Published on: May 18, 2025 / Updated on: May 18, 2025 – Author: Konrad Wolfenstein
Google search is becoming an answer engine: What this means for you and the web – Image: Xpert.Digital
The fundamental shift: Answer engines instead of web search – the end of links? Zero-click alert with AI search engines
Direct answers instead of link lists: How AI is changing your search behavior (and what Google is planning)
For over two decades, traditional search engines like Google have dominated how we search for information online. But we are in the midst of a fundamental paradigm shift: AI-powered answer engines are revolutionizing traditional link searches. These systems deliver direct, comprehensive answers instead of simply linking to relevant websites. The transformation from search engines to answer engines is not only changing user behavior but also has far-reaching consequences for the entire web ecosystem.
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The evolution: From link list to direct answer
The basic idea behind answer engines like Perplexity AI is simple yet revolutionary: Instead of entering search terms and receiving a list of links, users can ask questions in natural language and receive direct answers. This development marks a significant advancement in the way we interact with the internet.
The beginnings of change
For years, Google has been evolving from a pure search engine into an answer engine. With features like Knowledge Panels (2012), Featured Snippets (2014), and Quick Answers (2014), the search engine giant increasingly tried to answer user questions directly on the search results page. This was the beginning of a trend that received an enormous boost with the advent of advanced AI models.
The AI-driven breakthrough
The real breakthrough came with the development of powerful Large Language Models (LLMs). In 2017, a technological advancement was achieved with transformer models that could quickly and efficiently search large amounts of data on a semantic basis. This technology made it possible not only to search content for keywords, but also to actually understand the semantic meaning and generate context-aware answers.
How AI answer engines work
AI search engines primarily rely on two advanced technologies: Natural Language Processing (NLP) and Machine Learning (ML), which enable a completely new way of processing information.
Natural Language Processing
NLP enables search engines to understand complex search queries written in natural language. Users no longer need to reduce their questions to simple keywords, but can formulate them directly and naturally. For example, an AI search engine can provide a detailed answer to a complex question like "How can I increase my brand's presence in AI-generated content?", whereas traditional systems often deliver inadequate results in such cases.
Machine Learning
Machine learning ensures that AI search engines continuously learn from user behavior and automatically optimize their results. This allows these systems to deliver context-sensitive and personalized answers in real time, based on the entire diversity of the internet. Search results are becoming increasingly multimodal, enhanced by the addition of visual and auditory content.
Two main approaches to AI search
Two main approaches to AI-powered search engines have emerged:
- LLM with web search: Systems like Perplexity or ChatGPT with web search retrieve current information from the internet and process it into a summary answer.
- Search engines with AI summaries: Google is testing AI-generated summaries with Gemini, which are integrated directly into the search results. These so-called “AI Overviews” are intended to shorten the search process and make it more efficient.
Overview of leading AI answer engines
Perplexity AI
Perplexity combines a Google-style search engine with a chat interface similar to ChatGPT. Users can ask questions in natural language and receive a specific answer in text form with linked sources. This dialogue allows users to acquire the desired knowledge without having to click through numerous websites.
ChatGPT with Web Search
OpenAI has extended ChatGPT with a search function that enables direct internet searches. The results are completely ad-free and highly concise, with informative summaries generated via the language model.
Google SGE (Search Generative Experience)
Google is responding to the competition with its “Search Generative Experience” (SGE), which has been active in the US as “AI Overviews” since 2024. These AI-generated summaries appear above the organic search results and increasingly integrate videos and images. SGE introduces three key new elements: AI Snapshot, Conversational Mode, and Vertical Experiences.
Microsoft Copilot and Bing
Microsoft has massively revamped its Bing search engine, giving AI-generated results prominent placement. The new “Generative Bing Search” displays AI-generated results on the left, while traditional search results are placed in a narrower column to the right.
Zero-click searches: The changing user behavior
One of the most significant effects of answer engines is the increase in so-called “zero-click searches” – search queries in which users no longer visit external websites.
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Alarming statistics
Recent studies show that only one in three searches now leads to clicks on websites. In the US, nearly 60% of mobile and desktop searches end without a click on a search result. Even more worrying: Almost 30% of all clicks go to platforms owned by Google itself, such as YouTube or Google Maps.
AI amplification of the trend
The introduction of AI-powered response engines significantly reinforces this trend. A UX study on the use of Google's "AI Overviews" shows that these drastically reduce the number of outgoing clicks – on desktop, the click-through rate to external websites drops by two-thirds, and on mobile devices by almost half.
User trust and demographic differences
Younger users and those with a high affinity for digital media are particularly likely to trust AI answers. Users between 25 and 34 years old accept AI answers as the final answer in half of all search queries. Mobile users scroll further (54 percent) than desktop users (29 percent), while older users still prefer classic blue links.
Consequences for website operators and publishers
The shift towards answer engines has far-reaching consequences for the entire web ecosystem, especially for website operators and publishers.
Traffic losses and dependency
Zero-click searches are causing websites to lose massive amounts of traffic. The changed search landscape is leading to an even greater concentration of power among platform operators like Google and Meta, and potentially also Apple in the future. Publishers, whose business model depends on people directly accessing their websites, are particularly affected.
New metrics for success
In the context of this development, new key performance indicators (KPIs) need to be developed. The study on Google's AI Overviews recommends measuring visibility rather than clicks. The crucial factor will be how often and how prominently a brand appears in AI-generated responses. Metrics such as citation rank or "share of voice" will become more important than traditional ranking positions.
Different impacts depending on the industry
The impact of AI-generated answer engines varies depending on the industry and topic. For search queries involving personal risk—such as health or finance—users are significantly more skeptical of AI-generated answers and scroll further or seek additional sources. For simple questions or definitions, however, AI answers are more often accepted without further research.
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Future prospects: Strategies in a new search world
Despite all the challenges, the shift from search engines to answer engines also offers opportunities. However, website operators and content creators need to adapt their strategies.
From SEO to GEO (Generative Engine Optimization)
Optimizing for AI-powered search engines could evolve into a new discipline that goes beyond traditional SEO. The goal is no longer just to rank well in search results, but to be cited as a trustworthy source in AI-generated answers.
Focus on quality and trustworthiness
The UX study on Google AI Overviews shows that when selecting a source, users first check whether it is trustworthy – only then do they consider whether the information matches their search intent. In 58 percent of cases involving well-known brands or .gov/.edu domains, these were clicked first. Establishing oneself as a trusted brand is therefore becoming even more crucial.
Multimodal content is gaining in importance
When it comes to DIY questions, many users deliberately skip AI-generated answers to watch videos with practical demonstrations instead. The average viewing time for videos (37 seconds) exceeds that for AI answers (31 seconds). This underscores the increasing importance of multimedia content.
A new era of information gathering
The shift from search engines to answer engines marks a fundamental transformation in how we search for and consume information online. While this development promises users faster and more direct answers, it presents website operators and content creators with new challenges.
The future of web search will be defined by a balance between the efficiency of AI-generated answers and the need for trustworthy, in-depth information. Competition among major players like Google, Microsoft, and OpenAI will further drive this development.
For website operators and content creators, this means rethinking their strategies: away from simply optimizing for search engine rankings and towards establishing themselves as a trusted source for AI systems. Quality, trustworthiness, and multimodal content will be crucial factors in this new era of digital information gathering.
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