This White Paper provides an overview of adopting AI in fixed networks, moving from individual siloed research activities and proofs of concept (PoC) to real-world deployments and delivering an AI-native, intent-driven, self-operating infrastructure. It explains how advances from statistical machine learning (ML) to deep learning (DL) and large language models (LLMs) are reshaping network planning, operations, assurance, security, and customer experience. It also briefly addresses “Networks for AI,” outlining the transport and data centre interconnect upgrades required to support AI workloads. The report consolidates lessons from proofs of concept and live deployments, identifies gaps hindering scale, and discusses potential actions for ETSI and the industry to standardise interfaces, data, governance, and assurance of AI systems in multi-vendor fixed network environments.