Google under fire: why users are massively switching to AI search
The search engine market is undergoing a tectonic shift. More and more users are abandoning traditional search engines in favor of neural networks. Google and its counterparts are gradually giving way to chatbots, which people query directly, bypassing the classic list of links.
The trend is so noticeable that it has sparked a wave of active discussions on social media. I conducted my own analysis to understand the objective reasons for this phenomenon and to assess whether there is real practical value in replacing traditional search with artificial intelligence.
Where the debate began
The discussion was started by a user under the handle Carlos That Notices Things. He claims that Google has degraded to the point where searching for information through Grok has become frankly more convenient. This point was picked up by American blogger and political commentator Mike Cernovich. He said that several months ago he made Grok his primary search engine. According to him, he now only uses Google to check typos and spelling, since Grok is slower for such minor tasks. In Cernovich's opinion, Grok surpasses Google in every way.
Cernovich's post was retweeted by Elon Musk. Context is important here: Grok is developed by xAI, a company founded by Musk himself, so he has a direct interest in promoting the product. However, this does not negate the objective advantages of AI search.
How neural networks can surpass search engines
AI search has several objective advantages over classic search results. Here are the key differences of the new technologies:
- Ready answer instead of a list of links. The neural network provides a formulated conclusion, rather than ten tabs for manually sifting through clutter. If necessary, the system also provides links to sources.
- No ad-filled results. Classic search engines fill the top of the page with sponsored results, whereas the 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 search engine, a person is pursued 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 at once and consolidate results.
- Additional scenarios. Beyond search, neural networks effectively cover related tasks—from analyzing long texts to managing large projects.
Weaknesses of AI search
| Comparison criterion | Classic search (Google) | Search via neural networks (AI) |
|---|---|---|
| Data reliability | High (verification of primary sources) | Possible fabrication of facts (hallucinations) |
| Image search | Fast and convenient | Still 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, subscription required |
The tendency to fabricate facts remains the main problem with AI, so critical information has to be double-checked.
What users think
Under the posts of discussion participants, a debate flared up about the feasibility of switching from search engines to AI.
Supporters of the switch describe a similar scenario: tried it—and almost stopped using Google. The most common arguments include the absence of ads, the convenience of a ready answer, and AI's ability to find products based on a loose description. Some users note that even experienced internet regulars have stopped using Google as their default search engine.
Skeptics offer substantive counterarguments. Some users believe that neural network search still has many limitations and that switching search engines is premature until AI proves its superiority in practice. Complaints are voiced 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 note that the choice is not limited to the "Google versus one neural network" thesis.
My analysis shows: AI search indeed addresses several pain points of classic search engines, but it has not yet become a universal replacement. A reasonable approach is to combine tools for specific tasks and maintain the habit of double-checking important facts. The market is entering a phase of hybrid use, and the winner will not be a single tool, but an ecosystem capable of integrating both approaches.