AI-friendly Websites

The future of visibility lies not in search engines – but in AI responses.
Anyone planning or running a website today must confront a new reality: content is no longer just indexed by Google, but increasingly processed by AI systems. Voice assistants, chatbots, generative response systems like ChatGPT or Perplexity – they all access websites to provide users with direct answers. To make content accessible for AI systems, a classic SEO strategy alone is often no longer sufficient.

Technical optimisation
Content clarity
Semantic structuring
GEO (Generative Engine Optimisation)
AEO (Answer Engine Optimisation)

1. Technical Requirements:

Structured, fast and accessible

For content to be reliably captured by search engines and AI systems, a solid technical foundation is required. This is not only about performance but also about how easily content can be interpreted. Some metrics may not be directly crucial for AI crawlers, but they serve as indirect signals for page quality and visibility – thus influencing the chances of being considered in AI responses.

a) Accessibility and Crawlability
Search engines and AI crawlers require clearly accessible structures:

A correctly configured robots.txt and – if possible – a supplementary llms.txt to allow AI systems access to the content.
A flat, well-thought-out site architecture that makes all important content easily reachable.
Preferably server-side rendered content based on HTML – rather than solely relying on JavaScript-based rendering.

b) Performance and Loading Speed
User experience and machine processing benefit from fast loading times:

Ideally, the LCP value (Largest Contentful Paint) should be under 2.5 seconds.
Responsive design and the avoidance of unnecessary JavaScript load create advantages on mobile devices.
Techniques such as caching, the use of a Content Delivery Network (CDN), image compression, and lazy loading help to measurably improve performance.

c) Indexing & Sitemaps
For content to be correctly categorized and indexed:

An always up-to-date XML sitemap should be available and submitted to Google Search Console.
The use of canonical tags helps to avoid duplicate content and clarify attribution.

2. Content and structure:

Clarity for users and machines

Not only what is said, but how it is structured determines visibility on the web – especially when AI models are supposed to pick up and share content.

a) Clearly structured content
A logical, readable structure makes it easier for both humans and machines to navigate:

Headings with a clear hierarchy (H1–H3).
Short, precise paragraphs.
Key messages at the beginning – following the journalistic principle: “Most important first”.

b) Thematic depth through content clusters
A smart linking of related content not only increases dwell time but also creates a semantically strong overall picture:

Logically link main topics with corresponding subpages or posts
Consistent internal linking to establish context

c) Trustworthiness and relevance
Search engines – and increasingly AI systems – evaluate content based on how credible and well-founded it is:

Statements should, where appropriate, be supported by reputable sources.
Make authorship and expertise visible – e.g. through author profiles, expert quotes, or original studies.

Despite all the requirements for structure and machine readability, the content itself remains the most important factor: Those who provide their own reliable data sources, treat topics with professional depth, and formulate in a brand-compliant and user-oriented manner not only create relevance for AI systems but also increase the value for human visitors.

3. Semantic Markup and Structured Data

AI systems "read" content differently than humans: They rely on structured cues to understand the meaning and purpose of a page. Semantic markup helps make information machine-readable.

Important formats & use cases

FAQ page for pages with frequently asked questions.
Article, Product, Organization – depending on the type of content.
Implementation as JSON-LD within the HTML code.

4. GEO (Generative Engine Optimization)

With the rise of AI-driven search systems like ChatGPT, Perplexity, or Claude, the way digital content is found and used is changing. In addition to traditional indexing by search engines, another aspect is coming into focus: content that is formulated in such a way that it can be directly recognized, understood, and integrated into responses by generative systems.

What does GEO mean?
GEO stands for Generative Engine Optimization – an approach aimed at structuring and formulating content so that it can be reliably picked up by AI systems. This is less about technical tricks and more about clarity, structure, and content relevance.

GEO in practice:

Use clear formulations: Specific terms, clear statements, understandable language style.
Incorporate questions and answers: Design content to cover typical user questions.
Context over keywords: Instead of focusing on keyword density, a natural, well-structured conversational style is helpful.
Think thematically: Cluster content meaningfully to clarify connections – both for users and for AI systems.

GEO is not a replacement for SEO, but an evolution – with the goal of making content visible in dialogue-based applications as well. Those who pay attention early on to how information will be processed in the future will secure a tangible advantage in the digital competition.

5. AEO (Answer Engine Optimization)

While GEO aims to make content understandable and citable for AI systems, AEO (Answer Engine Optimization) adds an important dimension to this approach: the trustworthiness and discoverability of a website outside its own page structure. It is about being recognised as a reliable source – and being specifically mentioned in responses from AI models.

What is meant by AEO?
AEO includes measures that help a website to be classified by AI systems as a relevant, credible entity. Many language models rely on interconnected, external knowledge sources when answering questions – particularly where structured information and public references are available.

Important AEO measures:

Create or maintain a Wikidata entry: Many Large Language Models (LLMs) refer to Wikidata to clearly associate entities (such as brands, places, or organisations). A well-maintained entry creates relevance and machine anchoring.
Presence on open, referable platforms: Profiles on platforms like Wikipedia, LinkedIn, business directories, or industry portals contribute to digital credibility – especially when they are consistently maintained.

Digital Visibility Reimagined Conclusion:

Search engines and information behaviour are changing – and with them, the requirements for websites. In addition to classic SEO, new factors are coming into focus:

A solid technical foundation: fast, mobile-friendly, well-structured.
Content that is not only easy to read but also structured and machine-readable.
Texts that can be cited and used by AI systems (GEO).
Reliable information that can be found through structured data and trustworthy sources (AEO).

At haj.tech, we develop websites that meet these requirements – functional, user-centred, and future-proof.

This creates a digital presence exactly where your target audience finds answers today:
In the systems that are already thinking ahead.