Why Sub-Second Voice AI Is the New Gold Standard

In live conversation, timing is everything. Human speech naturally flows in ~200 ms beats, with brief silences that give each participant room to think and respond. Push beyond half a second and something subtle but powerful happens: the exchange starts to feel stilted, robotic, and less trustworthy.

That is why the best voice AI systems today aim for sub-second, end-to-end response times. At Giga, we believe this is not just a nice-to-have. It is the foundation for any AI that aspires to feel truly human.

The Human Threshold

Telecommunications research and human–computer interaction studies have long shown that people notice lag as low as 100–120 ms. The ITU’s G.114 guideline sets 150 ms as the ideal one-way limit for high-quality interactions, with anything above 400 ms risking conversational breakdown. In other words, once you cross the 500 ms mark in total voice-to-voice time, users instinctively perceive the agent as slow, even if they cannot explain why.

What the Industry Targets

Across the industry, a total latency budget of ≈800 ms has emerged as a realistic target for cloud-based voice AI. This typically breaks down into:

• ASR (speech-to-text): 150–250 ms

• LLM processing: 200–300 ms

• TTS (text-to-speech): 150–250 ms

• VAD / end-pointing: tuned to under 500 ms silence

• Network: 50–150 ms

Leaders like Google, Microsoft, and Amazon aim for sub-300 ms averages in specific components. Independent leaderboards such as Jambonz show that top TTS providers like Rime and PlayHT now deliver audio in under 200–250 ms, while others still exceed 500 ms.

Why It Matters

Low latency is not just about sounding slick. It drives real business outcomes:

• Fewer hang-ups: Contact-center data indicates that responses over one second can increase call abandonment by up to 40%

• Higher satisfaction: Vodafone reported a +14 NPS point jump after deploying a modern AI assistant, along with significant first-time-resolution gains

• More revenue: Faster responses improve upsell rates and reduce customer churn in high-value sectors like retail, banking, and telecom

• Lower costs: Voice AI can cut per-interaction costs by up to 70% while scaling to handle surges without adding headcount

The Engineering Challenge

Achieving these speeds in the real world is not trivial. It requires:

• Optimizing every pipeline stage: from voice activity detection to LLM inference to TTS synthesis

• Reducing network overhead: especially for telephony, where jitter buffers and routing can add hundreds of milliseconds

• Balancing quality with speed: ultra-fast models must still deliver natural prosody, accurate recognition, and context-aware responses

At Giga, we continuously profile and tune each step, ensuring our median end-to-end latency stays well below the one-second mark even under peak load.

Why Sub-Second Is the Future

In human terms, latency is empathy. The faster an AI can process your words and respond naturally, the more it feels like it is truly listening. Sub-second responsiveness is not only a technical achievement. It is the invisible handshake that builds trust, keeps customers engaged, and turns a good conversation into a great one.

The companies that master it will set the standard for how we talk to machines and how machines talk back.