Free Analyst VBook:
Insights from Frost & Sullivan on the rise of AI-native networks and intelligent assurance
From Connectivity to Cognition: Building the AI-Native Network Through Intelligent Assurance
Inside, you will discover:
- Why networks must evolve from connectivity to cognition
- How AI-native architectures are reshaping operations
- The shift from AI-assisted to agent-driven autonomy
- Why data quality and context are now core to modern assurance
- The service assurance maturity model for AI-era networks
- Frost & Sullivan’s recommendations for CSPs preparing for AI-native operations
Building the AI-Native Network
As networks become cloud-native, distributed, and deeply infused with AI workloads, CSPs face a new operational reality. Assurance can no longer be a reactive function: it must evolve into a foundation for intelligent, autonomous operations.
The VBook highlights how CSPs are moving toward agent-driven autonomy, where intelligent agents continuously learn, collaborate, and act in real time. Achieving this requires pristine data hygiene, deep contextual insights, and a vendor-neutral assurance layer capable of orchestrating intelligence across domains.
This research explores why CSPs must modernize their assurance foundations now, and what steps will define success in the AI-native era.
AI and Intelligent Assurance: Why This Matters Now
AI is redefining how telecom networks operate. According to data in the VBook:
- Over 74% of CSPs expect enterprise customers to drive most AI-related traffic growth in the next three years.
- 60% believe AI will improve operational efficiency by 40% or more.
As enterprises adopt 5G standalone, edge computing, IoT, and multi-cloud environments, assurance systems must deliver predictive, contextualized intelligence that supports real-time decisions, dynamic scaling, and self-healing behaviors.
This VBook outlines how CSPs can build this foundation.
Frequently Asked Questions
How is AI transforming modern service assurance?
AI enhances anomaly detection, automated correlation, predictive insights, and closed-loop actions - enabling faster detection, diagnosis, and resolution across multi-domain environments.
What are agentic AI systems in telecom?
Agentic systems use intelligent software agents capable of perceiving intent, reasoning autonomously, and coordinating actions across domains — accelerating progress toward autonomous operations.
Why are AI-native, self-healing networks difficult to build?
They require trusted, context-rich data, multi-domain visibility, predictive models, aligned governance, AI-to-AI interoperability, and resilient architectures capable of executing autonomous decisions safely.
Explore Enghouse Service Assurance
See how Enghouse helps CSPs modernize their assurance foundations, improve visibility, reduce operational complexity, and take practical steps toward agent-driven, AI-native networks.
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