Videos
Google on Agentic AI for Telco Operations, Customer Experience, and Security
Insights
- AI is helping telcos move toward more autonomous operations through predictive maintenance and earlier issue detection.
- Customer experience is becoming more proactive, with agentic AI helping solve problems before customers need to contact support.
- Organizations are looking beyond chatbots to use agentic AI for end-to-end workflow transformation across the business.
At MWC 2026, David Levitch of Google discusses how AI priorities in telecom are centering on three key areas: autonomous operations, customer experience, and internal transformation. He explains that telcos are increasingly focused on predictive maintenance and better operational visibility so they can address issues before they occur. The conversation also highlights how agentic AI can improve customer experience by helping resolve problems before customers ever reach the call center. Beyond these use cases, he emphasizes that many organizations are still working through how to unlock value from AI securely and at scale. He also describes a broader shift from siloed chatbots to agentic systems that can redesign end-to-end workflows, creating new opportunities for efficiency and transformation.
Samad Masood:
What do you see as the big shift amongst telcos this year with AI?
David Levitch:
My conversations have focused on three areas. The first is on autonomous operations. How do you actually drive better predictive maintenance, better understanding of what's happening before it actually happens? The second is a lot of focus on customer experience. How do we actually drive a much better agentic customer experience? How do we ensure that before people even call the call center, we're helping to solve that problem? And then the third piece is a lot of focus on just an internal operations with an agentic standpoint.
AI still struggles to deliver value and trust at scale
David Levitch:
Even several years into this moment, people are still struggling to figure out how to get the value out of it. Where do I go next? What are the use cases to focus on? And how do I actually ensure those use cases are highest order? That's the first piece the second piece people are really focused on is security. How do I ensure I have a secure and end-to-end stack? How do I think about the right framework within AI security?
Agentic AI is transforming end-to-end business workflows
David Levitch:
We moved from chat bots, very siloed chat bots on a website to really focus on workflows. And it was about efficiency. But those were just taking an existing workflow and updating components of that workflow. What we're seeing now is a true opportunity for transformation, which is around agentic workforces in agentic era, where what we can actually do is figure out how do we change an end-to-end workflow instead of just updating it? And so that becomes a huge opportunity for transformation. That's where we're partnered with a lot of customers right now is on that end-to-end transformation.
