
About this episode
We all know AI agents can answer calls (with varying success rates depending upon their sophistication). But what if AI agents could also help CX leaders analyze their deployments, ask questions about their unique challenges and opportunities, and continuously improve?
In this episode of Deep Learning with PolyAI, Nikola Mrkšić sits down with Damian Sasso, Group PM at PolyAI, to explore how the field is moving from solely customer-facing AI agents toward agentic AI teams that can do all of the above.
We cover:
- Why MIT says 95% of AI pilots fail — and how to be in the successful 5%
- The role of QA Agents in monitoring performance
- How Analyst Agents like Smart Analyst surface business insights in real time
- The promise of Builder Agents that drive continuous optimization
- Why contact centers are shifting from call centers to command centers
If you want to understand how agentic AI is changing the landscape — one in which AI agents don’t just talk, but think, analyze, and build — this episode is for you.
👉 Subscribe today for more info about AI for CX.
Get every episode summarized
Each time Deep Learning with PolyAI publishes, we email you a written briefing from the transcript — the topics, who appeared, and any specific claims, with the ad reads skipped.
Email me new episodesFree for 3 shows. No card needed.
Hosts & guests
No transcript yet
This episode has not been transcribed. Request it and it moves to the front of the queue.
More episodes
More from Deep Learning with PolyAI

Who's coordinating your army of AI agents?
Deep Learning with PolyAI

Why should CX leaders care about MCP?
Deep Learning with PolyAI

Can AI really hear a call the way a person does?
Deep Learning with PolyAI

Is word error rate just a vanity metric?
Deep Learning with PolyAI