Optimization of content for AI-supported search and digital assistants

Jed White provided important insights into how to deal with AI search in his article on Search Engine Land. The increasing integration of artificial intelligence into search engines and digital assistants is changing the way content is found, processed and presented. While conventional SEO strategies continue to be important, new optimization methods that are specifically geared to AI-supported search systems are becoming more relevant. To ensure that content is successful in this changing search landscape, companies and website operators should make targeted adjustments.

One example that many people have surely noticed is the increasing number of AI summaries appearing on websites, in search results or shops. Some of these have already been rolled out in Europe.

Amazon summarizes user ratings in a concise and straightforward way, making it quicker and easier to decide whether to buy something.

Differences between traditional SEO and AI-based search

Until now, the focus of search engine optimization (SEO) was on the use of relevant keywords, the quality of backlinks and the optimization of technical factors such as loading times and mobile user-friendliness. However, AI-based search systems set different priorities. Machine learning is used to analyze and evaluate content, thereby changing the criteria for high visibility.

One crucial difference is the way AI search engines retrieve and interpret content. AI-powered systems favor clearly structured content that is provided in an easily accessible format. While traditional search engines crawl and index HTML pages, AI systems additionally use large language models (LLMs) that extract information and reflect it in personalized search results.

Furthermore, the speed of data processing must be kept in mind. Many AI search systems operate under strict time constraints, which is why slow or difficult-to-access content may not be considered.

Optimization strategies for AI search systems

To successfully optimize content for AI-supported search systems, various adjustments should be made. First of all, webmasters should not exclude the bots. The disadvantage of doing so is that the AI bots cannot access the content and these pages cannot be used as a source for an AI search or as a basis for information.

If OBI were to prohibit the bot from reading the website in this case, the company would be at a major disadvantage. Users searching in this way would not find a major player.

In addition to this basic principle, there are of course further technical aspects that need to be taken into account, which Jed has analyzed in more detail.

Provide clear and structured content

AI search systems prefer well-structured texts written in clean HTML or Markdown. Nested or confusing content can lead to important information not being interpreted correctly. A logical arrangement of headings, paragraphs and lists facilitates processing by AI algorithms.

Particular attention should be paid to avoiding unnecessary JavaScript elements. Many AI crawlers have difficulty capturing content that is only loaded by JavaScript. If interactive or dynamic content is required, it should be checked whether it can also be made accessible in a static form.

Ensure fast loading times

A high loading speed is a central cornerstone, as AI crawlers often work with limited time. Slow websites or content that takes a long time to load can be excluded from the indexing process.

To optimize loading time, unnecessary scripts should be reduced, images compressed and an efficient server cache set up. Content should be placed as close to the top of the page as possible so that AI crawlers can immediately capture the most important information.

Use metadata and semantic markup

Metadata helps AI-based search engines to understand content. With structured markup such as schema.org, you can clearly define the content and highlight relevant information.

The following measures should be considered:

• Meaningful titles and descriptions: Precise wording helps AI systems to better categorize content.
• Date labeling: Up-to-date information can be given preferential treatment if the publication date is correctly labeled.
• Semantic HTML tags: The use of <article>, <header>, <section> and <aside> can help to make the structure more understandable for AI systems.

Ensure accessibility for AI crawlers

To enable AI-powered search engines to capture content, technical hurdles must be avoided. Robots.txt files or firewall rules should be regularly reviewed to ensure that they do not inadvertently block access for AI crawlers.

Particular attention should be paid to the configuration of bot protection systems. Security measures such as reCAPTCHA or aggressive DDoS protection mechanisms can cause AI crawlers to lose access to content.

Creating a llms.txt file

A new concept in AI optimization is the use of a llms.txt file. This file allows website owners to provide specific instructions for AI models, such as which content to prioritize or ignore. Similar to robots.txt, llms.txt can help to control visibility in AI search systems in a targeted manner.

Emphasize authenticity and human perspectives

With the increasing prevalence of AI-generated content, the importance of authentic, human voices is growing. Users and search engines are increasingly valuing content created by real people that reflects personal experiences or expertise. It also remains to be seen how this user-generated content (UGC) will be viewed in this context.

Platforms characterized by human moderation and real discussions are becoming more important. Content written by experts and enriched with in-depth knowledge has a better chance of being preferred by AI search systems.

It is becoming increasingly important that authors or experts are clearly identifiable. Author pages with references to publications, social media profiles or academic qualifications can strengthen trust in the content.

Future developments in AI search

The integration of generative AI into search engines is progressing rapidly. Google recently announced several updates designed to improve and personalize AI-powered search results. New features such as grouping search results into categories or interactive widgets change the way content is displayed and evaluated for relevance.

These developments underscore the need for continuous content adaptation and adjustment to new algorithms. Content must therefore be optimized for AI search systems at an early stage. It is also more important than ever to keep your content up to date so that the AI bots can pass on relevant content to users.