AI Search Engine Optimisation: Why 90% of SMEs Are Invisible in AI Search – and How GEO Changes That

The new reality: AI search engines are changing the market faster than expected

Imagine this: a potential customer asks ChatGPT for the best provider in your industry. The AI names three companies - yours is not among them. No ranking problem, no budget problem. Your company simply does not exist for this search engine.

In 2026 this is no longer a future vision but daily reality. According to a BrightEdge study (2025), over 30% of all informational search queries are already answered by AI-generated answers - and the trend is rising. Google AI Overviews, ChatGPT Search, Perplexity, Microsoft Copilot and Gemini have changed the way people find information and make purchase decisions.

The problem: the rules by which AI search engines decide which companies are cited differ fundamentally from classic SEO. And this is exactly where most small and medium-sized enterprises (SMEs) in the DACH region are blind.

This article shows you why your company is probably invisible in AI search results - and which concrete steps you can take to change that.

What is AI search engine optimisation - and why is classic SEO no longer enough?

AI search engine optimisation - also called Generative Engine Optimization (GEO) - is the systematic optimisation of online content so that AI models recognise your company as a trustworthy source, cite it and recommend it.

The decisive difference to classic SEO: with Google you rank on a list of ten blue links. With AI search engines there is no list. The AI synthesises a single answer from dozens of sources - and autonomously decides which companies are named and which are not.

Classic SEO vs. AI search engine optimisation

In classic SEO you optimise for keywords, backlinks, technical factors and user signals. The goal: appear as far up as possible in the search results. The mechanics have essentially stayed the same for 20 years.

AI search engine optimisation works differently:

• Entity recognition instead of keyword matching: AI models do not understand keywords, they understand entities - meaning concrete companies, people and concepts. If your company is not clearly defined as an entity in training data and the live web, you simply will not be recognised.

• Authority instead of backlinks: AI models do not rate the number of your backlinks, they rate whether your company is mentioned in trustworthy contexts - industry directories, trade media, review portals, Wikipedia entries.

• Citeability instead of ranking: your content must be structured so that an AI can use it as the answer to a question. That means: clear statements, numbers, definitions and source references.

• Consistency instead of one-off optimisation: AI models cross-check information from dozens of sources. Contradictory information about your company (different addresses, varying service descriptions, inconsistent industry classifications) makes the AI rate your company as unreliable.

Why this is especially critical for SMEs

Large companies and well-known brands have a natural advantage: they are mentioned in hundreds of sources, have Wikipedia entries, press coverage and a strong digital presence. AI models already know them.

SMEs, on the other hand, often sit in a digital no-man's land. The website is technically fine, perhaps there is even a blog - but the overall digital presence is not enough for an AI to recognise the company as a relevant entity.

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The 5 main reasons why SMEs are invisible in AI search

Reason 1: missing entity presence in the knowledge graph

Google has a knowledge graph with billions of entities. If your company does not exist there - or only fragmentarily - then the AI lacks the basis to recognise you.

What does that mean in concrete terms? Google Knowledge Graph is fed by structured data (Schema.org), Wikidata, official directories and consistent mentions on the web. Most SMEs have:

• No complete Google Business Profile
• No structured data on the website
• No consistent NAP data (name, address, phone) across all platforms
• No Wikidata entry
• No mentions in relevant industry directories

Without this foundation, no AI can classify your company as a trustworthy entity.

Reason 2: content without citeability

Most company blogs consist of generic texts that are optimised for keywords, but do not contain a single citeable statement. AI models look for:

• Concrete numbers and data: "Our customers increase their ROAS by 340% on average in 6 months" is citeable. "We improve your results" is not.
• Definitions and explanations: clear, concise definitions are preferred by AI models as an answer building block.
• Expert opinions with source reference: statements attributed to a concrete person are cited more often than anonymous texts.
• Structured data: FAQ markup, HowTo markup and other Schema.org annotations help AI models identify your content as an answer.

A blog post without these elements is, for AI search engines, like a book without a table of contents - theoretically available, practically untraceable.

Reason 3: no multi-source presence

AI models do not rely on a single source. They triangulate information. If your company only exists on your own website, external validation is missing.

A Princeton University study (Aggarwal et al., 2023) on Generative Engine Optimization shows that AI models prefer sources confirmed by several independent mentions. This means: your company must be consistently present on various platforms:

• Industry directories and review portals
• Trade publications and guest posts
• Social media profiles with regular activity
• Podcast appearances, webinar documentation, conference listings
• Review platforms such as Google Reviews, Trustpilot or ProvenExpert

The more independent, trustworthy sources mention your company, the more likely a citation by AI search engines.

Reason 4: outdated SEO strategy without a GEO component

Many SMEs still run SEO on the 2020 playbook: research keywords, write content, build backlinks, track rankings. That still works for classic Google search - but it does not address AI search.

GEO requires additional measures:

• Structured data at the organisation level: Organization schema, LocalBusiness schema, Product schema - not only individual blog posts, but the whole website must be machine-readable.
• E-E-A-T on steroids: experience, expertise, authoritativeness, trustworthiness matter even more for AI models than for classic Google. Author profiles, references, certifications and verifiable expertise decide whether your content is cited.
• Answer-optimised content: instead of only writing for keywords, content must explicitly answer questions - in a format an AI can use as an answer building block.
• Brand building as an SEO factor: the better known your brand, the more often it is mentioned by AI models. Brand searches, brand mentions and digital PR become central ranking factors.

Reason 5: no monitoring of AI visibility

How often is your company recommended by ChatGPT? In what context does your name appear on Perplexity? Is your brand cited in Google AI Overviews?

Most SMEs have no answer to any of these questions - because they simply do not measure AI visibility. In 2026 there are already specialised tools and methods to track how often and in what context your company is mentioned by AI models. Without this monitoring you are flying blind.

The concrete roadmap: how SMEs become visible in AI search engines

Phase 1: build the entity foundation (month 1-2)

Before you optimise content, you have to strengthen your digital foundation. That means:

1. Fill in the Google Business Profile completely

Every field, every category, every attribute. Photos, opening hours, service descriptions - everything must be current and complete. Google Business Profile is one of the most important data sources for AI models.

2. Ensure NAP consistency

Check EVERY platform on which your company is mentioned. Name, address and phone number must be identical everywhere. Every deviation confuses AI models and lowers your entity authority.

3. Implement structured data

At least Organization schema, LocalBusiness schema (if relevant) and FAQ schema on your most important pages. This gives AI models machine-readable information about your company.

4. Create a Wikidata entry

If your company does not yet have a Wikidata entry, create one. Wikidata is one of the primary sources for AI knowledge graphs.

Phase 2: optimise content for AI citeability (month 2-4)

Once the foundation is in place, it is about content. The rule: not more content, but better content.

1. Audit existing content

Which of your pages are currently used by AI models as a source? Which are not? Identify the gaps.

2. Optimise content formats for AI

• Add a clear definition of the main topic to every article (often used by AI as an answer snippet)
• Use numbers, statistics and concrete examples
• Structure content with clear headings and short paragraphs
• Integrate FAQ sections with precise answers
• Name authors with proof of expertise

3. Create thought-leadership content

Content that offers original insights, own data or unique perspectives is preferred by AI models for citation. Recycled content has hardly any chance of being cited.

Phase 3: build multi-source presence (month 3-6)

Your company must be visible beyond your own website:

1. Strengthen industry presence

Active profiles on relevant review portals, industry directories and platforms. Not just registered, but actively maintained.

2. Digital PR and specialist contributions

Guest posts in trade media, interviews, podcast appearances, conference contributions - every independent mention strengthens your entity authority.

3. Build social proof systematically

Actively collect customer reviews and spread them across several platforms. AI models use reviews as a quality signal.

Would you like to know how visible your company currently is in AI search engines? Nordsteg analyses your digital presence and shows you concretely where you stand and what needs to be done. Request a no-obligation consultation

Phase 4: monitoring and continuous optimisation (ongoing)

AI search engines are evolving rapidly. What works today may be weighted differently tomorrow. That is why you need ongoing monitoring:

• AI citation tracking: regularly check whether and how your company is mentioned by various AI models
• Competitive monitoring: which competitors are recommended by AI search engines - and why?
• Content performance: which content generates AI citations and which does not?
• Algorithm updates: AI models are updated continuously - stay informed about changes

Which AI search engines are relevant in 2026?

Google AI Overviews

Google AI Overviews (formerly SGE) are the norm in most markets in 2026. On informational search queries, an AI-generated summary often appears above the organic results. These overviews cite sources - but significantly fewer than the classic ten blue links.

According to an Authoritas analysis (2025), AI Overviews cite only 3-5 sources on average - compared to 10+ organic results on the first page. That means: only the most relevant and trustworthy sources make it into the AI answer. The rest lose visibility.

ChatGPT Search

OpenAI has created a fully-fledged search engine replacement with ChatGPT Search. Millions of users ask their questions directly to ChatGPT instead of Google. The particularity: ChatGPT cites sources with a link, but the selection is even more selective than with Google AI Overviews.

Perplexity AI

Perplexity positions itself as an "answer engine" and is particularly popular for research-intensive queries. The platform cites sources transparently and links them - which is a chance for companies to gain qualified traffic.

Microsoft Copilot and Gemini

Microsoft integrates AI answers into Bing and the whole Microsoft 365 stack. Google Gemini is integrated into Gmail, Google Docs and Google Search. Both platforms use their own crawling and citation mechanisms.

The cost of invisibility

What happens if SMEs ignore AI search engine optimisation? The consequences reach further than with classic SEO:

Creeping traffic loss

AI Overviews answer the question directly - the user no longer clicks on your website. Studies show that pages below AI Overviews receive up to 60% fewer clicks. For SMEs that depend on organic traffic, this threatens existence.

Loss of the recommendation position

If a potential customer asks ChatGPT "which marketing agency in Austria is good for B2B?" and your company is not named - then you do not exist for this customer. No second chance, no "scroll further". The AI has decided.

Competitive advantage for early adopters

Companies that invest in AI search engine optimisation now build a lead that is hard to catch up with. Entity authority and multi-source presence cannot be built overnight. The longer you wait, the bigger the backlog.

The compound effect

AI models learn from their own outputs. If a company is cited often today, the likelihood rises that it will be cited in future model updates too. Whoever is present early benefits from the compound effect of AI visibility.

Common mistakes in AI search engine optimisation

Mistake 1: treating AI optimisation as a separate project

GEO is not a parallel strategy to SEO - it is an extension. Whoever runs them separately doubles the effort without the double benefit. The best strategy integrates classic SEO and GEO into one unified approach.

Mistake 2: focusing only on your own website

AI models do not only read your website. They read the whole web. If your company only exists on your own domain, external validation is missing. Multi-source presence is not a nice-to-have, but mandatory.

Mistake 3: putting content quantity over quality

More blog posts do not mean more AI visibility. A single, excellently researched article with original data and clear statements is cited more often by AI than twenty superficial texts.

Mistake 4: neglecting structured data

Schema.org markup is, for AI models, like a manual for your website. Without structured data, the AI has to guess who you are and what you offer - and it often guesses wrong or not at all.

Mistake 5: not being patient

Building entity authority takes months, not days. AI models do not update their knowledge base daily. Anyone who gives up after two weeks wastes the long-term investment.

Industry-specific particularities

B2B companies

For B2B companies, AI visibility is particularly relevant because buying decisions increasingly start with AI research. A buyer who asks ChatGPT for providers of a specific solution gets a curated shortlist - and contacts only the listed companies.

B2B-specific GEO measures:

• Publish case studies with concrete numbers (AI loves measurable results)
• Be present on B2B review portals
• Publish whitepapers and studies that can be cited as a source
• Use LinkedIn presence as an authority signal

E-commerce and online shops

For online shops, AI visibility increasingly decides product recommendations. If a user asks ChatGPT "which hiking shoe is the best for beginners?", only products that are well documented in test reports, review portals and trade media are recommended.

E-commerce-specific GEO measures:

• Product schema on all product pages
• Active review strategy on Google, Trustpilot and industry-specific portals
• Aim for comparative tests and test reports in trade media
• FAQ sections on category and product pages

Service providers and freelancers

For service providers, personal entities are especially important. AI models recommend not only companies, but also people. A clearly positioned expert with a consistent online presence has better chances of AI citations than an anonymous company.

The future: what comes after 2026?

The development of AI search is only at the beginning. Some trends that are already emerging:

Multimodal search: AI models increasingly process not only text, but also images, videos and audio. Companies that optimise their visual content (product photos, infographics, videos) have an advantage.

Personalised AI answers: AI search engines will increasingly deliver personalised results - based on location, search history and user profile. Local SEO and GEO merge.

Agentic search: AI agents that not only deliver information, but also execute actions (book appointments, order products, request quotes), become more relevant. Companies must prepare their digital infrastructure for this.

Real-time updates: current AI models often have a knowledge gap of weeks or months. This lag will shrink - which means that current, regularly maintained content becomes even more important.

Checklist: AI search engine optimisation for SMEs

Use this checklist as a starting point for your GEO strategy:

Entity foundation:

• Google Business Profile complete and up to date
• NAP data consistent across all platforms
• Organization schema implemented on the website
• Wikidata entry in place
• Industry directory entries up to date

Content optimisation:

• Existing content checked for citeability
• FAQ sections with schema markup on main pages
• Author profiles with proof of expertise
• Clear definitions and numbers in all articles
• Thought-leadership content with original insights

Multi-source presence:

• Active profiles on at least 5 relevant platforms
• Regular customer reviews on Google and trade portals
• At least 2 external mentions per quarter (guest posts, interviews, PR)
• Social media profiles current and active

Monitoring:

• AI citation tracking set up
• Competitor monitoring active
• Quarterly GEO audit planned

Conclusion: AI search engine optimisation is no longer an option - it is a necessity

The question is not whether AI search engines will change the way your customers find you. They already do. The question is whether your company is prepared for it.

90% of SMEs are not. They rely on an SEO strategy developed for a world without AI search. Every day they wait, their competitors build entity authority that is hard to catch up with.

The good news: the measures you take for AI search engine optimisation simultaneously strengthen your classic SEO performance. Consistent data, high-quality content, structured information and a strong multi-source presence - these are factors that count in every search engine, classic or AI-based.

The first step is the most important: understand where you stand today. How visible is your company in AI search engines? What gaps exist? And which measures bring the biggest lever?

Would you like to find out whether your company is recommended by AI search engines - and what you can concretely do to increase your visibility? Arrange a no-obligation initial meeting with Nordsteg - and find out which steps have the biggest impact for your industry and your situation.

Frequently asked questions (FAQ)

Sources

1. Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., & Deshpande, A. (2023). GEO: Generative Engine Optimization. Princeton University. arXiv:2311.09735.

2. BrightEdge (2025). The Impact of AI Overviews on Organic Search Traffic. BrightEdge Research Report.

Further reading: What inaction on GEO really costs you every month