18/06/2026
Everyone is racing to add LLMs to voice products, but here is the uncomfortable truth: voice AI fails not because the model isn't smart, but because it's "deaf" to the real world until triggered.
For OEMs, relying solely on cloud-based LLMs isn't just a latency issue; it's a cost and differentiation trap.
As Kardome CEO Dani Cherkassky argues in his latest piece in The AI Innovator, the future of voice AI isn't about the biggest model. It's about a smarter distribution of intelligence: on-device cognition that enables spatial awareness, continuous hearing, and immediate responses.
The winners in voice AI won't be the companies with the largest parameter, but those who deliver devices capable of human-like conversation that work in real-life environments: overcoming noise, handling interruptions, and navigating overlapping conversations.
Is your product roadmap prioritizing edge-first context, or are you still tethered to the cloud? Let us know in the comments below.