Ask for named platforms, a page-level work plan, a documented baseline, and a way to review business outcomes. Judge the work by what changes and what the evidence supports.
An agency sends you a proposal to make your business visible in AI answers. It promises optimization, authority, and a dashboard. Before deciding whether the work is worth buying, you need a more practical answer: what will someone actually do to your website, and how will you judge the result?
AI search can be a reasonable topic for your marketing plan. The proposal still needs the same discipline as any other business investment. Use these questions to turn a broad sales pitch into a scope you can understand, compare, and hold someone accountable for.
1. Which platforms does the proposal cover?
Ask the provider to name the search products it intends to evaluate. “AI visibility” is too broad to define a project. A review of Google Search’s AI features is a specific scope. A claim about every assistant and answer engine needs a separate explanation of what is being checked in each one.
Google’s current guidance says its usual SEO practices remain relevant to AI Overviews and AI Mode, with no additional requirements or special optimizations needed. Supporting pages must be indexed and eligible for a search snippet. Google also says inclusion is not guaranteed and does not require a special AI text file or special structured data. The official documentation is linked below.
Use that guidance to ask questions about the proposed work. If a deliverable is described as mandatory for Google’s AI features, ask where Google documents that requirement. If the recommendation concerns another platform, ask for that platform’s evidence. A broad label should not replace a specific explanation.
2. What will change on which pages?
Request a list of the pages being assessed and examples of the changes the provider expects to make. A useful scope might identify unclear service information, outdated comparisons, weak supporting evidence, or a page that does not answer a customer’s buying question. Each proposed change should have a reason and an owner.
For an illustrative remodeling business, a provider might recommend improving a kitchen project page with the work included, decisions that affect scope, an explanation of the estimate process, and approved photographs. That gives the business something concrete to review. An instruction to publish large numbers of generic articles leaves much more unanswered.
Google’s people-first content guidance asks creators to assess originality, usefulness, completeness, and the evidence behind expertise. Our practical recommendation is to ask how the proposed work will help a customer make a decision. Review a sample before approving a batch, and confirm who checks technical accuracy and business claims.
3. What does the starting evidence show?
Ask for a dated baseline and enough detail to reproduce the review. For a manual check, record the platform, question, date, and relevant context, then preserve the answer and any cited pages. Include questions that represent customers at different stages, such as understanding a service, comparing options, and preparing to contact a provider.
Treat those checks as observations from a defined test, rather than a complete measure of how everyone sees your business. Ask how the provider chose the questions, what a missing mention means in its report, and which limitations remain. A screenshot can document an observation; a conclusion about market-wide visibility requires more support.
Keep the starting question set available during the engagement. If the provider changes it, record why. Otherwise a report may look better simply because the questions became easier or moved toward topics where your business was already represented.
4. How will the report support a business decision?
Agree on what the project is intended to improve. A local service company might want clearer discovery for a particular service and more relevant inquiries. A software business might want a better explanation of its product in buying comparisons. Those goals call for different content and different conversations about success.
Ask the provider to show completed work alongside the observations and business data it can actually support. Review relevant visits, qualified inquiries, and customer questions where information is available. Keep missing attribution visible. An inquiry should not be assigned to an AI interaction simply because the project is about AI search.
Decide what would make you continue, revise, or stop the engagement. A sensible review may find that a page needs better evidence, the offer needs clarification, or the measurement method needs improvement. A dashboard should help you choose that next action.
5. Who owns the work and reviews the result?
Confirm who approves copy, implements changes, checks the live pages, and maintains any reporting accounts. Ask what your business receives if the engagement ends: edited content, change records, access to the reporting you paid for, and a clear list of unfinished work.
Start with a bounded scope you can inspect. Agree on the pages, deliverables, review points, and evidence before expanding. Evaluate a guarantee against the part of the outcome the provider can control; a promise to complete agreed work is different from a promise that a third-party system will cite you.
At NextGenTech, we help businesses connect search strategy, useful content, and website improvements to practical goals. If you are considering an AI search proposal, bring us the scope and the customer questions you want to address. We can help identify the useful work, clarify the assumptions, and define a plan your team can evaluate.