SearchGPT and other AI search engines: a comparison
The new search landscape: more than just Google
The time when Google held an undisputed monopoly on online search is coming to an end. In 2025 and 2026, a new ecosystem of AI search engines has emerged that operates fundamentally differently from the traditional list of ten blue links. These platforms generate direct answers based on sources they retrieve, summarize and synthesize in real-time. For website owners, this means visibility no longer depends on a single search engine, but on a portfolio of AI platforms.
This is the core of Answer Engine Optimization: optimizing your content so that multiple AI systems select it as a source. Each platform has its own algorithms, its own preferences for sources and its own ways of presenting answers. An effective AEO strategy accounts for all these platforms.
In this article, we compare the most important AI search engines of today. We analyze how each platform selects sources, how they present answers and what implications this has for your content strategy.
The AI search landscape is changing rapidly. The information in this article is based on the state of affairs in April 2026. Always check the most recent documentation of each platform for current details.
SearchGPT: OpenAI's direct search challenger
SearchGPT is OpenAI's answer to the question of how to combine the power of GPT models with real-time web search. The platform, which is integrated into ChatGPT, combines the conversational interface of a chatbot with the information density of a search engine.
What distinguishes SearchGPT is the seamless integration with the GPT ecosystem. Users can search, ask follow-up questions and dive deeper within the same conversation. Search results are not presented as a separate list but woven into the conversational answer. Sources are displayed as footnotes with direct links to the original pages.
- Retrieval method: real-time web search combined with a proprietary index that is regularly updated.
- Source presentation: inline citations with footnote numbers and a source list at the end of the answer.
- Strengths: conversational follow-up, integration with GPT plugins and tools, broad knowledge base.
- Considerations: can sometimes show outdated cached results, preference for English-language sources.
- Crawler: GPTBot (user-agent: GPTBot/1.0). Respects robots.txt.
Perplexity: the source-focused AI search engine
Perplexity has positioned itself as the alternative that puts transparency at its center. Where other AI search engines sometimes treat sources as an afterthought, Perplexity makes source attribution a core component of every answer. Each claim is linked to a specific source, and sources are prominently displayed alongside the answer.
For website owners, Perplexity is particularly interesting because the platform offers the most transparent source attribution of all AI search engines. If your content is cited, it is directly visible to the user as a clickable link. This makes Perplexity the AI search engine with the most direct referral to the original source, something we discuss extensively in our article about how each model uses your content.
- Retrieval method: real-time web search for every query. No cached answers.
- Source presentation: prominent source cards with URL, title and summary alongside the answer.
- Strengths: maximum source transparency, real-time data, good support for technical questions.
- Considerations: more limited conversational depth than SearchGPT, smaller user base.
- Crawler: PerplexityBot. Fetches pages in real-time for every search query.
Google AI Overviews: the built-in AI layer
Google AI Overviews (formerly Search Generative Experience or SGE) is Google's response to the AI search revolution. Instead of launching a separate product, Google added an AI layer on top of existing search results. When Google determines that a query benefits from an AI-generated answer, a summary appears above the traditional search results.
The impact of AI Overviews on website traffic is considerable, as we analyzed in our article about Google AI Overviews. The platform combines the enormous scale of Google's search index with generative AI capabilities, giving it the largest potential impact on web traffic of all AI search engines.
- Retrieval method: Google's existing search index combined with AI synthesis.
- Source presentation: clickable links in the margin of the AI overview.
- Strengths: enormous reach (billions of searches per day), integration with existing search results, local results.
- Considerations: selective (not for every query), limited publisher control over citation.
- Crawler: Googlebot. The same crawler as for regular search results.
You.com, Brave Search and other players
Besides the three major platforms, there are various smaller AI search engines that each serve their own niche.
You.com offers a multimodal search experience with different "modes" for users to choose from: a chat mode for conversational answers, a research mode for in-depth investigation and a create mode for content generation. For technical professionals and researchers, You.com is an attractive alternative due to its customizability.
Brave Search integrates AI answers into its privacy-focused search engine. The platform attracts users who value privacy and do not want tracking. Brave's AI answers are based on a proprietary index, without dependence on Google or Bing.
Other emerging players include Kagi (a paid search engine with AI features that avoids advertisements), Phind (focused on developers and technical questions) and Arc Search (mobile-first with a focus on fast, visual answers).
# AI search engine comparison overview (April 2026)
Platform | Retrieval | Sources | Reach | Strength
----------------|------------- |----------- |----------- |-----------------------
SearchGPT | Real-time | Footnotes | Large | Conversational
Perplexity | Real-time | Prominent | Medium | Source transparency
Google AI Overv | Search index | Sidebar | Very large | Scale and reach
You.com | Hybrid | Inline | Small | Customizability
Brave Search | Own index | Compact | Medium | Privacy
Kagi | Own index | Detailed | Small | No advertisements
Phind | Real-time | Code-focus | Niche | Technical depthImplications for your content strategy
The fragmented AI search landscape requires a content strategy that does not depend on a single platform. The basic principles of good AEO apply to all platforms, but there are nuances that can refine your approach.
- Ensure your content is technically accessible to all crawlers. Check your robots.txt for rules regarding GPTBot, PerplexityBot, ClaudeBot and other AI crawlers.
- Write content that is factual, structured and source-based. This is the common denominator for all AI search platforms.
- Implement comprehensive Schema.org markup. Google AI Overviews relies heavily on structured data; other platforms benefit from it as well.
- Publish in both Dutch and English to maximize your reach across platforms. SearchGPT and Perplexity have better English-language coverage.
- Monitor your visibility on multiple platforms. Regularly test whether your content is cited in SearchGPT, Perplexity and Google AI Overviews.
- Diversify your traffic sources. Do not rely on a single platform for your AI visibility.
Learn more: Google AI Overviews and search results | How each model uses your content | What is AEO?
The winner in the AI search era is not the website that optimizes best for one platform. It is the website that is consistently selected as a reliable source, regardless of which platform processes the query.
Summary
- The AI search landscape is fragmented: SearchGPT, Perplexity, Google AI Overviews and various smaller players compete for users.
- Each platform has its own retrieval method, source presentation and strengths that influence your strategy.
- Perplexity offers the best source transparency, Google AI Overviews the largest reach and SearchGPT the best conversational experience.
- A platform-independent content strategy based on factuality, structure and technical accessibility is the best approach.
- Monitor your visibility on multiple platforms and diversify your traffic sources.
Frequently asked questions
Which AI search engine has the largest market share?
Google AI Overviews has by far the largest reach, simply because it is integrated into Google Search, which processes billions of searches per day worldwide. Perplexity and SearchGPT are growing rapidly but are still considerably smaller in total search volume. However, exact market shares are shifting quickly and are highly dependent on region and type of search query.
Do I need to optimize separately for each platform?
The basic principles of good AEO are universal: factual, structured, machine-readable content with strong authority signals. This works for all platforms. The nuances lie in details such as which crawlers you allow, how you deploy Schema.org markup and whether you publish an llms.txt file. In practice, 80 percent of your optimization effort is platform-independent.
Is AI search replacing the traditional search engine?
At this moment, AI search is a complement to traditional search, not a replacement. Many users switch between both forms depending on their query. Simple factual questions are increasingly being asked to AI. Complex comparisons, local searches and transactional queries remain the domain of traditional search engines for now. The expectation is that the share of AI search will steadily grow, but that traditional search will not disappear quickly.
How do I measure my visibility in AI search engines?
There are still limited standardized tools for measuring AI visibility. The direct method is to regularly ask relevant questions to each platform and check whether your content is cited. Automated monitoring can be done through APIs from Perplexity and SearchGPT. Additionally, you can analyze server logs for crawler visits from GPTBot, PerplexityBot and other AI crawlers as a proxy for your indexing status.
Is it worthwhile to create specific content for AI search engines?
It is not worthwhile to create content intended only for AI search engines. The most effective approach is content that serves both human readers and AI systems. Factual, well-structured content that answers questions is by definition valuable for both audiences. What you can do is add technical layers that are specifically for AI (Schema.org, llms.txt, robots.txt rules) without affecting the human reading experience.
The AI search landscape is a marathon, not a sprint. The platforms that are dominant today may be challenged tomorrow. Invest in fundamental content quality that works independent of any platform.
How does your website score on AI readiness?
Get your AEO score within 30 seconds and discover what you can improve.
