In the last 12 months, questions around AI adoption in the contact center have changed from if to when to “why haven’t we done this yet?!” But part of the obstacle to incorporating AI into your strategy is the total lack of transparency. When every tech company is claiming to solve all problems, it’s difficult to separate hype from actual value.
This panel brings together two experts who have successfully led AI adoption use cases in the contact center. Paula Kennedy, a thought leader in customer experience innovation who has held key strategic roles at IntouchCX, Concentrix, Sitel Group, TeleTech, and HCL BPO; and Etie Hertz, CEO of Loris, an AI startup using conversational intelligence to improve everything from customer insight to agent performance to quality assurance.
After this discussion, you’ll walk away with:
- The ability to prioritize AI adoption projects with a plan for success
- Clarity on necessary steps and missteps to avoid
- Ways to measure the value of AI adoption while also mitigating risks

What’s the Right Mix of AI Agents and Human Agents for Customer Service?
It’s 2025, and the conversation around customer service automation has matured. The hype around replacing support teams with chatbots has met the friction of reality. Now, leading companies are asking smarter questions: not “How can I automate more?” but rather

Understanding Call Center Cost Per Call (and Why You’re Measuring It Wrong)
Call Center Cost Per Call (CPC) is one of the most tracked metrics in customer support. It’s easy to calculate (total cost/# of calls), quick to benchmark, and gives an impression of efficiency. But here’s the catch: optimizing for a lower CPC doesn’t

Top use cases for human and AI collaboration in customer experience
The integration of AI in the contact center is driven by a growing demand for rapid responses and deeper insights. This technology can parse massive amounts of customer interactions, detect patterns, and highlight emerging issues long before they impact large numbers of customers.