April 7, 202618 min read

Which Niches Are Worst Represented in AI Answers: Analysis of 20 Industries

GEO Scout research: which industries and business categories are least likely to appear in AI responses. Why some niches are invisible to AI and how to fix it.

Vladislav Puchkov

Founder of GEO Scout, GEO optimization expert

Neural networks already decide which bank to choose, where to learn programming, and which marketplace to shop on. But when a user asks ChatGPT about life insurance, a crypto exchange, or agricultural equipment — AI often responds with generic phrases, without naming specific brands. Entire industries are invisible to AI.

We at GEO Scout analyzed the representation of 20 industries in responses from 10 neural networks. The result: the gap between the best and worst-performing niches is more than 10x. And this creates both a problem and a massive opportunity for companies that understand the rules of the game first.

Methodology: How We Assessed Niche Representation

What We Measured

The primary metric is Aggregate Mention Rate (AMR): the average share of AI responses that mention at least one brand from a given niche for queries relevant to that industry. For example, when asked "which hosting to choose for an online store" — does AI name a specific hosting provider, or does it only give generic advice?

Additional metrics:

Study Parameters

• 20 industries — from e-commerce to agriculture
• 10 AI providers: ChatGPT, Claude, DeepSeek, Gemini, Google AI Mode, Google AI Overview, Grok, Perplexity, YandexGPT, Alice AI
• 30-50 prompts per niche — commercial queries in Russian
• Period: March-April 2026
• Source: GEO Scout monitoring data

More about metrics in our articles on brand AI visibility and AI visibility benchmarks by niche.

Niche Rankings by AI Representation

Complete Table: 20 Industries

Well Represented: 60-80% Mentions

E-commerce (78%), travel (72%), FinTech (68%) — the three industries AI knows best. Unsurprisingly:

• Mass consumer demand — millions of queries monthly
• Huge volume of review content — rankings, comparisons, "top-10" lists
• Developed aggregator ecosystem — from marketplaces to banking supermarkets
• High competition between brands — marketers actively create content

In e-commerce, leader Yandex.Market shows 97% mention rate. In FinTech, Alfa-Bank — 78%. In travel, Yandex Travel — 78%. More on industry benchmarks in our research by niche.

Moderately Represented: 30-50% Mentions

EdTech (54%), hosting (48%), SaaS (42%), telecom (38%), auto (35%) — AI knows these industries, but knowledge is uneven. The top 3 brands in each niche receive 60-80% of mentions, while the remaining 10-20 players share the leftovers.

In EdTech, for example, Netology holds 86.55% mention rate, while ProductStar and Skypro get 0% from ChatGPT — as we showed in our AI blind spots research. In hosting: Timeweb — 94% positive sentiment, but AdminVPS — 0% from ChatGPT.

A defining characteristic of moderately represented niches: AI names 2-3 brands confidently, while mentioning the rest randomly or not at all.

Weakly Represented: 10-25% Mentions

Real estate (30%), healthcare (27%), HR (24%), insurance (22%), marketing (20%), consulting (18%), logistics (15%) — here AI frequently gives generic advice instead of specific recommendations.

Ask ChatGPT "which life insurance to choose" — and you will get a paragraph about types of insurance with a couple of mentions of major companies. Ask "which consulting firm for digital transformation" — and AI will suggest general selection criteria without naming a single firm.

Nearly Absent: 0-10% Mentions

Cryptocurrency (8%), government services (6%), charity (4%), agriculture (3%), gambling (2%) — AI practically never gives brand-level recommendations in these industries.

Instead of specific answers, neural networks use three strategies:

1. Generic advice without brands — "pay attention to the following criteria when choosing..."
2. Referral to independent research — "we recommend independently reviewing ratings and feedback..."
3. Refusal to answer — "I cannot provide financial advice" or "this topic is regulated by law..."

Why Some Niches Are Invisible: 4 Causes

Analysis of GEO Scout data revealed four systemic factors that determine a niche's representation in AI.

1. Lack of Expert Content

AI forms responses from open sources. If there is little quality content about products and companies from a niche on the internet, neural networks have nothing to base recommendations on.

Example: insurance. Dozens of insurance companies operate in Russia, but the volume of review articles "life insurance — ranking 2026" is an order of magnitude lower than similar articles "best hosting 2026" or "top banks for sole proprietors." Insurance companies traditionally invest in offline channels and agency networks, not content marketing.

Numbers: by our estimates, the volume of structured review content in insurance is approximately 8-10x lower than in e-commerce, despite comparable market size.

2. Complex Terminology and Regulatory Specifics

Some industries operate with terms that AI cannot unambiguously interpret without context. Cryptocurrency, DeFi, government services, legal consulting — all require precise understanding of the regulatory environment, which varies by jurisdiction.

Example: cryptocurrency. The query "which crypto exchange to choose" is technically relevant to millions of users. But AI providers operate in different countries with different legal statuses for cryptocurrencies. Instead of recommending specific exchanges (Binance, Bybit, OKX), neural networks prefer to give general advice about security and diversification.

Example: government services. Public services are by definition unique to each country. AI cannot recommend "My Documents" centers or "Gosuslugi" as the best service centers — because the query context determines which specific government services are meant.

3. AI's YMYL Caution

YMYL (Your Money, Your Life) is a category of content that directly affects the user's financial well-being, health, or safety. AI providers handle such queries with heightened caution.

Niches with maximum YMYL caution:

AI providers consciously limit recommendation depth in YMYL niches. Instead of "choose insurance company X," the user gets "when choosing an insurance company, pay attention to..." This is an architectural decision, not a technical limitation.

4. Few Reviews, Rankings, and Comparisons

AI is trained on internet data. The primary source of knowledge about brands is not their official websites but third-party platforms: reviews, rankings, comparison tables, forums.

Niches with the least independent content:

• Agriculture — reviews of agricultural machinery and fertilizers barely exist in "top-10" format
• Charity — no established culture of nonprofit rankings
• Logistics — B2B services are poorly represented on public platforms
• Consulting — few objective comparisons, the market relies on personal connections

For comparison: the query "hosting comparison 2026" yields dozens of detailed reviews with tables, tests, and recommendations. The query "logistics companies comparison for e-commerce" — a couple of generic articles without specifics.

Deep Dive: 5 "Invisible" Niches with Examples

1. Cryptocurrency and DeFi — AMR 8%

The most paradoxical niche. The crypto industry is one of the most active in content creation: thousands of blogs, YouTube channels, Telegram groups. But this content is not what AI cites.

What happens with user queries:

Why: regulatory ambiguity + YMYL caution. AI providers do not want to bear responsibility for recommending a specific exchange in a jurisdiction where it may be illegal.

2. Insurance — AMR 22%

Insurance is a massive market (in Russia — over 2 trillion rubles in annual premiums), but AI barely sees it. When asked "which life insurance company is best," ChatGPT usually provides a paragraph about policy types and suggests "comparing offers from several companies."

Contrast with FinTech: when asked "which bank to choose for sole proprietors," AI confidently names 3-5 banks with specific terms. When asked "which insurance company is best for OSAGO" — generic words.

Reason: insurance companies historically sell through agents and offices, not content marketing. The volume of comparative content "insurance vs insurance" is orders of magnitude lower than "bank vs bank."

3. Consulting and Business Services — AMR 18%

Consulting is a B2B market where decisions are made based on personal connections, referrals, and reputation. AI is weakly integrated into this chain.

When asked "company for digital transformation of business," AI names McKinsey, BCG, and Deloitte — but these are global brands. Russian consulting firms (IASB, Strategy Partners, Alexander Proudfoot) are invisible.

Reason: consulting does not create content for a mass audience. White papers and case studies are published on company websites but do not reach aggregators and review articles that AI cites.

4. Logistics and Delivery — AMR 15%

Logistics is the invisible infrastructure of e-commerce. A user asks "which logistics company is best for an online store" — and AI responds with general selection criteria without naming specific operators.

Paradox: in e-commerce (AMR 78%), AI actively recommends marketplaces — but logistics operators that serve these marketplaces are not mentioned. CDEK, PEK, Delovye Linii — large companies with billion-ruble revenues, but for AI they are a "blind zone."

Reason: logistics is a B2B service; end consumers do not think about it. There are few public reviews and comparisons. Business clients choose logistics through personal experience and tenders, not internet reviews.

5. Agriculture and Agro — AMR 3%

The most "invisible" of mass industries. When asked about agricultural machinery, fertilizers, or seeds, AI gives technically competent but completely impersonal answers. Specific brands — manufacturers, distributors, agro-consultants — are never mentioned.

Why: agriculture operates through dealer networks, exhibitions, and industry publications. Content is created for professionals and distributed in closed channels. There is virtually no "agro-content" on the open internet — and AI does not see it.

Why "Invisibility" Is an Opportunity

Here is the key insight many miss: niches with low AI representation are not a problem — they are a window of opportunity.

The SEO 2005 Analogy

In 2005, SEO was a young discipline. Those who started optimizing websites first occupied top search results with minimal effort. By 2015, SEO competition had become so fierce that reaching the top 10 required budgets of millions of rubles.

GEO in 2026 is like SEO in 2005. But with one difference: in some niches, competition for AI attention is exactly zero.

The Math of First-Mover Advantage

In e-commerce, dozens of brands with multi-million marketing budgets fight for the top-3 in AI responses. Yandex.Market, Ozon, Wildberries, Megamarket, Avito — all invest in content, structured data, and platform presence. Breaking into the top-3 against such competition is enormous work.

In insurance, nobody fights for the top-3. Create 10-15 quality expert articles, get mentions on 3-5 authoritative platforms, implement structured data — and you will likely become the brand that AI recommends by default.

Effort comparison:

Industries with Maximum Potential

According to GEO Scout, the highest potential for GEO optimization in 2026 belongs to:

1. Insurance — huge market, zero competition for AI attention
2. Logistics — growing e-commerce creates demand for AI recommendations
3. HR and recruiting — niche is digitalizing fast, AI queries growing
4. Consulting — premium segment, high value of AI recommendation
5. Real estate — large transaction values, high dependence on recommendations

Practical Steps: How to Increase Your Niche's Representation

If you operate in a niche that is "invisible" to AI, here is a concrete action plan.

Step 1: Create Expert Content That AI Can Cite

AI extracts facts from structured content. Your articles should answer specific questions:

• "How to choose [your product/service] — criteria and comparison"
• "[Your service] vs [alternative] — which is better in 2026"
• "Top 5 [products in your niche] — ranking with justification"
• "How much does [your service] cost — prices and plans 2026"

Format: detailed articles of 3000-5000 words with tables, comparisons, and concrete numbers. AI loves facts that it can extract and rephrase.

Step 2: Get Mentions on Authoritative Platforms

AI does not cite your articles — it cites third-party sources. You need mentions on platforms that neural networks trust:

• Industry media — tech blogs, business publications, industry-specific outlets
• Ranking aggregators — ratings, comparisons, directories
• Expert platforms — blogs, podcasts, interviews
• Directories — maps, industry catalogs, business directories

Step 3: Implement Structured Data

JSON-LD markup helps AI understand your content. The minimum set:

• Organization — company data
• Product / Service — products and services with prices
• FAQ — questions and answers (AI particularly favors this format)
• Review — reviews and ratings
• Article — expert articles with authorship

Learn more in our article on FAQ Schema Markup for AI responses.

Step 4: Monitor Progress and Adapt Strategy

GEO optimization is not a one-time action — it is a process. Track:

• Mention Rate of your brand — is it growing month over month
• Aggregate Mention Rate of your niche — is it appearing in AI responses more often
• Position — where AI places you
• Sentiment — positive, neutral, or negative

The GEO Scout platform tracks all these metrics daily across 10 AI providers. You see the dynamics and understand what works and what does not.

Step 5: Become the "Voice of the Industry"

In niches with low AI representation, a single expert resource can become the primary knowledge source for neural networks. Create:

• An industry blog with regular publications
• An annual ranking of market players
• A glossary of terms and definitions
• Calculators and tools for comparison

If AI starts citing your resource as authoritative — you become not just a visible brand but the source through which AI learns about the entire industry. This is a strategic advantage that cannot be purchased with an advertising budget.

FAQ

What does it mean for a niche to be "poorly represented" in AI?

It means that when users ask questions related to that industry, neural networks rarely mention specific brands and companies from that niche. Instead of brand recommendations, AI gives generic advice, suggests brands from adjacent niches, or outright admits it cannot provide a concrete answer. In our data, this is expressed through a low Aggregate Mention Rate — the average percentage of AI responses mentioning at least one brand from the niche.

Why are cryptocurrency and DeFi almost absent from AI responses?

Three reasons. First: YMYL caution. AI providers deliberately avoid giving financial advice in high-risk areas — instead of naming specific platforms, they offer general warnings. Second: regulatory ambiguity. The legal status of cryptocurrencies varies by country, and AI prefers not to recommend services that may be illegal in the user's jurisdiction. Third: lack of structured expert content. The crypto industry creates content for insiders, not for neural networks.

How can a small business in an "invisible" niche increase its chances of AI mentions?

Four steps. 1) Create detailed content answering specific questions from your audience — AI extracts facts from such materials. 2) Get mentions on authoritative platforms — rankings, reviews, expert articles on industry media. 3) Add structured data to your website — JSON-LD markup with FAQ, products, services. 4) Register in aggregators and directories — AI actively cites them. The first results will appear within 2-4 months of systematic work.

Does company size affect niche representation in AI?

Indirectly yes, directly no. Large companies create content more often and have media presence, which increases their chances of being mentioned. But our analysis shows that within a niche, business size does not correlate with AI position. In hosting, AdminVPS (a small company) outranks Selectel (a large provider). In FinTech, T-Bank outranks Sberbank. AI evaluates not size but content quality and digital presence. More details in our study on business size and AI position.

How was niche representation measured in this study?

We used Aggregate Mention Rate — the average share of AI responses mentioning at least one brand from a given niche when asked queries relevant to that industry. Monitoring was conducted across 10 AI providers (ChatGPT, Claude, DeepSeek, Gemini, Google AI Mode, Google AI Overview, Grok, Perplexity, YandexGPT, Alice AI) using commercial queries in Russian. GEO Scout data, March-April 2026.

Why is niche "invisibility" an opportunity for businesses?

Because in niches with low AI representation, competition for neural network attention is practically zero. The first brand that creates quality expert content and gets mentions in cited sources will automatically dominate AI responses. In EdTech and e-commerce, dozens of brands with budgets fight for top-3. In insurance or agriculture — almost no one. Minimal effort yields maximum results.

Which niches are best represented in AI responses?

According to GEO Scout data: e-commerce (Aggregate Mention Rate 78%), travel (72%), and FinTech (68%). These industries are best represented due to abundant review content, comparison aggregators, active brand marketing strategies, and high frequency of user queries. In e-commerce, Yandex.Market shows 97% mention rate; in FinTech, Alfa-Bank — 78%; in travel, Yandex Travel — 78%. Full data on 716 brands is available in our 5-niche study.

Full AI visibility monitoring data by industry and brand is available on the GEO Scout platform. Daily tracking across 10 AI providers, automated reports, competitive analysis.