|---Module:text|Size:Small---| The telecom industry is at a critical turning point, as traditional networks struggle to meet growing digital demands and user expectations. With 5G expanding and 6G approaching, Communication Service Providers (CSPs) must modernize their network strategies.
The solution lies in building AI-native networks - intelligent, self-optimizing systems that improve performance in real time. Without this shift, CSPs are losing market share and losing revenue opportunities.
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The AI-Native Platform building intelligence into the network
A longstanding challenge in network engineering and operations is that critical data (vital for planning, optimisation, troubleshooting, resolution, and many other tasks) often resides in multiple, uncoordinated, and segregated systems. In many instances, data from different network and service domains - such as RAN, transport (TX), voice, and data - is further siloed, amplifying this complexity. As a result, telecom providers face slower time-to-market, higher costs, redundant efforts, and missed opportunities to fully leverage network data.
An AI-native platform addresses these challenges and turns the telecom network into a cohesive, intelligent system. Integrating AI, cloud-native infrastructure, and automation at its core, it enables collaboration, data sharing and acting on based real-time insights.
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|---Module:text|Size:Small---|Key AI-Networks Platform components include:
- Telco Cloud
- Network Functions
- Management & Orchestration Layer
- Data & AI Factory Layer
- App Enablement Layer
- Applications Layer
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The Role of Digital Twins in AI-Native Evolution
The effectiveness of any AI application depends on the speed, quality, and relevance of the data it processes. A robust data readiness framework and well-structured data model are essential for quickly accessing and using data for specific use cases.
Such a framework eliminates silos, standardizes formats, and enables cross-source correlation, paving the way to more efficient troubleshooting, streamlined operations, and better AI outcomes. This requires adopting a hybrid data ecosystem that strategically employs various storage technologies to balance both efficiency and performance.
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Telecom leaders must recognise that AI-native is not a distant future, nor do they need to wait for 6G - they can begin by making their 5G networks smarter. Starting with scalable data strategies, introducing modular orchestration tools, deploying AI agents where insights are most needed, and exposing APIs for external integration.
The networks that embrace this shift will lead the industry in innovation, efficiency, and profitability.
