The big map of AI: fields and sub-fields
AI sits where several sciences meet. Its sub-fields overlap and do not fit into one neat tree.
What is it?
AI is not one discipline but a crossroads of computer science, mathematics, statistics, cognitive science, law and other fields. Its subfields, such as machine learning, computer vision and robotics, overlap and cannot be arranged in a single tree.
An everyday example
A single self-driving system combines vision, planning, learning, control, law and safety.
Why does it matter?
The map helps place a piece of news: is it a new model, a new use or a new rule? That makes it easier to judge what has actually changed.
A common misconception
That AI is one neat hierarchy in which everything sits under chatbots or deep learning.
In more detail
What sits above AI?
In education, AI is most often treated as part of computer science. It is also connected to mathematics, statistics, logic, linguistics, cognitive science, neuroscience and philosophy.
What sits below AI?
The main sub-fields include machine learning, knowledge representation, reasoning, search, planning, language processing, computer vision, robotics and multi-agent systems.
Where do deep learning and generative AI fit?
Deep learning is part of machine learning. Generative AI is a group of abilities and methods that often relies on deep learning. So it is not simply a parallel branch.
What about law, ethics and economics?
These are disciplines and areas of use connected to AI, not “less important extras”. They shape how the technology affects people.
Remember: AI is not one neat hierarchy: methods, tasks and consequences overlap.
Reliable sources
Last reviewed 1 November 2026. An explainer, not professional, legal or medical advice. For rules and figures that change, check the official version.