Huawei has embraced the transformation of mobile networks from rule-based systems to intelligent agents capable of perceiving, concluding, and acting without human intervention. Over the last two years, Huawei’s objective for RAN intelligent agents has shifted from enabling individual areas for engineers to managing entire networks of radio access nodes. Their new unified RAN agent incorporates several AI-driven functions, replacing traditional operations. This trend is reflected in the recent AI MWC Barcelona and DTW Ignite 2026 events, where autonomous network development moved from conceptual debates to real-world applications, open-source initiatives, and operator-level demonstrations. Artificial intelligence is set to become integral to telecom network infrastructure, with the industry shifting from proofs-of-concept to commercial rollout to realize benefits in efficiency, performance, and energy consumption. Two major factors drive this shift: AI workloads are changing traffic patterns, as generative AI applications introduce interactive traffic more sensitive to latency, requiring constant uplink and downlink allocation. Additionally, network operations are becoming more complicated with new radios, spectrum bands, and technologies, making rule-based automation difficult. Unlike traditional automation following hard-coded logic, agentic networks observe, understand, recognize optimization opportunities, make choices, and learn from results, controlling and coordinating optimization across planning, execution, maintenance, and assurance.