Is agentic AI the answer to broken analytics?
About the show
Hosted by Nikola Mrkšić, Co-founder and CEO of PolyAI, the Deep Learning with PolyAI podcast is the window into AI for CX leaders. We cut through hype in customer experience, support, and contact center AI — helping decision-makers understand what really matters.
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Summary
Analytics has always been the hardest part of the contact center. Dashboards are slow, incomplete, and rarely used outside of specialist teams. But what if analytics could be as simple as asking a question?
In this episode of Deep Learning with PolyAI, your host Nikola Mrkšić brings back Damian Sasso to explore how agentic AI is transforming analysis itself. Instead of waiting weeks for trends to surface, leaders can now interact with their data in real time: surfacing insights, testing hypotheses, and finding the “needle in a haystack” moments that drive real business change. Capabilities like PolyAI's new Smart Analyst are making it all come to life, and Damian shares a demo to show exactly how it all works.
The conversation touches on:
- Why analytics has lagged behind in AI transformation
- How unstructured conversation data is finally becoming accessible
- The shift from static dashboards to dynamic dialogue with data
- What this means for the evolution of the contact center — from a cost center to a true command center
Key Takeaways
- From dashboards to dialogue: Traditional BI tools require analysts to build dashboards and ontologies that often miss nuance. Smart Analyst replaces this with natural language queries, making it fast and intuitive for CX leaders to uncover insights.
- Structured + unstructured data combined: Unlike standard reporting tools, Smart Analyst draws from both structured metrics (containment, handle time) and unstructured call transcripts, surfacing trends, anomalies, and even “weirdest calls” that matter most in the contact center.
- Needle-in-a-haystack solved: Analysts can find specific conversations — successful bookings, long back-and-forths, or problem cases — in seconds. What once took days of manual review now takes moments, helping teams iterate faster and with greater confidence.
- Toward agentic self-improvement: Smart Analyst isn’t just a reporting tool; it’s the foundation for AI-driven continuous improvement, suggesting automation opportunities and informing updates to agents, knowledge bases, and workflows.
Transcript
Nikola Mrkšić: Hi everyone. Welcome to another episode of Deep Learning with PolyAI. I’m here in New York with Damian this time in person. Welcome to another episode.
Damian Sasso: Thanks, Nikola. Thanks for having me. It’s good to have you in person. Yeah. In our New York, in our New York office, in our improvised New York studio. So
Nikola Mrkšić: Absolutely, Damian and I just moved five different lights and realized that our sound insulation is not as good as we thought it was. So we hope this turns out okay, but we have something much more exciting than our acoustics here to talk about. Last time we recorded the episode, we talked a bit about kind of like the different agents we have and the different gen frameworks that operate over our agents. God, how many times can I say the word agent in a single sentence? But one that we are really excited about and we kind of committed to demoing this time is smart analyst. Yeah. Like the tool that we use and that we think is a gateway for mere mortals, which is pretty much everyone in the contact center and elsewhere. To be able to actually ask questions of the dataset, draw insights, and operate on the whole kind of a customer service state. So, what is a smart analyst?
Damian Sasso: Yeah, so I mean, this is the, we talked a little bit about smart analysts in our last podcast where we went through our QA agent concept, our supervisor agent concept, and really the idea that we wanted today was to kind of show what we were talking about, which is what’s the functionality that’s part of Agent Studio that allows our customers to use natural language to get deep insights into their data. So we’re going to spend some time kind of going through Smart Analyst. So I brought up smart analysts for one of our agent projects. And you can come in here into Agent Studio and you see, right off the bat, you have a natural language framework for querying any information. And we have kinda suggested queries, which you can see. Why are people calling your agent? What are the most recent successful calls? But it really is this idea of flexibility. Experience for getting insight into your data. Now, we talked a little bit about this in our last podcast that is trying to get trends out of your data. Out of the call center. It takes time. And the whole idea behind smart analysts was to make that something that doesn’t take time.