Schema.org: Structured data markup as a bridge between content and future AI technologies

There was an interesting discussion on Twitter recently, inspired by an article by Jono Alderson. He suggests considering Schema.org structured data markup as a way to help new AI technologies better understand and discover published content on the Internet.

Content on a website is called "unstructured data" because it does not have a formally organized structure that contains labels for each part of it in a machine-readable format.

Structured data is the same content, but organized with tags that identify images, authors, and content so that a machine can immediately understand it.

🚀 Schema.org structured data markup is commonly seen by publishers and the SEO community as a tool that makes a web page Google-friendly. However, new AI technologies that can use structured data require search marketers to take a new approach to implementing structured data.

• 📌 The article suggests looking at Schema.org markup as a way to communicate what a web page is about and how it relates to everything else on the website.
• 📌 Jono writes, "Don't avoid creating a connected graph of broader, 'descriptive' schemas just because Google doesn't immediately show the impact. These 'descriptive' types and relationships can be the bridge between your content and the AI ​​models of the future."