API (application programming interface): An API (application programming interface) is a way for one piece of software to talk to another. An AI API lets your own tools, spreadsheets, or automations send a prompt to a model and receive the response, without a person typing in a chat window.
When you use ChatGPT or Claude in the browser, you are using a consumer app. Behind it is an API, a set of instructions a program can call: send this text, get this reply. Developers, automation platforms like Zapier and Make, and many business applications use those APIs to put AI inside their own workflows.
APIs are priced per token rather than per seat, so you pay for what you process. They also expose settings the apps hide, such as temperature and maximum response length, and let you choose among several models from the same vendor. Major providers state that data sent through their APIs is not used to train their models by default, which is often a better privacy posture than a free consumer app; check the vendor's current terms for your account.
You do not have to code to benefit. Automation tools offer AI steps that call an API behind a form, and a growing number of business apps let you plug in your own API key. Knowing the term helps you understand what a vendor means when it says a feature is 'powered by' a particular model.
Example at work
A logistics company's operations lead uses an automation platform to watch a shared inbox. Each new carrier email is sent to an AI model through its API with a prompt that extracts the shipment number, pickup date, and any exceptions, and the results land as rows in a tracking spreadsheet. No one on the team wrote code.
Why it matters
Once you understand that any AI model can be called from other software, you start seeing automation opportunities everywhere: intake forms, inbox triage, report generation, data cleanup. It also clarifies pricing and privacy conversations with IT and vendors.
Related terms
- TokenA token is the unit of text a language model reads and writes, usually a word or a piece of a word. Models measure input limits, output limits, and pricing in tokens; as a rough rule, 1,000 tokens is about 750 words of English.
- Workflow automationWorkflow automation connects apps and steps so that a trigger, such as a new form response or an incoming email, automatically runs a sequence of actions, increasingly with an AI step that reads, decides, or writes along the way.
- TemperatureTemperature is a setting that controls how random a language model's output is. Low values make the model pick the most likely next word and give consistent, predictable answers; higher values allow more varied and creative responses.
- Rate limitA rate limit is a cap on how much you can use an AI service in a given period, such as messages per hour on a chat plan or requests and tokens per minute on an API, set to protect the provider's capacity and to tier pricing.
- InferenceInference is the act of running a trained AI model to produce an output, such as answering a prompt or classifying an image. Training happens once; inference happens every time anyone uses the model, and it is what you pay for as a user.