GEO vs SEO: do you need a new agency or the same one?

The question I hear most from marketing leaders right now is not "what is GEO". It is "do I need to hire someone new for it, or can my current SEO agency handle this". It is a budget question dressed as a technical one, and the honest answer will save some of you a second vendor you do not need.

GEO and SEO share most of their technical foundation, so in most cases you do not need a separate agency or team for AI search. What you need is a provider who measures the right outcome and has reprioritised the work for it. You should bring in a specialist only in specific circumstances: when your current provider cannot show you a method for measuring AI visibility, or when they treat AI search as a separate product to upsell rather than a shift in the work they already do. This article is about telling those situations apart, so you can make the call rather than be sold one.

Why this feels like a decision at all

Part of the reason this feels like a fork in the road is that the market has an incentive to make it one.

"Generative engine optimization" and "answer engine optimization" are useful terms, and they are also useful things to sell. A new acronym creates a reason to pitch a new service, a new retainer, and a new line item, and plenty of providers have reframed AI search as a distinct discipline for exactly that reason. If the difference between GEO and SEO is genuinely a new discipline, you need a new specialist. If it is a shift in emphasis within a discipline you already pay for, you do not. A lot of marketing spend rides on which of those framings you accept, which is why it is worth reasoning it out rather than taking anyone's word, including mine.

What GEO and SEO actually share

Start with the overlap, because it is most of the picture.

The work that earns you a ranking and the work that earns you a citation in an AI answer are, at the foundation, the same work. Content a search engine can crawl and render is content an AI crawler can crawl and render. A page structured so a search engine understands it is a page a language model can extract from. An entity that is clear and consistent across the web is easier for both a search index and a model to place. Authority earned through genuine third-party references helps you rank and helps you get cited. I have set out how the terms relate and where they genuinely diverge in AEO, GEO, and SEO: what the terms actually mean, and the short version is that they are one discipline with a broader definition of where visibility happens, not three disciplines competing for your budget.

This is why "SEO is dead" is incoherent. For any answer an assistant builds by browsing the live web, conventional search visibility is the entry requirement, because that is where the model draws its candidate pages from. The foundation did not get replaced. It got more important, and it got a second output.

Where they genuinely differ

The differences are real, but they are narrower than the marketing suggests, and they are about outcome and emphasis rather than about a separate skill set.

The outcome you measure changes. Classic SEO measures rankings and the traffic they produce. AI search measures whether you are found, described accurately, and cited across the assistants your buyers use, which is a different thing to instrument and a different thing to report. A provider set up only to report ranking positions is measuring the wrong outcome for this, not because they lack a skill, but because they have not changed what they look at.

The priorities shift. Some work that was a nice-to-have for ranking is now load-bearing for citation: server-side rendering so your content is actually present for a crawler, entity consistency so a model knows who you are, and answer-first structure so there is a passage to extract. The tasks are familiar. Their order of importance has moved. That reprioritisation, not a new toolkit, is what "doing GEO" actually consists of for most sites.

The real question: can your current provider do it?

So the useful question is not "GEO or SEO". It is "is my current provider measuring the right outcome and prioritising for it". There are clear signs either way.

Signs they can handle it: they already talk about how you appear in AI answers, not just where you rank. They can describe how they measure it. They treat AI search as an evolution of your existing programme rather than a bolt-on. And when your traffic behaves oddly, such as rankings holding while clicks fall, they reach for the right explanation rather than a puzzled shrug, a pattern I have written about in why your organic traffic is falling while your rankings hold.

Signs they cannot, yet: they report only rankings and organic sessions and have no view of AI answers at all. They describe AI search vaguely, or with a certainty about "the algorithm" that no one honest has. Or, most tellingly, they respond to your question by producing a brand-new product to sell you, priced separately, rather than folding the work into what they already do. That last one is worth pausing on, because it is common and it is expensive.

What to ask your current provider

You do not need to become an expert to assess this. You need a few direct questions and the confidence to notice a non-answer.

Ask how they measure your visibility in AI answers today. A capable provider will describe a method: a set of prompts, the surfaces they test, how many times they run each, and how they handle the fact that these systems give different answers each time. Vagueness here is the tell.

Ask which of your pages, if any, are currently being cited by assistants, and how they know. This separates providers who are actually looking from providers who are guessing.

Ask what they would change first, and why. A good answer is sequenced and reasoned: fix retrieval before extraction, because a page that cannot be reached cannot be cited. A weak answer is a list of tactics with no order.

And ask, plainly, whether this is included in your current scope or a new charge. The answer tells you whether they see it as part of their job or a chance to expand the account.

One more question separates the adaptable from the stuck: ask what they have changed in the past year in response to AI search. A provider who has genuinely adapted can point to specific shifts in how they work and what they report. A provider who has changed nothing, yet is now offering to sell you a GEO package, is repackaging rather than adapting, and you are being asked to fund the relabelling.

When you genuinely need a specialist

Sometimes the answer is yes, bring in someone new, and it is worth being honest about when.

You need outside help when your current provider fails the questions above and shows no sign of adapting, because you cannot wait for a team to learn a shift they do not acknowledge is happening. You need it when you have no in-house measurement capability and want an independent baseline, uncoloured by the incentives of whoever does your delivery. And you need it when you are making a high-stakes change, a migration or a repositioning, and want the visibility risk assessed by someone whose only job is to assess it.

Even then, "specialist" often means a diagnosis engagement rather than a permanent second agency. You bring in measurement and strategy, get a clear read on what is wrong and in what order to fix it, and hand the delivery back to your existing team with a plan they can execute. That is a very different, and usually smaller, commitment than retaining a whole second vendor in parallel, and I have set out how that diagnosis-versus-delivery split works in answer engine optimization services: what to look for.

The trap to avoid

The expensive mistake in this category is buying a second vendor to do work your first vendor should be doing, and paying twice for one discipline as a result.

It happens because the new-acronym framing is persuasive and because doing something feels safer than asking hard questions of an incumbent. But two providers working the same foundation with different labels tends to produce duplicated effort, conflicting advice, and a muddle over who owns the outcome. In most cases the better move is to hold your existing provider to the higher standard, give them the questions above, and either watch them rise to it or replace them, rather than layering a second retainer on top of the first.

What this looks like for an in-house team

Not everyone reading this has an agency. Plenty of marketing leaders have an in-house SEO function and are asking whether they need to add an AI search specialist on top of it. The reasoning is the same, with one adjustment.

An in-house team has an advantage an agency does not: proximity. They know your site, your buyers, and your history, and the reprioritisation that AI search requires is often easier for them to absorb than for an outside vendor splitting attention across many clients. What they usually lack is not skill but an independent baseline and the time to build the measurement discipline from scratch. So the specialist you bring in is frequently not a permanent hire but a diagnosis engagement: someone who establishes the measurement, hands your team a clear read on which gaps matter, and shows them how to keep running it. You buy the outside rigour once, and the ongoing work stays in-house where the proximity is.

The failure mode for in-house teams is different from the agency one. It is not overpaying for a second vendor. It is assuming that because the team is busy and competent, the measurement must be happening, when in fact no one has ever run a fixed prompt set or captured a baseline. Ask your own team the same questions you would ask an agency. If the answers are vague, the gap is measurement, not talent.

The cost of getting the decision wrong

It is worth naming what each wrong answer costs, because the two errors are not symmetrical.

Bringing in a second vendor you did not need costs money and creates confusion: duplicated work, conflicting advice, and no clear owner of the outcome. It is expensive, but it is visible, and you can unwind it. Failing to adapt when you should have is quieter and usually more costly. A provider who keeps reporting rankings while your citations erode hands you a dashboard that looks fine while the actual outcome, whether buyers find you in AI answers, gets worse unmeasured. By the time the effect reaches your pipeline, you have lost quarters you cannot recover, and a competitor has consolidated the citations you were not watching.

That asymmetry argues for measuring first and deciding second. A single diagnosis tells you whether you have a real gap and whether your current provider can close it, and it costs a fraction of either wrong answer. You are not really choosing between GEO and SEO. You are choosing whether to make the decision with evidence or without it.

The takeaway

GEO and SEO are one discipline with a broader definition of where visibility happens, not two disciplines needing two teams. The decision is not "GEO or SEO". It is whether your current provider measures the right outcome and has reprioritised for it. Ask them how they measure AI visibility, what they would fix first, and whether it is in scope. Bring in a specialist when they cannot answer, and even then, prefer an independent diagnosis over a permanent second vendor.

If what you want is that independent read, a measured baseline and a clear diagnosis you can hand to whoever does your delivery, that is what an AI search visibility audit is for.

This article is part of the SEO in the AI Era: The Complete Guide guide.