Google under fire: why users are massively switching to AI search
A tectonic shift is brewing within the crypto community and beyond: users are increasingly abandoning traditional search engines in favor of neural networks. Google and its counterparts are rapidly losing ground, making way for chatbots that people query directly. This is not just hype—it's a real paradigm shift in how we interact with information.
The trend is so significant that it has sparked a wave of active discussions on social media. We decided to explore the roots of this phenomenon and whether there is any practical sense in completely replacing classic search with artificial intelligence.
How It All Started
The spark for the conversation was ignited by a user under the handle Carlos That Notices Things. He claimed that Google has degraded to the point where searching for information through Grok has become noticeably more convenient. This thesis was immediately picked up by American blogger and political commentator Mike Cernovich, who said that several months ago he made Grok his primary search engine. Google, according to him, is now only used for spell-checking and minor edits—tasks for which Grok works slower. In everything else, Cernovich believes, Grok surpasses Google.
Cernovich's post was retweeted by Elon Musk. The context here is critically important: Grok is developed by xAI, a company founded by Musk himself, so he has a direct interest in promoting the product. But even considering this factor, users' arguments are becoming increasingly convincing.
How Neural Networks Objectively Outperform Search Engines
AI search has several undeniable advantages over classic search results. Here are the key differences of the new technology:
- Ready answer instead of a list of links. Instead of opening a dozen tabs and manually filtering out junk, the user receives a formulated conclusion. If necessary, the system provides links to sources.
- No ad-filled results. Classic search engines fill the top of the page with sponsored results, whereas a chatbot responds strictly to the essence of the query. Users are no longer annoyed by paid links.
- No intrusive retargeting. After searching for a product in a regular system, a user is haunted by contextual ads for weeks. A dialogue with a neural network leaves no such trace.
- Understanding complex and vague queries. AI can parse a task description, clarify details, and find a solution. A regular search engine requires precise keywords. Meanwhile, advanced models handle multiple queries simultaneously and consolidate the results.
- Additional scenarios. Beyond search, neural networks effectively cover related tasks—from analyzing long texts to managing large projects.
The Flip Side: Weaknesses of AI Search
| Comparison Criteria | Classic Search (Google) | Search via Neural Networks (AI) |
| Data Reliability | High (verification of primary sources) | Possible fact fabrication (hallucinations) |
| Image Search | Fast and convenient | Currently lags in volume and quality |
| Current Events | Reflected almost instantly | May update with a delay |
| Cost and Limits | Completely free, no restrictions | Basic mode is limited, requires a subscription |
The tendency to fabricate facts remains the main problem with AI. Critically important information has to be double-checked. This is a fundamental flaw that has yet to be resolved.
User Opinions: The Battle for the Future of Search
A heated debate erupted under the posts of discussion participants. Proponents of the switch describe the same scenario: tried it—and almost stopped using Google. The main arguments: no ads, the convenience of a ready-made answer, and AI's ability to find products based on a loose description. Some users note that even experienced internet veterans have stopped using Google as their default search engine.
Skeptics offer substantive counterarguments. Many believe that neural network search still has many limitations, and switching search engines is premature until AI proves its superiority in practice. Complaints include that AI answers can also be false, and voice search provides incorrect information.
A separate grievance is the cost and limits. Free access is restricted to a small number of queries per day and requires a subscription, whereas traditional search is free.
A notable portion of the audience points to alternatives to Grok—from Gemini and Perplexity to Claude. They emphasize that the choice is not simply a matter of "Google versus one neural network."
My analysis: AI search indeed addresses several pain points of classic search engines, but it has not yet become a universal replacement. A sensible approach is to combine tools for specific tasks and maintain the habit of double-checking important facts. The search technology market is entering an era of hybrid solutions, and the stakes here are higher than they might seem at first glance.