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Nokia and AWS pilot AI automation for real-time 5G network slicing

versatileaiBy versatileaiFebruary 26, 2026No Comments4 Mins Read
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Telecommunications networks may soon start adjusting in real-time as carriers test systems that allow AI agents to manage traffic and quality of service. AI may soon be making operational decisions.

This week, Nokia and AWS announced a new network slicing system that uses AI agents to monitor network health and automatically adjust resources. According to a joint Nokia announcement, the setup is being tested by carrier du in the United Arab Emirates and Orange in Europe and Africa.

Adaptive AI-powered network

Network slicing allows operators to create multiple virtual networks on the same physical infrastructure, each tailored for a different purpose. For example, slices can be configured for emergency services or high-bandwidth consumer traffic. Slicing is part of the 5G standard, but it often requires manual planning and fixed configuration, which limits how quickly networks can respond to changes in demand.

The new system aims to fill that gap by introducing AI agents that track network performance metrics such as latency and congestion, and consider data such as event schedules and weather conditions. According to Nokia’s pilot description, agents can adjust network settings to keep services running at agreed-upon performance levels.

AWS said the solution combines Nokia’s slicing and automation tools with AI models provided through Amazon Bedrock, the company’s managed AI services platform. The companies describe this approach as “agent AI.”

autonomous connectivity

Interest in such systems reflects long-standing challenges. 5G networks have delivered faster speeds and lower latency, but carriers have struggled to turn those technological gains into new revenue streams. Research firm GSMA Intelligence notes that while many carriers see network slicing as a potential source of corporate revenue, operational complexity and uncertain demand have slowed implementation.

If networks can quickly adapt to sudden demands, such as a crowded stadium or emergency responders entering a disaster zone, carriers may be able to provide temporary connectivity or guaranteed service levels without manual setup.

Orange previously said business customers expect connectivity to behave like cloud computing, with resources able to scale on demand. Systems that allow automatic control of network resources could help bring communications services closer to that model.

Cloud platform and communication network operation

The test also revealed how cloud providers are involved in the telecom business. Over the past few years, some carriers have moved parts of their core networks to public cloud platforms or built cloud-based control systems. Industry analysts at Dell’Oro Group report that communications cloud spending is increasing as carriers modernize their networks and adopt software-driven infrastructure.

Adding an AI-driven control loop on a cloud platform represents the next step in having AI systems monitor conditions and quickly apply adjustments.

This technology is still in the testing phase. Nokia’s announcement explains that its work with Orange will be a demonstration and pilot deployment. Questions remain about how such systems could be deployed, how operators would oversee automated decisions, and how regulators would view AI control of critical communications infrastructure.

Telecommunications networks carry critical traffic, so reliability and accountability remain key concerns. Operators typically introduce automation gradually and maintain human oversight while validating the system’s operation under real-world conditions.

This experiment suggests that AI is beginning to act as an operational controller, adjusting physical and virtual resources in response to live events.

Businesses that rely on private 5G networks in factories or large venues may have access to connections that adjust automatically. This can impact how enterprises design applications that rely on stable and predictable network performance.

(Photo provided by M. Lennim)

See also: How e& leverages HR to bring AI to company operations

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