API (Application Programming Interface) is a way for one piece of software to talk to another. In AI, an API lets developers add a model’s capabilities to their own apps by sending requests to it over the internet.
What it means in plain English
An API is like a waiter between your program and a service: your software sends a request in an agreed format, and the service sends back a response. AI companies offer APIs so that instead of building and hosting your own model, you can simply call theirs — sending text and receiving the model’s output. This is how most AI-powered apps are built.
Usage through an API is typically billed by the amount of text (tokens) processed.
A simple example
A startup building a writing app does not train its own language model. Instead, it calls an AI provider’s API: it sends the user’s text, the API returns AI-generated suggestions, and the app displays them — all in a fraction of a second.
Why it matters
APIs are how AI reaches the wider world. They let any developer integrate powerful models into their products without the enormous cost of building models themselves, which is a major reason AI features have spread so quickly across software.
Related terms
- Token — the unit API usage is usually billed in.
- Inference — what an AI API performs on each request.
- Function Calling — a way models interact with external APIs.
Frequently asked questions
How do APIs relate to AI?
Many AI models are accessed through APIs: developers send a request (such as a prompt or an image) to the provider’s API and receive the model’s output, letting them add AI to their apps without hosting the model themselves.
Do AI APIs cost money?
Usually yes — most commercial AI APIs charge based on usage (for example, per token, per image, or per request), though some offer free tiers for testing.
