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AI‑native Networks, NTN Progress and the Road to 6G

The Mobile World Congress panel highlighted a shifting narrative: AI is no longer a side topic but a core driver for both network optimization and new service monetization. Participants debated “AI for networks” versus “networks for AI,” underscoring how telecom operators must leverage artificial intelligence to boost efficiency while also positioning their infrastructure as the backbone for AI‑powered applications. Key insights included the validation of Open RAN as the preferred foundation for large‑scale AI deployment, with the open front‑hall at MWC showing broad vendor compliance. Despite this progress, global 5G Stand‑Alone adoption lags under 25%, tempering immediate pressure for a 6G rollout. The conversation also pivoted to the transition from AI training to inference workloads, which promise lower latency demands and new revenue streams for operators. Notable moments featured TIP’s board meeting reaffirming a strategic focus on AI at scale, and concrete examples such as language‑model‑driven network analytics built on open SMO interfaces. Speakers emphasized that AI‑ran solutions can be layered atop existing Open RAN stacks, and that edge compute placement—referred to as “compute latency”—will become a decisive factor in delivering real‑time inference. The implications are clear: operators who accelerate software‑defined, open‑RAN‑based networks can capture AI inference revenue, reduce operational costs, and extend the economic life of 5G while laying a pragmatic foundation for future 6G capabilities. Flexibility, edge compute, and open interfaces will be the competitive differentiators in the next telecom evolution.