Every pitch in this category sounds similar right now, which makes evaluation harder than it was three years ago. The claims are usually true in some form. The question is whether they mean anything for your situation. Below are four things you will almost certainly hear from an ai seo company, along with a way to test each one before you sign.
“Search Has Changed, So Your Approach Needs To”
Broadly accurate. Buyers do increasingly read a synthesized answer before visiting any website, and that shifts what content needs to do.
The overreach is in the conclusion. It does not follow that your existing work is obsolete. Crawlability, topical depth, and accuracy still determine whether anything gets cited at all. Notionmind’s own framing describes AI SEO as making traditional practice faster and more data driven rather than replacing it, which is the more defensible position.
How to test it: ask what they would keep from your current setup. A useful answer names specific existing assets worth building on. A weak answer implies starting over, which usually means they have not looked at your site closely enough to find anything worth keeping.
“We Use AI to Find Opportunities You Are Missing”
This one is checkable in the first conversation, which makes it the most useful claim to probe.
Real intent work goes past search volume. People ask assistants longer, more specific, more conversational questions, and they ask follow ups, so the meaningful unit is a cluster of related questions rather than a single term. Notionmind lists intent analysis and competitor SERP analysis as separate capabilities, aimed at understanding why particular content is currently surfacing rather than only what is being searched.
How to test it: before the call, write down the five questions your buyers actually ask you. Then ask the prospective partner what they found when they researched your space. If their list matches your five, they did the work. If it is generic keyword output, the AI is doing volume research with a new label.
You can also run the cheap version yourself. Ask an assistant your buyer questions, note which sources it draws on, and look for what those sources have structurally in common.
“We Will Get You Cited in AI Answers”
Here the honest answer is more limited than the pitch usually is.
Content can be structured to be more citable. Direct answers near the top of a section, claims stated in self contained sentences that survive being quoted alone, specific figures and named entities instead of general assertions. All of that helps and none of it hurts human readers, which is a good sign it is durable.
What cannot be promised is placement. There is no equivalent of a rank tracker with reliable coverage, and self reporting from assistants about their own sources is inconsistent.
How to test it: ask how they will measure it. Acceptable answers involve a repeatable manual check against your core buyer questions on a set schedule, plus movement in branded and direct search volume. Any answer implying guaranteed inclusion or a proprietary tracking metric deserves scrutiny.
“Results Take Time”
True, and also the most common cover for a lack of early progress. The distinction is whether anything measurable happens in the meantime.
Notionmind publishes a figure of roughly 3x faster movement from plan to execution and an average client partnership of 18 or more months. Both are self reported rather than independently audited. The second number is the more informative one for setting expectations, since this work compounds slowly and a single quarter rarely produces enough signal to judge fairly.
How to test it: ask what they expect to be measurably different at 30, 90, and 180 days. Structural work like consolidating competing pages and adding direct answers should show up early. Ranking and citation movement is reasonable to expect later. A partner who cannot separate those two timelines has not run enough of these engagements.
Signals Worth Weighing in Either Direction
Across the whole evaluation, some patterns are more diagnostic than the pitch itself.
Worth taking seriously: they ask what your sales team hears from buyers. They name existing content they would consolidate or retire rather than only what they would add. They separate what they can influence from what they can only observe. They tell you which of your target terms are not worth chasing.
Worth pausing on: deliverables measured in article count. Reporting that leads with impressions. Reluctance to explain what changed in a given month. Anything positioned as a complete replacement for the discipline rather than an addition to it.
That fourth item on the first list is the strongest single signal. Recommending against a keyword shrinks their own scope, and few firms do it without reason.
Where This Fits Alongside Everything Else You Are Buying
One connection most organizations miss: the structural work here overlaps with other AI work you may already be considering.
Clean entity definitions, consistent terminology, and content organized so machines can interpret it reliably serve both external visibility and internal systems. Notionmind’s writing on ai solutions for business makes a related argument about sequencing, that the teams seeing real gains solved two or three genuinely painful problems properly rather than running the most advanced setup.
The same logic applies to visibility work. Ten pages restructured well beats forty published thinly, and it is easier to attribute results afterward.
One practical step before any vendor conversation: pick your single most commercially important question, find the page that should own it, and check whether the first three sentences on that page actually answer it. Most sites fail that test on their highest value page, and fixing it costs nothing.