In the Future of Voice AI series of interviews, I ask three questions to my guests:
- What problems do you currently see in Enterprise Voice AI?
- How does your company solve these problems?
- What solutions do you envision in the next 5 years?This CCW episode features guest Jordan Zivoder, Quantitative Research Lead at Customer Management Practice (CMP Research).
Jordan Zivoder has 10 years of experience in Market Research and Voice of the Customer leads quantitative research and analysis for CMP Research, Customer Management Practice’s dedicated independent insights and research product. With a primary focus on empowering executives to leverage data for data-driven decisions, Jordan combines expertise in survey research with machine learning to deliver unparalleled understanding of the customer and employee experience.
CMP Research delivers unlimited advisory support, diagnostic tools, and data-driven insights to help customer contact & CX executives optimize experience, technology, and operations, while enabling solution providers with go-to-market strategies and customer insights—all powered by the organization behind Customer Contact Week.
Recap Video
Takeaways
Rising cost pressures are shifting priorities toward automation and self-service instead of hiring, changing how leaders approach customer support.
AI is helping agents do better work faster. Companies can boost performance without replacing people.
One bad self-service or bot experience can damage customer trust and stall long-term adoption.
Even as AI gets smarter, customers still expect clear access to a human—over-automation risks breaking trust.
Leaders and agents have different views on what matters most. Closing that gap is key to strong performance and retention.
Executives overestimate the impact of culture while agents care more about good managers, flexibility, and career growth.
Internal tools like Agent Assist are a safer way to test AI performance and reduce risk before deploying customer-facing automation.
AI only works well if the data behind it is accurate and up to date. Bad information leads to poor results and failed launches.
Contact centers are rich in conversation data, but few use it well. Those who miss this opportunity fall behind.
The best teams feed call data into AI tools to fill knowledge gaps and continuously improve performance.
New AI tools can detect missing knowledge and automatically update content, creating a self-improving feedback loop.
AI adoption forces companies to treat knowledge management as a core priority, not an afterthought.
AI’s value is not just in automating conversations but in creating systems that help both bots and humans improve over time.
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