Inference latency is the delay from when audio or text from a customer interaction is received to when an AI model produces an output, such as real-time transcription, intent detection, compliance flags, or an agent prompt. It is typically measured in milliseconds to a few seconds and can include capture, processing, and model runtime.
Operationally, inference latency determines whether AI can support agents in the moment. If latency is too high, prompts arrive after the customer has moved on, agents ignore the guidance, and supervisors see less consistent adherence to scripts, disclosures, and troubleshooting steps.
Latency also affects customer experience and handle time. Slow or unstable responses can force agents to repeat questions, pause while waiting for guidance, or rely on manual lookups, which can increase silence time, extend calls, and reduce first-call resolution.
