Artificial intelligence - an illusion of human thinking created in software. _Artificial Intelligence_ is a catchall term that describes a range of technologies, sub-disciplines, and applications. We tend to use the term AI to apply to cutting-edge or future technologies, making the definition something of a moving target. In fact, “[AI Effect](https://en.wikipedia.org/wiki/AI_effect)” is the term for a phenomenon where products that were once considered AI are redefined as something else, and the term AI is then applied to “whatever hasn’t been done yet” (Per Tesler’s Theorem, [apparently misquoted](https://www.nomodes.com/larry-tesler-consulting/adages-and-coinages).) There are at least three different types of AI, according to Austin Govella and Michelle Caldwell in their workshop “[Information Architecture for Enterprise AI](https://www.theiaconference.com/sessions/information-architecture-for-enterprise-ai/)”: - **Generative AI** creates content in response to prompts. - **Content AI** processes and analyzes content, automating business processes, monitoring and interpreting data, and building reports. - **Knowledge AI** extracts meaning from content, building knowledge bases, recommendations engines, and expert systems. There are [other ways to slice AI](https://medium.com/@marketing_89629/discover-the-types-of-artificial-intelligence-in-2024-cc46d5e77b2d). AI can be narrow (focused on a specific task or range of tasks), general (capable of applying knowledge like humans do), or super (better than humans). It can include machine learning, deep learning, natural language processing, robotics, and expert systems, among other things. Dive deeper here: [Artificial intelligence - Wikipedia](https://en.wikipedia.org/wiki/Artificial_intelligence)\