How AI and ML Creates Value in Telecom Operations

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AI and machine learning are rapidly transforming telecom operations - from reactive troubleshooting to intelligent, data-driven decision-making.

Interview with Emil Radonchikj, Head of Customer Experience Assurance at Polystar, on How AI Creates Values in Telecom

Where AI and ML Deliver Real Value

In two short videos, Emil Radonchikj, Head of Customer Experience Assurance at Polystar, explores how AI and ML enable telecom teams to work smarter, faster, and more efficiently.

By leveraging existing network data and domain knowledge, AI accelerates root cause analysis and streamlines the path from detection to resolution. This helps operations teams move beyond manual investigation and toward automated, insight-driven workflows.

The result is measurable operational impact.

AI-driven capabilities within Polystar’s Customer Experience Assurance platform - such as automated insights, call summarization, and agentic AI - further enhance efficiency by processing large data volumes and supporting deep technical analysis.

Watch the video for more details.

Emil Radonchikj, Head of Customer Experience Assurance at Polystar shares insights on the maturity of AI/ML in telecom

Where AI and ML Deliver Real Value

In two short videos, Emil Radonchikj, Head of Customer Experience Assurance at Polystar, explores how AI and ML enable telecom teams to work smarter, faster, and more efficiently.

By leveraging existing network data and domain knowledge, AI accelerates root cause analysis and streamlines the path from detection to resolution. This helps operations teams move beyond manual investigation and toward automated, insight-driven workflows.

The result is measurable operational impact.

AI-driven capabilities within Polystar’s Customer Experience Assurance platform - such as automated insights, call summarization, and agentic AI - further enhance efficiency by processing large data volumes and supporting deep technical analysis.

Watch the video for more details.

From Experimentation to Real-World Use Cases

AI and ML in telecom are no longer experimental, they are delivering clear, high-value outcomes across operations. Operators now better understand where these technologies create both operational and commercial impact.

Key AI-supported use cases from Polystar include:

These practical applications enable telecom operators to act proactively, preventing service degradation before it impacts users and reducing operational complexity.

The Next Phase: Agentic AI

Looking ahead, the evolution continues with agentic AI - introducing intelligent automation that can execute tasks and orchestrate workflows across network operations with minimal manual intervention.

This next phase marks a shift toward more autonomous networks, where AI not only provides insights but also takes action. By combining advanced analytics with automation, operators can scale operations more efficiently while maintaining high service quality.

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