AI Search Optimisation Playbook: From SEO To GEO
Marketing professionals are watching organic traffic behave strangely. Pages still rank, impressions look healthy, yet sessions slide. Google’s AI Overviews and similar browser features give users a complete answer at the top of the page, often without a single click.
Recent reports show a sharp rise in “zero-click” searches as AI summaries resolve the query inside the search itself.
Users are still searching. They just see the answer long before they ever see your site. AI search optimisation is the work of earning a place inside that answer.
What is AI search optimisation, really?
Most definitions converge around a simple idea:
AI search optimisation is the practice of making your content frequently referenced and prominently featured inside AI-generated answers across platforms like Google AI Overviews, ChatGPT, Gemini and Perplexity.
In other words, it is the operational side of Generative Engine Optimisation (GEO). Instead of chasing rankings, you are optimising:
- Inclusion
Are you mentioned or cited in the answer at all? - Salience
Are you a primary reference or buried in a long list of sources? - Framing
How do engines describe you compared with competitors?
Traditional SEO still matters. Technical health, crawlability and strong on-page content give AI systems something reliable to read. But generative engines favour:
- Clear, unambiguous explanations
- Chunk-level relevance rather than whole-page signals
- Earned media citations from authoritative third parties on top of your own site
That last point is critical and drives the largest percentage of AI citations (up to 90% as per a recent study by Muck Rack).
SEO vs GEO: how the rules of visibility are changing
In simple terms: SEO brings visitors to pages, GEO brings your ideas into AI answers.
Industry research backs this shift:
- GEO focuses on full conversational questions, SEO on shorter keyword strings
- GEO success is measured in citations and inclusion, SEO in rankings and clicks
- GEO leans heavily on earned authority and structured evidence, SEO can rely more on owned content and links
For an in-house team, the difference shows up in daily work:
| Old playbook (SEO) | New layer (GEO / AI search optimisation) |
|---|---|
| Target keywords | Target question patterns and roles |
| Optimise pages | Optimise paragraphs, snippets and FAQs |
| Build backlinks | Build citations, quotes and mentions in trusted outlets |
| Track rankings & CTR | Track inclusion rate, share of answer and sentiment |
The opportunity is obvious: very few brands treat AI search as a first-class channel or a new stakeholder. The ones who do will compound authority faster than those waiting for the traffic charts to stabilise.
Step 1: Map AI demand, not just keywords
1. Role based prompts
These reflect how people talk to AI assistants:
- “As a B2B CMO, how should I approach GEO this year?”
- “As a founder in fintech, what is the best way to prepare for AI Overviews?”
2. Decision stage prompts
These surface objections and urgency:
- “Is GEO worth it for a mid sized B2B SaaS company in 2025?”
- “What is the risk of ignoring AI search for our brand this year?”
3. Comparison prompts
These drive a lot of evaluative research:
- “GEO vs SEO for B2B SaaS”
- “AI search vs traditional SEO metrics”
You do not need expensive tools to find these. Start with:
- Questions from sales calls and RFPs
- Q&A from events, webinars and podcasts
- Internal search logs and site queries
- Questions you see repeatedly on LinkedIn, Reddit, niche communities and conference panels
Then translate the best prompts into a topic map:
- One canonical explainer per core topic
- Supporting articles for “how”, “why”, “risk” and “comparison” angles
- FAQ clusters that read naturally to humans and machines
This gives you the scaffolding to build AI ready content with intent baked in.
Step 2: Build AI ready content hubs
AI search raises the bar on something you already know: topic ownership.
The brands that win become the default answer in their category, both for humans and for machines. That usually does not come from a random collection of blog posts. It comes from content hubs.
A strong hub becomes:
- The source of truth AI engines can quote for clean definitions
- The single URL that consolidates experience, evidence and media
- The reference journalists and analysts use when they need a definitive explanation
To make a hub AI ready:
- Lead with a clean definition
Start with one or two plain sentences that define the concept with no fluff. This is the paragraph AI engines love to lift.
2. Use question based sub headings
Structure your article around real questions such as: “How does GEO work with traditional SEO?” or “Who should own AI search optimisation in a marketing team?”
3. Expose your methods and evidence
Dedicate a section to “How we know this” that includes: data points and study references, real world examples and case snapshots, links to original sources that matter in your industry, etc.
4. Add structured data and schema
Implement JSON LD for Article, FAQPage and HowTo where relevant. It will not guarantee inclusion in AI answers, but it gives engines extra context about entities, relationships and question sections.
You are still writing for people. The only difference is that you are deliberately making things easier for AI systems to parse, quote and trust.
Step 3: Optimise at the paragraph level for GEO
Generative engines do not quote entire pages. They pull factual spans from multiple sources and rewrite them into a new answer.
That means your real optimisation unit is the paragraph. When you write or edit AI critical content, apply a few simple rules.
1. Make each key paragraph self contained
The reader should understand the claim without scrolling up.
Instead of: “Which is why this matters so much for modern brands.”
Write: “AI search optimisation matters because AI answers often replace clicks entirely for many queries, which means brands can lose visibility even while they still rank.”
2. Use entity rich language
Include:
Concept names: Generative Engine Optimisation (GEO), AI search optimisation
Roles: CMO, Head of Communications, Performance Marketing Lead
Verticals: B2B SaaS, fintech, healthcare, professional services
This helps models connect your explanation to specific scenarios and personas.
3. Pair claims with light evidence
When you reference trends, such as zero click searches rising or AI Overviews impacting organic traffic, point to a study, benchmark or platform report. Even a short mention with a link gives models a stronger confidence signal.
4. Treat FAQs as a GEO surface
Add a compact FAQ beneath the main content with questions like:
- “How is AI search optimisation different from SEO?”
- “Which metrics should we track for GEO?”
- “Does GEO replace PR or SEO?”
Answer each in two to four sentences, written as if the AI will quote them verbatim.
This is practical GEO. You are shaping the snippets that models find easiest to understand and reuse.
Step 4: Earn the citations AI engines trust
There is an uncomfortable but useful truth here. Most AI citations do not come from your own site. They come from earned media and high authority third parties.
Studies of AI search behaviour show a strong bias towards:
- Reputable news outlets and trade publications
- Long form explainers that define concepts clearly
- Sources with consistent terminology across multiple pages
For marketing and communications teams, this means GEO sits at the intersection of:
PR and earned media
Get your definitions, frameworks and quotes into publications AI already reads.
Owned content
Maintain a clean, stable source of record hub on your own domain, which those articles can point to.
Executive and expert visibility
Place your spokespeople in panels, podcasts, reports and events that become new training and reference material.
Step 5: Measure AI search visibility like a serious channel
If AI search matters, it deserves real metrics. Rankings and clicks are no longer enough. You can start with a simple framework.
1. Inclusion metrics
For your priority topics, track how often your brand appears in:
- Google AI Overviews
- ChatGPT answers
- Gemini or Perplexity responses
Pick a small set of canonical prompts and check them monthly. Capture screenshots or export logs where possible.
2. Source influence
Note which domains appear repeatedly alongside you or instead of you. Group them into:
- Trade media
- Vendors
- Analysts
- Government or standards bodies
This shows where you need more earned presence.
3. Sentiment and framing
Look at how models describe your products and approaches. Ask:
- Does this language reflect our brand narrative?
- Are we being framed as a leader, a follower or simply a vendor in the list?
If the wording is off, you do not fix it with a clever prompt. You fix it upstream, through clearer messaging and stronger reference content.
4. Business impact
Connect AI visibility back to business outcomes:
- Changes in direct traffic and branded search
- Consultation bookings and demo requests
- Referral quality from articles and pages where you already control the narrative
This keeps you honest and avoids another wave of vanity metrics dressed up with an AI badge.
A 30 day GEO first action plan
If your team has limited bandwidth, you can still build momentum in one month.
Week 1: Pick your flagship topic
- Choose one topic where you deserve to be the reference
- Map 10 to 15 AI style prompts around that topic
- Audit your existing articles, landing pages, talks and press mentions against those prompts
Week 2: Build or sharpen the hub
- Write or refine your canonical explainer
- Add three or four question driven sections that mirror common prompts
- Implement basic schema and a short FAQ written in natural, answer style language
Week 3: Seed earned authority
- Pitch one trade press article, guest column or podcast that quotes your definition and links back to the hub
- Repurpose a recent talk or webinar into a Q&A that sits under the hub and reuses the same language
- Align messaging with your wider communications strategy so that executives, sales and marketing all tell the same story
Week 4: Baseline AI visibility
- Capture how AI engines answer your priority prompts today
- Note inclusion, source mix and sentiment
- Use this as your quarter one baseline to see how GEO work shifts visibility over time
By the end of 30 days you will have:
- One credible source of record hub
- At least one earned media placement that reinforces it
- A simple measurement baseline for AI search visibility
From there you can scale across more topics without guessing.
Circular Marketing and GEO: one loop, not separate projects
AI search optimisation is not a separate discipline that lives in an experimental corner of marketing. In a Circular Marketing Model, it behaves more like a quality check on the entire system.
If your stories are strong, consistent and genuinely useful, they tend to:
- Be quoted by journalists and analysts
- Be trusted by AI systems and answer engines
- Be shared and reinterpreted by communities and partners
Performance campaigns feed prompts and traffic. Content hubs provide the substance. Events and speaking create fresh, human material that anchors your expertise in reality.
GEO simply asks a hard question:
“When AI compresses this entire category into three paragraphs and a handful of citations, do we appear in that story, and do we like the way we are described?”
If AI search is becoming the new homepage, Circular Marketing is the engine room that keeps that homepage worth visiting.
Iskren Lilov
iskren@lilov.com
Marketing and communications expert specialising in strategic consultancy and sustainable brand building. Author of the Circular Marketing Model™ that offers a paradigm shift for marketers in the age of AI, replacing the classic understanding of the funnel with a sustainable circular model.
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