What AI search engines are and how they differ from Google

AI search engines - ChatGPT (with Browse and Search), Perplexity, Google AI Overview, Microsoft Copilot and others - represent a new search paradigm. Unlike traditional Google, which shows a list of 10 links, AI engines aggregate information from multiple sources and deliver a direct, synthesised answer.

This means a fundamental shift in SEO strategy. In traditional SEO the goal is to get into the top 10. In AI engines the goal is to become a source the AI cites in its answer.

Key differences

Why AI SEO matters right now

Through 2025-2026, the number of AI search users is growing fast. Perplexity handled more than 100 million queries per month at the end of 2025. ChatGPT with Browse is used by millions of users daily. Google AI Overview already appears in a large share of search queries.

Businesses that ignore AI SEO do not risk losing visibility in traditional Google search (that still works as before) - they risk becoming completely invisible in the new search channel, where more and more potential customers look for information.

How AI engines choose sources

AI models do not rank pages the way Google does. Source selection is based on different principles:

1. Content structure and citability

AI engines find it easier to cite content that is:

2. E-E-A-T signals

AI engines evaluate source trustworthiness and expertise. Important:

3. Technical accessibility to AI crawlers

AI engine crawlers (GPTBot, PerplexityBot and others) are different from Googlebot. Make sure:

llms.txt - the new standard for AI engines

llms.txt is a new, growing industry standard that helps AI engines understand your site's content. It works like robots.txt but for AI.

What llms.txt is

llms.txt is a text file at the root of your site (for example, jkonsult.lv/llms.txt) that contains:

Why it matters

While Google Ads and organic SEO have been well-documented channels for more than a decade, AI search optimisation is new territory. llms.txt is one of the first concrete steps companies can take to make their site AI-friendly.

Structured data optimisation for AI engines

Schema.org structured data is even more important in the AI context than in traditional SEO. The reason: AI engines often use structured data to understand content context and facts.

Priority schema types for AI SEO

Creating citation-friendly content

AI engines cite content that is easy to "snip" and place into an answer. Practical guidelines:

Write definitions and one-sentence answers

At the start of each article or section, give a direct, concise answer to the question. Example:

"SEO optimisation is the process of improving a website to raise its positions in Google search results."

This kind of sentence can be cited directly by an AI engine.

Use Q&A blocks

Integrate a question-answer format throughout the content, not only in the FAQ section. AI engines often extract these pairs specifically.

Provide unique data and opinions

AI engines prefer sources that offer something others do not:

Google AI Overview - how to appear

Google AI Overview (formerly SGE - Search Generative Experience) is the AI-generated answer at the top of Google search results. To get your content cited:

Perplexity optimisation

Perplexity is one of the fastest-growing AI engines. It actively cites sources and provides links. To get cited by Perplexity:

ChatGPT Browse and Search optimisation

ChatGPT with Browse and Search can visit and cite your site in real time. Optimisation principles:

JKonsult's AI SEO experience

JKonsult has actively integrated AI SEO into its service offering since 2024. Our approach:

  1. AI visibility audit - we check whether your site is visible in AI engines and whether crawlers can access it
  2. llms.txt implementation - we create and optimise the llms.txt file
  3. Content restructuring - we rework content into a citation-friendly format
  4. Schema.org expansion - we implement additional structured data for AI
  5. Monitoring - we track how AI engines cite your content

AI SEO is not a replacement for traditional SEO - it is an additional channel. The best strategy is a strong traditional SEO foundation + AI-specific optimisation on top.

Learn more about JKonsult SEO services, which include AI search engine optimisation.

Measuring AI engine traffic

One of the biggest challenges with AI SEO is measuring traffic. Unlike Google organic traffic, which can be tracked precisely with Google Analytics and Search Console, AI engine traffic is often not clearly identifiable.

How to track AI traffic

Metrics to track

AI SEO strategy by business type

AI SEO is not equally important for every business. Here are the priorities by business type:

B2B service companies - high priority

B2B decision makers increasingly use AI tools for research before a purchase decision. If you offer consulting, SaaS solutions or professional services, AI SEO is critical. Your expertise content needs to be structured so that AI cites it when a potential client asks "best [your service] in Latvia".

E-commerce - medium priority

AI engines currently handle informational queries better than product searches. However, product comparisons and "best [product] 2026" queries are becoming more common in AI engines. Optimise comparison content and product category pages.

Local service businesses - lower priority (for now)

Local search ("plumber in Riga") still happens mostly on Google with Maps integration. AI engines handle these queries less effectively. Focus on Google Business Profile and traditional local SEO, but prepare the site for AI's future with structured data and llms.txt.

Future outlook - what to expect in 2026-2028

The AI search landscape is changing very fast. Based on current trends, our predictions:

Main recommendation: do not wait until AI SEO becomes "mandatory". Companies that start optimising now will gain an advantage over those that wait another 2-3 years.

Related resources

Jānis Kursītis
Jānis Kursītis CEO, JKonsult · Google Ads expert since 2008 · SEO strategist
"When a client first asked me how to show up in ChatGPT answers, I had to rethink every SEO fundamental. What matters in AI engines is not keyword density, but source trustworthiness."

← All articles