5G traffic surges under growing AI usage
Future network evolution, 5G‑Advanced and edge-focused infrastructure, aims to integrate AI for smarter resource allocation and self-healing capabilities.
AI-driven applications are reshaping mobile data norms, and 5G networks are feeling the pressure. Analysts warn that uplink demand generated by tools like virtual assistants and AR platforms could exceed the current 5G capacity by around 2027. Traditional networks are built to handle heavier downlink traffic, leaving them under stress as AI flows increase in the opposite direction.
At the same time, artificial intelligence is playing a constructive role by helping optimise these strained networks. AI techniques, such as predictive traffic forecasting, dynamic spectrum allocation, beamforming, and energy management, are improving efficiency and reducing operational costs. Networks are becoming smarter in detecting congestion and self-adjusting to maintain performance.
Industry discussions point to 5G‑Advanced, also known as 5.5G, as a key evolution that embeds AI and machine learning into network architecture. These upgrades promise higher uplink speeds, tighter latency control, and built‑in intelligence for optimisation and automation. Edge computing is set to play a central role by bringing AI decision‑making closer to users.
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