TL;DR / Key takeaways:

• The localisation gap: AI search results are highly volatile; a study by Peec AI found a 144% variance in results between regions for identical B2B queries.
• The English bias: In localised markets like Sweden, English-language prompts can return 100% US-based sources, making local brands invisible if they do not optimise for local context.
• Value at stake: Research by Precis shows that nearly 20% of all B2B search value is now filtered through AI summaries, intercepting high-stakes, bottom-of-funnel traffic.
• Share of Model (SoM): Success in AEO/GEO is measured by how often your brand is cited as a trusted recommendation, rather than just ranking in a list of links.
• The framework: Visibility is engineered through a 5-step process: Intelligent prompting; Scalable collection; Gap analysis; Content mapping, and Influencing third-party sources.

Why does visibility in AI search matter for B2B?

For us B2B marketers, the search landscape has shifted beneath our feet. Discovery no longer begins and ends with a list of blue links on Google. Today, your potential customers are building their vendor shortlists within Answer Engines like ChatGPT, Perplexity, and Gemini.

Whether you call it AEO (Answer Engine Optimisation) or GEO (Generative Engine Optimisation), the goal is the same: ensuring your brand is the one cited when an AI model synthesises an answer for a buyer. In this new "zero-click" reality, if an AI model cannot verify your data or find consistent signals of your authority, your brand effectively ceases to exist in that buyer's journey.

The "localisation gap": why global strategies fail locally

In a recent study of almost 5,000 prompts conducted by Peec AI, we uncovered a staggering reality for international B2B firms. While traditional search results are relatively stable across regions, AI search results are volatile. For "employment compliance tools", we found a 144% variance in results between the US, UK, and Sweden.

Perhaps most alarming for brands in localised markets: English-language prompts used in Sweden can return 100% US-based sources. If you aren't optimising specifically for how these generative engines interpret local context and language, you risk being invisible to some of your most high-intent leads.

The value at stake: insights from Precis research

Our own research at Precis has highlighted that this is more than just a visibility issue: it is a financial one. In our AI Overviews Report, we found that B2B search shows the highest "value density". Nearly 20% of all B2B search value is now filtered through AI summaries, meaning AI is intercepting the high-stakes, bottom-of-funnel queries that used to drive your most valuable organic traffic.

The Precis 5-step framework for AI search visibility

To capture this pipeline, we deploy a data-led approach to bridge the gap between intent and citation.

1. Intelligent prompt engineering
2. Scalable data collection
3. Strategic gap analysis
4. Content mapping and creation
5. Influencing the source

Step 1: Intelligent prompt engineering

What is it?
Identifying the specific questions your buyers ask and translating them into high-quality prompts that mirror real-world "fan-out" queries.

Why does it matter?
As insight into what people prompt is a "black box" right now, this step must be considered carefully. The quality and accuracy of your prompts determine the quality of your data output. To ensure your data is worth acting on, you must constantly reiterate and improve your prompts based on actual buyer pain points and questions.

Here’s how you do it:

• Collaborate with sales teams: Map out real-world pain points, such as specific feature requests or cost comparisons.
• Use SEO volume as a proxy: Map search volumes to prompts to understand which topics are most valuable to track.
• Create prompts for key business areas: Ensure you have coverage for every vertical and service you offer. 

Step 2: Scalable data collection

What is it?
The process of gathering a large, accurate dataset across different LLMs and regions to build a strategy worth acting on.

Why does it matter?
Manual prompting only reveals a fraction of the truth. Factors like your location and how you use the model will determine the answers you see; therefore, you need scale to eliminate bias and gain accuracy. You need a solution—whether bespoke or platform-built—that provides data across the entire LLM landscape.

Here’s how you do it:

• Track your Share of Model (SoM): Measure your brand visibility and volume across various LLMs and regions.
• Identify citation sources: Log the specific domains and sources LLMs use to retrieve answers.
• Audit language performance: Collect data in both English and your local language(s) to see where English sources might be outperforming your local content.

Step 3: Strategic gap analysis

What is it?
A data-led comparison of your visibility against competitors for specific "entities" or topic areas.

Why does it matter?
You need to identify which topics your competitors own and where you are missing from the conversation. By categorising your prompts by intent, you can see if LLMs are considering your brand for every part of the funnel or if you are only appearing at the very end of the buyer's journey.

Here’s how you do it:

• Audit TOFU (Top of Funnel): Check if you are being retrieved for educational content and category definitions.
• Audit MOFU (Middle of Funnel): Ensure you are helping buyers gain insight into their specific needs and solutions.
• Audit BOFU (Bottom of Funnel): Verify that when a buyer asks for a vendor comparison, the AI mentions your unique differentiators.

Step 4: Content mapping and creation

What is it?
The tactical process of ensuring your website is retrievable by AI and creating new content to plug visibility and intent gaps.

Why does it matter?
AI models prioritise highly structured data and scannable formats; if your best insights are locked in non-scannable PDFs or complex JavaScript, the LLM simply cannot find them. A mapping document acts as the bridge between your data insights and the actual actions required to become more visible.

Here’s how you do it:

• Create a mapping worksheet: Identify which pages require structured FAQs, comparison tables, or brand-new content.
• Prioritise by "Tier": Focus on "Tier 1" areas where you have zero citations or where gaps with competitors are widening.
• Optimise existing assets: Ensure content exists for "commercial moments" where competitors are currently outperforming you.

Step 5: Influencing the source

What is it?
A Digital PR and brand strategy designed to build authority on the third-party platforms that LLMs use to form opinions.

Why does it matter?
While your website is the foundation, LLMs synthesise information from across the web. Data from the Peec.ai study shows that while giants like Reddit and YouTube are widely cited, smaller, industry-specific sites are often the primary sources for niche B2B sectors. You must own the narrative across all touchpoints to "train" the LLMs on what your brand stands for.

Here’s how you do it:

• Identify citation leaders: Use your data collection to find the specific sources that get cited most for your vertical.
• Execute an off-page strategy: This may include listicle inclusions, guest blogging, or updating business profiles on sites like G2.
• Maintain brand consistency: Use your brand voice, key selling points, and "tagline" across all online mentions to reinforce your authority with the models.

Top tip: Consistency is key. Every mention of your brand online is training the LLMs: ensure you own the answers by owning the narrative.

From ranking to recommendation

In 2026, winning at search has moved far beyond ranking no. 1 in Google. Now it’s about being the trusted recommendation in a conversation. By implementing this framework, B2B brands can move from uncertainty of where they stand in AI search, to start owning the answers and carving out their future organic search visibility. 

Is your brand being recommended by AI, or are competitors capturing your pipeline? Start by auditing your Share of Model today, or get in touch with us to get started.