Three partners, one goal: autonomous networks that think for themselves. Google Cloud, Nokia, and One NZ are joining forces to create networks that don't wait for human intervention â they predict, fix, and evolve autonomously by 2026.
The telecom industry stands at a breaking point. What was once simple connectivity is evolving into something far smarter. **AI networks** aren't science fiction anymore â and Google's partnership with Nokia and One NZ proves it in practice. When Google announced its **Autonomous Network Operations framework** last year, many thought it was talking about the future. Now, as we approach MWC Barcelona 2026, that future is knocking. But how realistic is it to expect a network to solve its own problems?đ Read more: AI Agents Negotiate 5G Network Slices Autonomously in 2026
đŹ The Architecture of AI Networks
The secret lies in how these companies approach the problem. Traditionally, telecom networks operated reactively â something breaks, someone fixes it. Google's new approach deploys **machine learning** and artificial intelligence algorithms that can predict problems before they happen.Network Digital Twin: The Virtual Mirror
The foundation of this vision is the **network digital twin**. Instead of a static map, we have a dynamic, temporal graph representing the network's living state. This isn't just a representation â it's a living organism that captures reality in real-time.Imagine a network that remembers how it looked five hours ago, five days ago, even five months ago. This "memory" allows AI agents to perform cause-and-effect analysis with accuracy that surpasses any human capability.
Graph Neural Networks: Mathematical Prediction
The key to the Nokia-Google collaboration is using **Graph Neural Networks** (GNN). These networks train on Google's Vertex AI and can mathematically predict how a failure will spread through the network. No guesswork, no assumptions â pure science.đ Read more: Nokia AI RAN: GPU-Accelerated Networks Ready for 2026
⥠Nokia Autonomous Network Fabric: Tomorrow's Toolkit
Nokia didn't stay theoretical. In June 2025, it announced the **Autonomous Network Fabric**, an integrated technology suite promising to bridge the gap between traditional management and full automation. The company claims this is the industry's first suite of **telco-trained AI models**. What does this mean in practice? Instead of general-purpose AI models trying to understand telecom data, we have specialized algorithms "born" for this purpose.360° Observability across all layers
0 Human intervention in routines
The Tool in Action
How does it work in practice? The Autonomous Network Fabric collects, organizes, and publishes all relevant network data as data products. It uses a data mesh architecture that allows operators to create new data assets with minimal code. Nokia insists its solution offers "explainable AI" â something critical when discussing critical infrastructure. The system must not only work but also explain why it made specific decisions.đ One NZ: Real-World Testing Ground
Theory is impressive, but what happens in the real world? Enter One NZ, the New Zealand telecom giant that has become the testing ground for these innovations.Autonomous Network Agents in Operation
According to Google, One NZ is already testing **autonomous network agents** managing voice core and OSS networks. These agents aren't limited to monitoring â they take active action. When they detect call quality drops, they autonomously reroute traffic or restore network settings. But One NZ has taken another step. The company adopted **Google Security Operations** (SecOps) with Gemini AI for cybersecurity management. Laura Ross, the company's head of cyber security, describes how Gemini can answer queries like:"Show failed logon attempts coming from outside NZ and AU in the past day" or "Find events about outbound network traffic to 8.8.8.8"
Gemini prompt examples from One NZ
Implementation Results
Adopting these technologies at One NZ has produced measurable results. The company reports significant improvement in Security Operations Centre (SOC) efficiency, increased telemetry processing capability, and cost reduction. However, the real value appears in the system's ability to filter false positives and accelerate response time to genuine threats.đ Read more: 6G: What the Next Generation of Networks Brings
đ Network as Code: When Networks Speak Human Language
One of the most exciting elements of this collaboration is Nokia's "Network as Code" program. Instead of requiring technicians to write complex code, the system understands natural language. Imagine telling your network: "Prioritize all traffic from hospitals for the next two hours" â and the network does it, without manual engineering. This isn't science fiction, this is 2026.Implementation Challenges
Of course, transitioning to **network automation** isn't without obstacles. Nokia acknowledges that traditional operators are held back by legacy systems, siloed processes, and fragmented data.Unified Data Management
Integrated data management with data mesh architecture
360-degree Observability
Complete end-to-end chain of custody monitoring
Explainable AI
AI that clearly explains its decisions
đ Read more: AI RAN Networks: From Monitoring to Autonomous Control 2026
đŻ The Future of Global Networks
What do these developments mean for the global telecom space? Major carriers worldwide will need to watch these developments closely. Not just for technological advantages, but for economic benefits. Google reports that companies like Deutsche Telekom and Vodafone Group are already seeing operational cost savings and improved reliability. In an era where every dollar counts, automation could become a competitive advantage.The Global Challenge
However, implementing such solutions globally will face unique challenges. Implementation costs, the need for specialized personnel, and integration with existing infrastructure are issues requiring attention. On the other hand, many regions could benefit from the "leapfrog effect" â jumping directly to advanced solutions without the burden of older infrastructure.đź 2026: A Critical Year
2026 is shaping up as a critical year for **AI networks**. Google aims for Level 4 to 5 autonomy â networks that recognize, diagnose, and solve their own problems without human intervention. If this sounds ambitious, remember that a decade ago the idea of a smartphone understanding what we say was equally ambitious. Today, Siri and Google Assistant are everyday reality. The difference is we're now talking about critical infrastructure. A mistake in a voice assistant can be annoying. A mistake in an autonomous network can affect thousands of users. That's why companies insist on explainable AI. The system must not only work â we must understand why it makes specific decisions. Especially when those decisions affect millions of users daily. The question is no longer whether we'll have AI networks, but when and how quickly we'll adopt them. The first to do it right will have a significant competitive advantage. The rest will be playing catch-up.Sources: