Does B2B SEO Still Make Sense After ChatGPT? SEO, GEO and AI Search

Does SEO still make sense for B2B companies now that people increasingly use ChatGPT, Gemini and AI-generated search results instead of clicking through to websites?

Yes.

But the reason for investing in SEO is changing.

For years, one of the main arguments for SEO was relatively simple: create useful content, rank for relevant searches, generate organic traffic, convert part of that traffic.

AI search changes the middle of that equation.

A company can create useful content, rank well and provide information that gets used in an AI-generated answer without necessarily receiving the website visit.

At the same time, AI search creates another opportunity that can be extremely valuable for B2B companies:

Being recommended as the solution.

For us, these are two very different effects of AI search, and B2B companies need to think about both.

AI creates two very different outcomes for B2B SEO

The easiest way to think about the change is to separate AI searches into two broad groups.

The first can reduce the traffic companies historically received from SEO. The second creates a new kind of commercially valuable visibility.

That distinction matters much more to us than simply asking whether AI is “good” or “bad” for SEO.

1. Informational AI searches can take traffic away from SEO

Imagine somebody wants to know how a B2B SaaS company should structure its Google Ads account.

Historically, they might search Google, see a list of organic results, click an article and read the answer there.

Now they can ask the same question in ChatGPT or Gemini. Google itself can also provide an AI-generated answer directly in the search results.

The person gets the information. But they don't necessarily visit the website that originally provided it.

This creates a strange situation for companies that have historically generated substantial organic traffic through know-how content.

Their content can still be useful. It can still rank. It can still provide information that gets used in an answer. But the website doesn't necessarily receive the visit.

In other words:

Your content can contribute to more answers while generating fewer clicks.

For B2B companies that spent years building large educational content libraries, this changes the traditional SEO calculation.

Ranking doesn't necessarily mean traffic anymore

Historically, the connection was relatively direct. If your content became more visible, you expected more traffic. If you ranked higher, more people clicked.

AI-generated answers weaken that connection. An LLM can use the relevant part of a page and give the user what they need without requiring another click.

This is particularly relevant for informational content. If someone asks what demand generation is, they might be perfectly satisfied with the answer generated by the AI. They don't necessarily need to read another 2,000-word article about it.

That means companies can continue investing heavily in know-how content while seeing the organic traffic from that content decline.

This doesn't necessarily mean the content has become useless. It means traffic is no longer the only way that content can have an effect.

2. Recommendation searches work very differently

Now consider a different kind of question:

• Which B2B agencies specialize in Google Ads?
• What are the best CRM tools for a mid-sized B2B company?
• Which project management software would you recommend for a manufacturing company?

The AI isn't simply explaining something anymore. It's filtering potential solutions.

For a B2B company, being included in that answer can be extremely valuable. And this kind of visibility works differently from ranking organically for a traditional keyword.

An AI recommendation can behave more like an expert recommendation

Imagine your company ranks sixth for a commercially relevant Google search. The user sees ads, organic results and other search features. Then they decide which company they want to investigate.

An AI recommendation can feel different. The system might give the user a shorter list and explain why particular companies could be relevant.

That can behave more like asking somebody:

“Do you know a good provider for this?”

It can feel closer to receiving a recommendation from an expert, somebody on LinkedIn or a friend. That potentially makes the recommendation commercially powerful.

The amount of traffic coming from these searches might be lower than the informational organic traffic companies were used to. But the traffic can arrive in a different way.

The person didn't simply discover your website. Your company was recommended as a possible answer to their problem.

Less traffic doesn't necessarily mean less commercial value

This is why we'd be careful about evaluating the effect of AI search purely through website traffic.

Suppose historically you received substantial traffic from searches such as “what is B2B demand generation?” Some of that traffic disappears because people now get the answer directly from an AI.

At the same time, your company starts appearing when someone asks which B2B demand generation agencies they should consider.

You might receive fewer visits overall. But the second interaction is much closer to a commercial decision.

This doesn't mean that recommendation visibility will automatically compensate for lost informational traffic. It means the two types of visibility have to be evaluated differently.

For B2B companies, the objective increasingly shouldn't be simply to generate as much organic traffic as possible. It should be to be visible for the searches and recommendations that matter commercially.

SEO and GEO aren't exactly the same thing

We wouldn't treat GEO as simply a new name for SEO.

There is overlap. Similar to SEO, AI recommendations can depend on a combination of on-page and off-page signals.

But an AI recommendation isn't simply the equivalent of ranking number one for one keyword. The AI is trying to answer a question. That changes how we need to think about the information available on the website.

Traditional SEO asks: which keywords do we want to rank for?

For GEO, we'd add: for which questions do we want our company to be part of the answer?

That's a meaningful difference.

The goal is to become an answer, not just rank for a keyword

For a B2B company, those questions might be:

• Which software is best for this use case?
• Which agencies specialize in this market?
• What companies can solve this problem?
• What are the alternatives to this competitor?
• Which providers have experience with companies like mine?

There may not be large traditional keyword volumes attached to every exact question. But that doesn't necessarily make them commercially unimportant.

If a qualified buyer asks one of those questions and your company is included in the answer, that's valuable visibility.

This is one of the reasons GEO makes us think more about commercial relevance and less about traffic volume alone.

GEO changes how some pages need to communicate

There are also practical changes in how we think about content. Machines consume information differently, which means some elements of a page increasingly have a second audience beyond the human reader.

A clear TL;DR or summary section can make the main answer explicit rather than burying it somewhere inside a long article. Clear answer-oriented sections can make the information easier to identify. An author page can make explicit who is behind the content.

And some of the information on a page may exist partly because we want machines to understand the content and its context, not because every human reader needs to consume every element.

This doesn't mean filling a website with text written for robots. It means making important information explicit.

If the answer is buried somewhere inside several thousand words, that's not particularly useful for either a human or a machine.

Generic content has a different problem

Take the question: should a B2B company invest in SEO or paid ads first?

We could answer: “it depends on your goals — SEO is a long-term strategy, while paid advertising can generate immediate traffic.”

That's technically an answer. But there are thousands of versions of essentially the same answer already.

Our actual answer is more specific:

If we have to choose, we'd start with paid ads in more than 90% of the B2B cases we see.

Then we can explain the variables behind that conclusion: market maturity, actual available traffic, customer value and budget. We can say that with a €2,000–€3,000 total monthly budget, we'd usually put it into paid first.

Those are actual positions based on how we approach accounts.

The important distinction isn't simply “write unique content because Google likes unique content.” It's that generic content gives both people and machines very little additional information.

If you're saying exactly what everybody else already says, there isn't much new information to take from you.

GEO makes low-volume commercial questions more interesting

Traditional SEO strategies often start with search volume. A keyword with 5,000 searches looks more attractive than one with 50.

For GEO, that calculation can be different. Consider: “which B2B marketing agencies have experience scaling SaaS companies across Europe?”

There might not be large traditional search volume attached to that exact sentence. But if a qualified buyer asks it and an AI recommends your company, the interaction could be highly valuable.

That means a low-volume question can still be strategically important.

Again, the goal isn't maximum traffic. It's showing up in the right answer at the right time.

Paid ads can't currently replace this kind of visibility

This is also why SEO and GEO matter even to companies that primarily rely on paid acquisition.

With Google Search, if we want to show up for a commercially relevant query tomorrow, we can often pay to do it.

With AI recommendations, we generally don't have the same option. A Google Ads campaign doesn't simply make your company appear as an organic recommendation in ChatGPT or Gemini.

So a company can be highly visible through paid search while being largely absent when a buyer asks an AI system for recommendations.

That's one reason we'd be careful about choosing only paid acquisition and ignoring organic and GEO visibility entirely. They increasingly do different jobs.

SEO still matters because traditional search hasn't disappeared

None of this means Google Search is gone. People still search. Commercial searches still happen. Organic rankings still matter. Paid search still captures existing demand.

The change is that part of the informational journey can now happen inside AI-generated interfaces without producing a website visit. At the same time, AI systems have become another place where potential buyers can discover and evaluate companies.

So we'd be cautious about responding to AI search by abandoning SEO. Instead, we'd change what we expect SEO and content to achieve.

What should B2B companies optimize for now?

We'd start with two different questions.

For traditional search

Which commercially relevant searches do we want to rank for?

For GEO

For which commercially relevant questions do we want our company to be part of the answer?

Then we'd look at whether the company has information that can actually support those positions.

That can mean landing pages. It can mean comparison content. It can mean expert articles. It can mean clear summaries and answer-oriented sections. And it can mean making the person behind the expertise explicit through author information.

The point isn't to produce more content simply because an SEO tool found another keyword. It's to make sure useful information exists around the questions where being visible could actually matter.

So, does B2B SEO still make sense after ChatGPT?

Yes. But the investment thesis is changing.

Informational SEO is under pressure because AI can answer questions without sending the user to the source. That means companies can produce useful content and still see less organic traffic from it.

Recommendation searches are different. When somebody asks an AI system which company, software or provider they should consider, being included can put your company directly into the consideration set.

So we'd increasingly think about B2B search visibility in two ways: can we be found when somebody searches, and can we be recommended when somebody asks?

The metric can't be traffic alone. The more useful question is: when a potential customer asks Google, ChatGPT or Gemini a question that could lead them toward our category or our company, are we part of the answer?

That is increasingly what B2B SEO and GEO have to achieve.

The budget side of this decision is covered in B2B SEO vs. paid ads: budget, costs and ROI, and the sequencing argument in why we usually run Google Ads before investing in SEO. If you want to know whether your paid search is currently buying the right searches, a B2B Google Ads audit costs €450 per account, with a written assessment and a prioritized action plan within 14 days.

One caution before judging either channel on its reported numbers: B2B SEO vs. PPC attribution is often misleading, and the channel choice itself is easier with the SEO, Google Ads or paid social demand framework. As a B2B advertising agency we run B2B Google Ads and B2B LinkedIn Ads alongside this kind of organic and AI visibility work. More in our B2B strategy articles.