AI Glossary
What it means, why it matters to your business, and where it shows up in a real build decision.
In plain terms
Latency is the delay between a user's request and the AI system's response. It shapes whether AI feels helpful or frustrating. Some quality gains come from slower, larger models, so latency is a real trade-off against accuracy and cost.
Latency in AI is the gap between asking a question and getting an answer. A one-second wait feels like speed. A ten-second wait feels like the system is broken, even if the answer that arrives is excellent.
A sales team's AI call summary tool takes 45 seconds after a call ends. Adoption is low. Optimizing the prompt and switching to a faster model brings it to 8 seconds. Adoption doubles.
Measure latency for every user-facing AI feature from the first prototype. Set an acceptable maximum threshold before choosing a model, not after users are already complaining.
Chasing minimum latency at the expense of accuracy is the wrong optimization for many back-office tasks. A nightly batch job that takes 5 minutes is fine. A real-time assistant that takes 15 seconds is not.
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