Ever since ChatGPT became mainstream, people have been using it and other AI tools like it to test the extent of its knowledge. At first, it was pretty good at recalling general knowledge questions, but its ability to comprehend and write on complex subject matter would often result in pretty inaccurate content.
However, as AI has progressed, it has become far better at doing research and reporting with factual statistics more often than not. In fact, tools like Perplexity AI have been particularly useful in their ability to write content while also being sure to cite sources found on the web when referring to specific data sets or pieces of information.
These advances have made many wonder if there will actually be much use for search engines like Google and Bing in the future. If we can just ask our questions and get direct answers via our AI assistants, then what is the point of trying to find the answer on Google anymore?
This sort of thinking denotes a pretty flawed understanding of the way Google and AI platforms like Claude and ChatGPT work. We’ll break down the inner workings of each to give you a better understanding of where and when each of these tools is going to be most useful.
The library vs the librarian
The best way to think about the difference between AI and Google as a search function is to think of Google as the library and AI as the librarian.
The Library
Google is a collection of websites (books) that people can search through in order to find answers to their problems. These websites contain valuable information that users are looking for, whether it’s recipes on a cooking blog or information about the ongoing trade war between America and China on the New York Times’s website.
When you search for something, Google is able to provide users with the closest possible match to your question based on the keywords you used to make your search, as well as the domain authority linked to the websites that Google has in its archives.
This is basically how search engine optimization (SEO) works. SEO professionals simply give the websites they work on the best possible chance of ranking by aligning the website with specific keywords that searchers might be looking for. Pair this with a high domain authority as a result of reputable backlinks, and your website comes up top to search users.
Google simply hears your request and gives you a bunch of different options where the answer might lie—no different to what a library catalog would do when you ask about history books or books on photography, for example.
The Librarian
AI works a little differently though. Instead of just giving you a bunch of material to look at like Google does, AI is more akin to talking to the librarian. AI isn’t an expert on anything, and by no means should you have AI draw up a business agreement for you without having a professional lawyer at least look it over. AI is simply familiar with material of this nature in the same way a librarian is familiar with Plato’s theory of forms, which she has a passing understanding of after years of stocking the philosophy section of the library.
Because of this understanding of a wide range of topics, AI is able to give far more direct answers, whereas Google just lets you know where to look to get to the answer.
How do I know when to use Google vs AI
So now that you have an understanding of the different roles AI and Google play, you might be wondering when you should use each to get the best results.
The key distinction comes down to the type of question you’re asking. For argument purposes, we can call this difference “single-layer questions vs. multi-layer questions.”
Single-Layer Questions
There will always be a need to reply to questions that have just a single, straightforward answer. Some examples include:
- “What’s the score of the basketball game?”
- “How far is it from LA to New York City?”
- “What’s the weather right now?”
- “When was the Declaration of Independence signed?”
- “What are the symptoms of strep throat?”
All of these questions have one simple answer and are based on fact. There is no need for follow-up questions, as each question and answer stand on their own. Google has largely solved this for many queries with its “OneBox” feature, where you don’t even need to click on a link—it shows the answer immediately at the top of search results.
Google is also superior when you need:
- The most up-to-date information (like news, stock prices, or current events)
- To verify information across multiple sources
- To find specific websites, products, or services
- To see images, videos, or other media related to your query
This approach is efficient for quick information gathering but is not how we normally learn about most topics, especially as they become more complex.
Multi-Layer Questions
Now, let’s consider slightly more complex topics that benefit from a conversation rather than a single answer. Examples of multi-layer questions include:
- “What do I need to do to prepare for climbing Mt. Kilimanjaro?”
- “How do I delete backgrounds in Photoshop?”
- “Is being a vegan healthy?”
- “What’s the best way to start investing with $1,000?”
- “How can I improve my public speaking skills?”
If you Google these questions, you’ll get lots of answers, but then you need to sift through these results and try to find the ones most relevant to you. With AI assistants, you can ask these questions, get an initial answer, and then dig deeper with follow-up questions tailored to your specific situation.
For example, after asking about Kilimanjaro, you might follow up with: “I’m in my late 20s and will be arriving in the Fall with three friends. I’ve also climbed a few 14er mountains before. What preparations should I do specifically?”
Or after asking about Photoshop: “I tried deleting a background, but it wasn’t working. I’m still getting lots of remnants from the initial image. What am I doing wrong?”
This is where AI truly shines—the conversation shifts from “give me the answer” to “let’s have a dialogue.” The AI can remember context from previous questions, tailor its responses to your specific situation, and help you navigate complex topics in a more natural, human-like way.
