Conversational AI
AI systems designed to simulate human conversation across voice, text, and chat.
Conversational AI is the broad category of artificial intelligence systems built to hold natural, back-and-forth conversations with humans across channels — voice calls, chat, messaging, and email. An AI voice agent is conversational AI applied specifically to the phone channel.
What makes it "conversational"
Unlike scripted bots that match keywords, conversational AI understands intent, maintains context across turns, handles interruptions and corrections, and produces fluent, context-aware responses. On voice, it combines several components:
- Speech recognition (ASR/STT) to understand spoken input.
- Natural language understanding (NLU) to extract intent and entities.
- A large language model (LLM) as the reasoning and dialog engine.
- Text-to-speech (TTS) to respond in natural voice.
Voice vs. chat conversational AI
Voice is the harder problem: it is real-time, unforgiving of latency, and must handle disfluencies, background noise, and barge-in. A chatbot can take a second to "think"; a voice agent that pauses too long feels broken. This is why voice-first conversational AI is engineered around an end-to-end latency budget.