In this special edition of the Future of Voice AI series, welcome leading voices on the state of voice AI in CX:

- Nicole Kyle of CMP Research on CX market data and shifting priorities

- Kwindla Hultman Kramer of Daily on building and scaling voice AI agents

- Brent Stevenson of IntouchCX on AI adoption on the frontlines

Fullband 2025 brought together research, technology, and frontline leaders to cut through the hype and show where voice AI is actually working today. Here’s the distilled recap.

The State of Voice AI in CX

Nicole Kyle, Managing Director & Co-Founder of CMP Research

Nicole leads groundbreaking research on customer contact and shared why voice remains essential in CX and how priorities are shifting in an AI-driven era.

3 Takeaways:

* Voice is still the biggest automation prize because it carries the most volume.

* Interest in self-service is high, but adoption lags due to poor experiences.

* Leaders are shifting from GenAI hype to use-case deployments and early agentic AI.

Stat to remember:Only 3% of customers prefer conversational voice AI for self-service today, driven by quality gaps, not lack of interest.

What you can do today:Pick one high-volume voice use case and lift quality: define success, measure completion rate and CSAT, and iterate until adoption rises.

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The State of Voice AI Agents

Kwindla Hultman Kramer, CEO & Co-Founder of Daily

Kwindla is pioneering real-time AI agents for voice and video. He unpacked unpacked what it takes to build, scale, and deploy AI agents that actually work.

3 takeaways:

* Enterprises moved from curiosity to concrete agent roadmaps in just 12 months.

* Constrained, vertical agents (esp. outbound) are finding product–market fit faster than broad platforms.

* 2024 solved plumbing (turn-taking, latency); 2025 is about natural conversations and reliable structured data capture.

Stat to remember: One in three enterprises is already in production with AI agents.

What you can do today:Choose one constrained workflow (e.g., outbound confirmation calls). Define latency and handoff goals, then launch and tune before scaling.

The State of Voice AI in BPOs

Brent Stevenson, Chief Experience Officer of IntouchCX

Brent offers a frontline view of CX transformation, showing how BPOs adopt AI by fixing workflows and blending automation with human expertise.

3 takeaways:

* Workflow design and governance are the real blockers, not technology.

* BPOs are acting as “AI administrators,” with QA analysts repurposed into agent trainers and prompt engineers.

* Agent assist is now table stakes, with translation and accent conversion expanding labor pools and market access.

Stat to remember:Agent assist at IntouchCX delivered ~10% AHT reduction, 3–5% CSAT lift, and 20% faster agent ramp.

What you can do today:Stand up an “AI QA” function to own prompts, tuning, and bot governance — manage AI like you manage human agents.

Q&A

The event was jam-packed, and we couldn’t get to every question live. Here are the ones we missed.

1. Nicole, the research shows a lot of shifting priorities. Which do you think will have the biggest long-term impact on how companies invest in voice AI?

The need to increase customer adoption of self-service will have the biggest long-term impact on how companies invest in voice AI. Everything depends on the quality of the experience. If voice AI delivers a high-quality interaction, voice becomes the channel with the most to gain—from greater customer adoption of automation to significant cost savings through deflection. But if the solution falls short, it risks damaging the customer experience. It’s a classic case of high risk, high reward.

2. Nicole, where do you see the biggest gaps between executive priorities and the technology that’s actually available today?

This isn’t a fun answer but honestly, knowledge base management and governance. Good knowledge is the key ingredient to making an AI (conversational, generative or agentic) function properly. And it’s hard for most customer contact and CX organizations to manage right now. They’re looking for AI solutions that can proactively add to and audit the knowledge base, but there’s a gap in the market right now.

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