example, the workflow might route an unrecognized request to a person instead of choosing a category automatically. Only describe that behavior if it exists in the offered service. The page should distinguish an intended safeguard from a tested capability and an implementation option requiring additional work.
Attach evidence to performance language
If you publish an accuracy or time-saving figure, retain the task definition, test sample, comparison method and review conditions behind it. An excellent result on a small curated demonstration does not establish performance on every customer’s documents. Where no representative measurement exists, describe the workflow benefit you intend to test rather than invent a percentage.
NIST describes its AI Risk Management Framework as voluntary guidance for incorporating trustworthiness considerations into AI design, development, use and evaluation. It can inform a team’s review questions, but citing it does not make a service certified or prove a particular result. Keep any reference to a framework separate from claims about what your own implementation has demonstrated.
Worked example: a draft assistant for enquiries
Illustrative example: a service reads a submitted enquiry and proposes a reply using approved service information. The operator checks the source material and edits the response before sending. A precise page description is “prepare reply drafts for staff review,” provided those steps reflect the actual offering. “Handle every customer conversation autonomously” describes a materially different service.
The demonstration should show a normal request and a request the workflow cannot answer from the available information. Label the records as sample data and show the handoff instead of fabricating a successful response. If sending is not part of the integration, say so near the example. These are hypothetical design choices, not claims about an existing customer deployment.
Review the page against the current product
Before publishing, ask the delivery owner to classify every capability statement as available, conditional or planned. Remove unsupported absolutes such as flawless, unlimited or fully autonomous. Check that screenshots, button labels and frequently asked questions describe the same level of automation, and identify dependencies such as customer-provided documents or a separately configured integration.
Repeat this review after a meaningful capability change. A useful service page helps a buyer understand what to evaluate during a trial and who remains responsible for acting on output. For SEO Growth Assistant, describe recommendations and content drafts with the review they need; do not turn a recommendation into a claim that the website has already been changed or that a ranking is assured.