Free Analyst Report:
Insights from STL Partners and Charlotte Patrick on the Future of Assurance
AI and Agents in Next-Generation Assurance
Inside, you will discover:
- How AI and ML are being used in current assurance workflows
- The role of agent-based architectures in next-generation operations
- Why self-healing networks remain difficult to achieve
- Insights from operator and vendor interviews
- Recommendations from STL Partners and Charlotte Patrick
Using AI to Build the Next Generation of Assurance Solutions
Creating a genuinely self-healing network is likely to be an extremely demanding journey for CSPs. Many are now beginning to pilot agentic architectures within their assurance domains, and even these early experiments reveal a wide spectrum of challenges. Success will require sustained architectural evolution, far richer and cleaner data foundations, and the ability to coordinate intelligent agents reliably across multiple domains and vendors.
This research examines the current and future requirements for AI and ML in service assurance as telcos move toward more autonomous, self-healing networks.
To help CSPs understand what’s changing and how to prepare, Enghouse Networks partnered with STL Partners and Charlotte Patrick to examine how AI, machine learning, and emerging agentic architectures are reshaping service assurance.
Discover why self-healing networks remain challenging, what progress the industry has made so far, and what steps operators should take next.
AI and ML in Service Assurance: Why This Matters Now
Telecom networks are becoming more distributed, cloud-native, and data-heavy. AI and ML are increasingly used to detect anomalies earlier, enrich alarms with context, improve prediction accuracy, and support faster decision-making. As CSPs adopt 5G standalone, slicing, IoT, and multi-vendor architectures, assurance systems must evolve to deliver deeper visibility and form the foundation for more autonomous, self-healing operation
This report outlines how these technologies can support that progression.
Frequently Asked Questions
How is AI used in telecom service assurance?
AI supports anomaly detection, alarm correlation, predictive insights, and enhanced root-cause analysis - helping operators respond to issues earlier and reduce manual investigation.
What are agentic AI systems in telecom?
Agentic systems use coordinated software agents that analyse network events, retrieve context, and perform or recommend actions across domains.
Why are self-healing networks challenging to build?
They require reliable data foundations, strong knowledge layers, predictive models, multi-domain coordination, and robust decision-making across vendors and systems.
Explore Enghouse Service Assurance
See how Enghouse applies these research insights to help CSPs improve visibility, reduce complexity, and take meaningful steps toward more intelligent network operations.
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