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What is an AI API? Definition and business implications
An AI API is a technical interface that lets a software application send requests to an AI model hosted by a provider, and retrieve its responses. It is the standard access mode to AI in enterprise, as opposed to local hosting of the model.
Concretely, an AI API operates by authenticated HTTPS call. The client application sends a structured message (prompt, parameters such as temperature, model choice) to a provider endpoint (api.anthropic.com, api.openai.com, etc.), authenticated by a secret key. The server runs the inference and returns the response, generally in streaming (token by token) for interactive uses. Three characteristics structure usage. The billing model: almost always pay-per-use, in tokens consumed at input and output, with no fixed subscription. Latency: 200 milliseconds to 2 seconds for the first response, plus the generation time. Resilience: the best-designed APIs offer an explicit SLA, with availability rates above 99.9% and a fallback endpoint in case of incident. The AI API has become the dominant mode of AI consumption in enterprise, ahead of local hosting, which remains reserved for cases with strong sovereignty or volume constraints.
Concrete example
A 120-employee industrial SME integrates an AI assistant in its ERP via the Anthropic API. Three metrics to monitor for production. Monthly inference cost (variable depending on the volume of business prompts, here about 280 euros per month for 2,000 daily calls). Average latency, measured at 1.1 seconds for first response plus 18 seconds for a typical 500-token generation. API error rate, tracked via the provider console: 0.4% of 5xx errors over three months of observation, compliant with the Anthropic SLA. Without these three metrics, the deployment is piloted blind.
See also
Further reading
Sources
- Anthropic Messages API documentation, 2026. https://docs.anthropic.com/en/api/messages
- OpenAI API reference, 2026. https://platform.openai.com/docs/api-reference