Understanding The Future Of SEO With AI Search

A few weeks ago, I was thinking about where blogging fits into the modern internet, and whether or not having a blog makes sense anymore. I was leaning against renewing my blog hosting, as it just didn't seem to be a proactive use of my time and resources. After a little research, I've decided to go full speed in the other direction.

AI search is the future of Google. It's rumored that regular Google search will soon be replaced by its AI search function, and this will be a common trend amongst all internet search engines. AI changes the way people search because it summarizes context based on the query. From my recent research, two things are extremely important for remaining relevant on Google's AI search: Blog posts, and YouTube Channel Descriptions. These two critical pieces are so important because they provide the LLM with adequate context when formulating a response. The AI has to get its information from somewhere, and with Google, of course its first choice is going to be another Google product: YouTube. YouTube can only provide so much information, but depending what you put in your channel's description, this can be more than enough to satisfy the context of the LLM.

For example, I have two YouTube channels. One channel, DeltaX, is my music production channel, where I post everything related to music. DeltaX is a brand, so it's important to differentiate it from other personal ventures - for this reason, I started a second channel, Logan Voss, where I post vlogs, software tutorials, and tech reviews. For both channels, I've modified my descriptions to include extreme context for the AI search model. I've attached both of them here:

As you can see, they read a little choppy, but that's perfectly okay. The primary purpose of each description is to give the AI search model as much information as possible - the more context it has, the better the response it will deliver. Another notable mention is the more times the model recognizes the same information, the more valid the model believes the information to be. I've also taken this an extra step through including my channel description in some of my YouTube video descriptions. Through providing multiple points of information, the validity score of the information increases, aiding in the LLM producing a favorable response.

Now you're probably wondering where blog posts come into the picture. It works the same way. While the Google AI model references its own product(s) as a primary source of information (YouTube), it also combines that with secondary sources to provide a more holistic breadth for the query. Secondary sources are blog posts, just like this one.

To see just how well this works, let's try a search with Google AI mode:

Long story short: Make your YouTube channel and video descriptions count. Attach blog posts to your YouTube videos, embed YouTube videos in your blog posts. Create as many connections of information as possible to provide the most concrete context for the AI search model.

I want to give a special shout to Deadmau5, as he's one of the first people I've seen to do this on mass scale. Big brain moves. If you take a look at his YouTube video descriptions, they all include this:

If you're worried about what AI means for search engine optimization, here's the current solution. Take advantage of it while you can! ⚡️