Next-generation Networks: 3 AI Technologies to Watch at MWC 2026

February 2026

Telecoms & Connectivity

Ardit Ballhysa

Senior Research Analyst

AI is set to dominate the agenda at MWC Barcelona 2026.

Under the ConnectAI banner, the focus is on what actually happens when operator networks, AI, and machine learning start to converge in a meaningful way. That is, rethinking how networks are built and run, as operators move towards becoming genuinely AI-native.

A number of leading MNOs are now pushing towards Level 4 in TM Forum’s Autonomous Networks framework. That’s the point where automation starts handling complex, high-value scenarios with limited human input; not just optimising performance, but taking on more strategic decision-making across the network.

So, what does that mean for MWC? Expect announcements around Agentic AI, AI-RAN, and edge inferencing, as well as practical steps towards more autonomous infrastructure. Below, I look at what’s likely to surface at MWC 2026, and where operators should focus if they want AI to deliver real operational and commercial impact.

Agentic AI

Agentic AI has risen substantially over the last 24 months; garnering notable media attention. Agentic AI is a system comprising autonomous ‘agents’ underpinned by AI that can monitor their environments and act towards a predetermined goal.

Juniper Research envisages new product launches, announcements, and demonstrations for the integration of AI agents into the network, with the goal of introducing intelligent autonomy. Ericsson has already announced the launch of its Agentic rApp as a Service via AWS. This leverages Agentic AI and Generative AI for network optimisation using the Service Management and Orchestration (SMO) open architecture, and we expect other vendors and MNOs to follow with similar announcements. 

AI agents in the network are expected to be critical to expanding autonomous operations in cellular networks, as well as simplifying interactions through natural language interfaces that enable users to provide instructions to AI agents. These investments will enable MNOs to increase efficiency and reduce costs in their network operations; eventually moving towards using AI agents to optimise service delivery.

AI-RAN

AI-RAN is the integration of advanced AI and ML capabilities directly into the radio network layer of a telecoms network; enabling the RAN to analyse data, make decisions, and optimise performance autonomously.

By implementing AI in the RAN, operators can continually adjust the parameters, including spectrum allocation, beamforming, and energy consumption. This can be executed autonomously based on real-time network data. The end goal for operators is to make their networks as autonomous as possible. 

At MWC 2026, Juniper Research expects to see live demos for AI-RAN, with vendors such as Ericsson having already announced its launch of hardware such as AI-ready radios, antennas, and AI-RAN software. Juniper Research anticipates a key question for MNOs will be the potential of GPU-accelerated RAN, with MNOs considering whether there will be sufficient return on investment given the high cost of GPUs.

AI Inferencing at the Edge

A key technology MNOs will be demonstrating, discussing, and evaluating at MWC 2026 is AI inferencing at the edge, with MNOs weighing the potential of providing AI inferencing via edge nodes in the network, such as a base station. AI at the edge enables ultra-low latency and real-time autonomy by removing the need to send network requests to a centralised cloud system.

Recently, SoftBank and Nokia announced that SoftBank’s AITRAS Orchestrator can now interoperate with Nokia Bell Labs' AI platform (Nokia AI-RAN External Compute Engine). The AI platform brokers and manages computing resources provided by multiple operators; making it possible to support external AI workloads by enabling access to computing resources within an AI-RAN environment. 

Juniper Research believes that there will be much attention on the demonstrations, discussions of AI at the edge, and multi-tenancy, with MNOs looking for practical implementations, as well as analysis of potential demand and pricing. However, with multi-access edge computing having been overhyped, many in the telecommunications space are sceptical of similar services; therefore, MWC 2026 will be a platform for NVIDIA, SoftBank, and others to make the case for AI inferencing at the edge.

How Do Telcos Capitalise on the Emerging Opportunities for AI in Networks?

With the rise of these new technologies and the announcements expected at MWC 2026, how can telcos capitalise on these opportunities? Juniper Research recommends the following:

• Operators Must Use AI Gains to Increase Return on Spectrum Holdings: Discussions on the outlook of mobile networks and future technologies, such as 6G, regularly mention the necessity of new spectrum allocations to mobile networks. Juniper Research urges MNOs to prioritise the development of AI and AI agents for spectrum efficiency and spectrum sharing applications, as this will help minimise the additional costs associated with further spectrum purchases and increase the return on investment from existing holdings.
• Operators Must Position Themselves as Leaders in Sovereign AI: MNOs already possess strong relationships with governments and regulators, and have experience in providing and operating mission-critical services. They must leverage these traits to position themselves as leaders in the sovereign AI space, with Juniper Research expecting a continued trend towards sovereignty in the AI space.
• Establish Clear Business Cases for AI Inferencing at the Edge: MNOs must work with customers to build clear and realistic use cases for edge AI inferencing. These use cases will enable them to gauge potential return on investment and pricing for edge AI inferencing services; helping build confidence on the commercial viability of edge AI inferencing. Juniper Research expects IoT to be an important area to explore, with MNOs serving IoT connections both with connectivity and inferencing.

Ardit works within the Telecoms & Connectivity team; providing insights and strategic recommendations on current and future markets within the telecoms industry. His primary area of focus is on operator and CSP strategies. He previously worked at GlobalData for four years where he covered the technology and telecommunications industries, and prior to that, worked at Gartner for two years.