Not all B2B industries are equally visible in AI search, and the gap between the most-cited verticals and the least-cited ones is wider than most marketers expect. Based on Simaia's audit work across B2B companies in APAC, citation rates vary dramatically by industry because LLMs weight sources differently, trust signals differ by vertical, and content maturity across sectors is uneven. Knowing where your industry sits on that spectrum is the first step to closing the gap.

TL;DR

• AI search citation rates differ significantly across B2B verticals, not just across companies.

• Industries with mature, structured online content (SaaS, professional services) tend to earn higher citation rates than industries that have historically relied on trade shows and referrals.

• LLM citation probability is strongly tied to content structure, trusted-source presence, and organic search authority [thedigitalbloom.com].

• Measuring LLM brand visibility requires tracking four distinct signals: mention rate, citation rate, share of voice, and sentiment [thomas-peham.com].

• Companies can move from near-zero visibility to meaningful citation share in a matter of months with the right strategy, as Simaia's client results demonstrate.

About the Author: Simaia is an agentic marketing team specialising in AI search visibility for B2B companies across APAC. Simaia has run AI search audits across ChatGPT, Gemini, Claude, Perplexity, and Google AI Overview for clients ranging from healthcare SaaS companies to global manufacturers.

Why Does Citation Rate Vary So Much Across B2B Industries?

The short answer: LLMs cite what they can find, trust, and extract. Industries that have invested heavily in structured, authoritative online content over the years have built up a citation advantage that newer or more traditional sectors simply have not matched yet [onely.com].

Several factors drive this disparity:

• Content density: Industries like B2B SaaS have years of case studies, comparison articles, and analyst coverage that LLMs can draw from. Industries like manufacturing or industrial supply still rely heavily on product catalogues and trade publications that are not always indexed in formats AI systems prefer.

• Trusted-source presence: LLMs do not cite your website directly as often as they cite what is written about you on platforms they already trust: LinkedIn, Reddit, major media outlets, and industry publications [presenceai.app].

• Organic search correlation: There is a meaningful relationship between a brand's organic search ranking and its AI citation probability. A site sitting at SERP position one earns roughly a 33% chance of appearing in an AI Overview citation, while position ten drops that probability to around 13% [thedigitalbloom.com].

The practical implication is that your industry's citation baseline sets the floor, but your content strategy determines how far above that floor you can climb.

What Do Citation Rate Benchmarks Actually Look Like Across B2B Verticals?

AI search now drives a significant portion of B2B discovery, and citation rates across verticals reflect where buyers are researching and where content supply is richest [data-mania.com]. The table below reflects observed patterns from Simaia's audit work and published benchmarks [data-mania.com][thomas-peham.com].

The verticals at the bottom of this table are not invisible because they are unimportant. They are invisible because their historical go-to-market channels (trade exhibitions, referrals, cold outreach) produce no content that LLMs can cite [onely.com].

How Should B2B Companies Measure Their LLM Brand Visibility?

Stepping back from the vertical benchmarks, a separate but equally important question is how to measure where you actually stand. A meaningful measurement framework covers four components [thomas-peham.com]:

• Mention rate: How often does your brand appear in AI-generated answers at all, even without a direct citation link?

• Citation rate: How often does the AI system reference your content as a named source?

• Share of voice: What percentage of relevant AI answers in your category include your brand versus your competitors?

• Sentiment (Net Sentiment Score): When your brand is mentioned, is the framing positive, neutral, or negative?

Between 30% and 50% of B2B buying decisions now involve an AI search interaction at some point in the research process [thomas-peham.com]. A company that scores zero across all four metrics is effectively invisible to a large and growing share of its potential buyers.

Running an audit across all five major AI platforms (ChatGPT, Gemini, Claude, Perplexity, and Google AI Overview) using a structured set of buyer-intent prompts is the baseline requirement before any optimisation work begins [keyword.com]. Without this, any content investment is directionally blind.

What Moves the Needle for Low-Visibility Verticals?

Building on the measurement framework above, the harder question is what companies in low-maturity verticals should actually do. The answer is not to simply publish more blog posts. It is to build the right content in the right places in the right format [presenceai.app].

The highest-leverage actions for industries starting from a low citation baseline:

1. Publish structured, question-based content on your own site formatted for LLM extraction, not just traditional SEO. This means clear definitions, labelled sections, and direct answers to the questions buyers ask AI systems.

2. Build presence on platforms each LLM prefers. ChatGPT draws heavily from LinkedIn. Google AI Overview cites Reddit. Claude and Perplexity weight industry publications and structured media [presenceai.app].

3. Earn press coverage on high-authority outlets. A single press release placed in a major publication can lift domain authority and citation probability in ways that dozens of blog posts cannot match on their own.

4. Monitor and iterate. AI citation patterns shift as models are updated. Tracking your mention rate and share of voice monthly against competitors in your vertical is not optional [keyword.com].

Simaia's work with a global textile manufacturer illustrates the pace of change that is possible: AI bot visits grew from 741 to 2,546 in a single year, and inbound leads grew from roughly one every two months to five per month within two months of the programme starting. For a vertical sitting at the very bottom of the citation maturity table, that is a structural shift, not a marginal gain.

For a Healthcare SaaS company in Australia, Simaia took AI search visibility from 0% to 45% of niche traffic across major LLMs in 2.5 months. An AI search visibility tool and audit process that spans all five major platforms was central to identifying exactly where and how to intervene.

Frequently Asked Questions

What is LLM brand visibility?
LLM brand visibility refers to how often and how favourably an AI language model surfaces your brand when a user asks a question relevant to your product or service category. It is measured across mention rate, citation rate, share of voice, and sentiment [thomas-peham.com].

Which B2B industries have the lowest AI citation rates in 2026?
Based on Simaia's audit work and published benchmarks, manufacturing, textiles, industrial supply, construction, and outsourcing services consistently show the lowest citation maturity. These industries have historically relied on offline channels that produce no citable content [data-mania.com].

How is AI search optimisation different from traditional SEO?
Traditional SEO optimises for keyword ranking on a results page. AI search optimisation focuses on whether LLMs cite your brand as a trusted source in a conversational answer. The content format, platform presence, and authority signals required are meaningfully different [onely.com].

Do I need a separate strategy for each AI platform?
Yes. Each major LLM has different preferences for the sources it draws from. A single strategy will not perform equally across ChatGPT, Gemini, Claude, Perplexity, and Google AI Overview [presenceai.app].

How long does it take to improve AI search visibility?
Timelines depend on your starting baseline and industry. Simaia's Healthcare SaaS client moved from 0% to 45% visibility in 2.5 months. Earlier-stage verticals with no existing content foundation may take longer to establish initial citation presence.

What does an AI search optimisation agency actually do?
A capable LLM optimisation agency runs a structured audit across AI platforms, identifies the trusted sources LLMs use in your category, produces and places content in those channels, and tracks citation performance over time. Simaia delivers all of this as a done-for-you service, including lead identification for inbound visitors from AI referrals.

Is AI citation correlated with organic search rankings?
Yes. Research shows that SERP position one delivers roughly a 33% AI Overview citation probability, while position ten delivers around 13% [thedigitalbloom.com]. Organic authority and AI visibility are not identical, but they are closely linked [lilyraynyc.substack.com].

About Simaia

Simaia is an agentic marketing team built for B2B companies that want to be found by buyers using ChatGPT, Gemini, Claude, Perplexity, and Google AI Overview. Simaia replaces the need to hire separately for strategy, content writing, PR, SEO, and lead intelligence by delivering all of these functions as one integrated service. With clients across APAC spanning manufacturing, healthcare SaaS, outsourcing, and technology, Simaia runs the full AI-visibility playbook from audit to execution so founders and sales leaders do not have to figure it out themselves.

Ready to see where your brand stands across all five major AI platforms? Get your AI search audit at https://www.simaia.co/.