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

You Don’t Have a Quality Problem. You Have a Data Problem.
If you’re leading a customer support team in 2025, your reality probably looks something like this: You’re being told to innovate using AI. And being asked why AI Agents can’t do half your team’s work. But you’re also running an operation that’s

Whitepaper: AI Analytics is the Key to Modern Quality in Customer Support
As customer experience leaders move beyond AI pilot programs into scaled AI agent deployments, they’re asking: What share of conversations should be handled by AI, and which should stay with human agents?

How do I use AI to Reduce Customer Churn?
Customer churn is one of the most expensive problems in customer experience. And it’s well known that acquiring new customers costs significantly more than keeping the ones you already have. So how do you keep customers as your customers? You could