Intro to AI Search: an Evidence-Based Primer for B2B Marketers
Table of Contents
AI search optimisation is still a new and fast-moving part of search marketing, and for B2B teams, this creates both opportunity and uncertainty. That’s why we’ve created this three-part series: to help you make sense of the AI Search landscape so you can seize the former and dispense with the latter.
In Part One of this series, , we’re covering the following:
- What AI search is and why it matters to your marketing strategy
- How AI search engines decide what pages to cite (and how that differs from search engines)
- AI search optimisation practices that don’t actually work
- What an AI Search audit is and why you should run one
If you’re confident you already know the basics and want to jump ahead to the AI Search Audit Framework or or DIY AI Search Audit Workbook, follow the trail to your left.
AI Search Optimisation 101: What Is It?
AI Search is the ongoing practice of optimising your website and online footprint to maximise visibility in AI search engines such as ChatGPT, Google AI Overviews, Perplexity, Claude, Gemini, and Copilot.
The building blocks of AI Search practices include:
- Topic research
- Content creation
- Technical optimisation
- Authority building
If all these things sound like off-brand variations of SEO, that’s because AI Search and SEO are closely related. Many people looking for a digestible definition of AI Search often call it the SEO of AI visibility. This is a great start, but you’ll soon find out why that definition is an oversimplification and slightly misleading.
To give you an example, the goals between these two marketing approaches are fundamentally different: for SEO, the goal is to get your page ranked on page one of Google. For AI Search, it’s to get your page cited or mentioned as a source when AI generates an answer.
Before we continue, you should also know:
AI Search Goes by Many Names
It seems like lexicographers haven’t been returning the world’s calls since AI shoved its way onto the scene, because a few years in, there still doesn’t seem to be any consensus on what to call this thing. Because of that, AI Search is also known as:
- Generative engine optimisation (GEO)
- Answer engine optimisation (AEO)
- Large language model optimisation (LLMO)
- AI optimisation (note we didn’t say AIO, because that stands for AI Overviews)
AI Search Is Still Very Young
Standard AI Search practices are not yet fully standardised. But Rome wasn’t built in a day. What we’re sharing with you now is as true and as accurate as we can make it at the time of writing. To keep it that way, we’ll be updating this guide as often as possible.
So, now that we’re all clear on what AI Search is, the most important follow-up question is…
Why Should B2B Marketers Care About AI Search?
Embracing AI Search practices means B2B marketers, such as yourself, can attract higher-quality AI-referral traffic and adapt to the changing landscape of online visibility, aka AI Overviews.
We fully recognise that much of the hype and frenzy surrounding AI Search is unfounded, especially if you look at the numbers and realise just how little traffic AI is actually responsible for. Google still sends 190x as much traffic to websites as ChatGPT, and ChatGPT accounts for just 0.21% of total site traffic. Traditional search still dominates in absolute traffic, but AI search is growing fast.
Here are other figures to consider:
- Google AI Overviews reach 2 billion monthly users and appear for 21% of all search queries. They process 276M prompts monthly, nearly 20 times as many as ChatGPT’s 14.5M.
- AI Overviews reduce position #1 CTR by 58%. When an AI summary appears, only 8% of users click a traditional link, down from 15%. Even ranking 10th results in a 19.4% loss of clicks.
- 28% of ChatGPT’s top 1,000 cited pages have zero Google organic visibility. A page can be invisible in traditional search but heavily cited by AI.
- AI-referred traffic converts at 14.2%, vs. Google organic at 2.8%. The average AI search visitor is worth 4 to 5 times as much as a traditional organic visitor.
- AI sessions jumped 527% year-on-year.
- Keyword stuffing actively harms AI Search performance by reducing AI visibility by 10% in controlled testing.
So, while we’re definitely not saying that you should pull the plug on your existing SEO efforts, we highly recommend that your marketing team consider adopting AI Search practices.
But first, you probably need to know what makes your page worth citing. If you can understand what drives this seemingly sentient decision-making, then you’re well on your way to mastering this intro course.
How Do AI Search Engines Decide Which Pages to Cite?
Rather than ranking pages, AI search engines synthesise answers from multiple sources before selecting which to cite and which to ignore.
The original AI Search paper, published by researchers from Princeton, Georgia Tech, and IIT Delhi, tested nine ways to make content more visible in AI-generated answers. They ran the experiments across 10,000 queries and checked the results in live Perplexity outputs.
The biggest takeaway was that AI systems respond better to content that includes clear, specific, verifiable information. Techniques like adding quotes, statistics, and source citations performed best.
One especially interesting finding was that “Cite Sources” had the greatest impact on lower-ranking pages, boosting visibility by 115% for pages that typically rank lower in traditional search results.
In other words, AI Search may help content that SEO already struggles to surface.
Here are the results, if you’re interested (visibility improvement vs. baseline):
The Nine Factors That Drive AI Citation
Drawing from the academic paper, platform-specific analyses, and large-scale citation studies, these are the factors that determine whether AI cites your content, ranked by impact:
Does Content Length Make a Difference?
Ahrefs analysed 174,000 pages cited in AI Overviews and found near-zero correlation between word count and being cited, a fact that kind of shocked our content writers. The average cited page is 1,282 words. 53.4% of cited pages were under 1,000 words. As the old saying goes, it’s quality over quantity.Does Misinformation Make a Difference?
To answer that question, Ahrefs ran a controlled experiment in which it created a fake luxury company, seeded three contradictory stories on external sites, and tested whether AI engines would pick them up over the official FAQ. Here’s what it found:- Gemini and Perplexity included the fake information 37–39% of the time
- ChatGPT-4 and Claude performed better, at under 7%
- One model hallucinated a “Black Friday campaign” that never existed
- Claude never hallucinated but also never surfaced the official website
AI Search “Tactics” That Don’t Actually Work
There’s a lot of AI Search advice floating around the internet. Some of it is overinflated, while some of it just isn’t backed by any substantial evidence. But some of it can actually even cause harm.
So the next time you’re tempted to test out these speculative or early-day AI Search tactics that you found on LinkedIn, resist them at all costs:
- Stuffing pages with keywords to game AI (not that anyone with basic digital marketing experience is still blowing this horn)
- Relying on llms.txt files as an AI Search shortcut
- Assuming homepage tweaks alone will move AI visibility
- Treating DR and backlinks as primary AI Search signals
- Applying the same AI Search tactics to every AI engine, as each engine has a fundamentally different citation and linking algorithm.
Let’s Compare AI Search vs. Traditional SEO
How They’re the Same
How They’re Different
Why AI Search Is More Important for AI Than SEO
As digital marketing approaches, SEO and AI Search have largely been treated as twins, but we should start thinking of them as sisters: related but recognisably different.
For example, here’s what sets AI Search apart from her older sister:
AI systems need to be able to lift a clear fact, quote, or statistic from your page. If the point is buried inside long, heavily descriptive paragraphs, it’s much less likely to be pulled into an answer, even if the page ranks well in search.
AI systems are more likely to cite content that includes concrete details such as statistics, named sources, and expert quotations. Those elements give the model something specific to trust and reuse.
Mentions across platforms like Trustpilot, Reddit, G2, Wikipedia, and industry directories can shape AI visibility even if they come from outside your own website. In other words, your broader online footprint should be taken into account.
Different AI engines favour different kinds of sources and content structures. What works well for Perplexity may not perform the same way in ChatGPT or Claude.
AI search results change over time, and even the same query can return different citations on different runs. This academic paper on measuring AI visibility recommends tracking rolling averages across 4–8 weekly observations.
An AI Search Audit Can Help You Discover Where You Stand
Now that you know what affects AI Search, the next step is to measure how your brand is actually performing against all those signals.
That’s where an AI Search audit comes in.
An AI Search audit gives you three things:
- Where you stand today: how visible your brand is across AI search engines and how that compares with competitors.
- What needs work: the gaps in your content, technical setup, authority signals, and overall readiness for AI visibility.
- What to do next: a prioritised action plan showing what to fix first, how much effort it will take, and what impact it should have.
What’s Included in Geeky Tech’s AI Search Audit
Because there are seven major dimensions of your brand’s AI visibility, the audit is divided into seven sections, each with its own audit and scoring rubric.
Designed as a diagnostic activity, our audit provides a complete picture of where you currently stand, including what needs improvement, how to address it, and what you should work on first.
Here’s an overview of each section:
How to Use Our AI Search Audit Framework
You can run this full AI Search audit in-house with our workbook and stack of third-party tools, or access your AI Visibility Audit on GeekyIQ, our AI brand intelligence platform.
If Your Team Is Running the Audit
You’ll need to assemble tools to track AI visibility, check Core Web Vitals, analyse search data, and check technical performance. The list of tools out there is pretty vast, but here are some suggestions:
- AI visibility tracking tools: Semrush, OpenLens, Otterly, or manual prompt testing
- Technical audit tools: Screaming Frog + Google Rich Results Test
- Performance and Core Web Vitals tools: PageSpeed Insights, CrUX, or your existing performance tooling.
- Analytics & search data tools: GA4 with a custom AI channel + Google Search Console
- Competitor analysis: Ahrefs or Semrush, plus manual checks on review sites and directories
Should You Perform Your Own AI Search Audit?
If you have the tools, time, and resources to act on your findings, yes, you should perform regular in-house AI Search audits. But it does require building and maintaining the process, which is a labour-intensive task and one that will likely need to be updated over time.
That’s why so many marketers work with AI search strategists to help manage these audits.
If You Prefer a Managed Approach
At Geeky Tech, we use GeekyIQ to run regular AI Search audits so our clients don’t have to run them themselves. With GeekyIQ, you can see:
- Which prompts drive buyer decisions in your category
- How each AI engine responds and their key differences
- Where competitors are cited, and you’re not
- Which gaps represent the highest commercial priority
In short: we do the work; you get a clear, live view of your AI visibility and what we’re doing about it.
Keep Reading to Perform Your Own AI Search Audit
We’ve covered what AI Search is, why it matters for B2B marketers, and which signals influence AI visibility. You’re ready for the next step: assessing your own visibility with an AI Search audit.
In Part Two, we’ll walk you through the framework you can use to evaluate where your brand stands and what to improve first.
