With integrated sensing and communications (ISAC), 6G can leverage shared hardware and processing to streamline end‑to‑end operations. When sensing powers high‑fidelity radio digital twins — virtual replicas of the radio environment — operators can continuously fine‑tune network performance, reduce energy consumption, and unlock entirely new classes of services. This demo shows how network‑integrated RF sensing combined with AI enables the creation of scalable and continuously updated radio digital twins in 6G. As wireless environments become more dynamic, AI models used by devices — for example, for beam prediction — must adapt efficiently without relying on large‑scale over‑the‑air data collection. This demo highlights the use of synthetic training data from radio digital twin to train environment‑specific AI models at scale, significantly reducing network traffic, energy consumption, and operational overhead. By combining these pre‑trained models with lightweight on‑device adaptation, this approach enables continuous optimization while minimizing data transfer, pointing toward a more efficient wireless AI model lifecycle for 6G. Energy efficiency is a foundational requirement for 6G. This demo highlights how 6G networks can use integrated sensing and communications (ISAC) and radio digital twins to optimize power consumption across both the network and devices. By combining RF sensing and AI, scalable digital‑twin‑aided radio modeling, and device‑level low‑power operating techniques (e.g., wake up receiver), 6G systems can dynamically adapt resources, reduce energy waste, and maintain a strong user experience — enabling a more sustainable and efficient wireless future.

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