What Is Conversational AI? How It Works, Use Cases, and How to Evaluate It
Blog post from Coval
Conversational AI refers to artificial intelligence systems capable of engaging in real conversations with humans through voice or text, distinguishing them from older chatbots by using large language models to comprehend intent and generate natural responses. The technology encompasses both text-based and voice-based systems, with the latter introducing additional complexity such as speech-to-text conversion and real-time turn-taking. As of 2026, conversational AI is increasingly prevalent in industries like healthcare, financial services, and customer support due to its efficiency in handling high-volume, repetitive interactions. The architecture of voice AI systems typically involves a cascaded model comprising speech-to-text, language models, text-to-speech, turn detection, and emerging emotional intelligence components. This shift in focus from sounding human to achieving high resolution rates is driven by the economic advantage of AI handling interactions at a lower cost compared to human agents. Nonetheless, the challenge remains in evaluating these systems effectively to maintain performance in real-world conditions where factors such as audio quality and conversational complexity can impact success rates.
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