PRISM-AI Phase III accelerates the telecom industry's journey towards Autonomous Networks by unifying operational assurance, sustainability, and Agentic AI into a single intelligent closed-loop solution. Built on the proven foundation of previous PRISM-AI phases, the project extends beyond fault resolution and service experience management to address one of the industry's most pressing challenges: achieving net-zero objectives while maintaining network reliability and operational efficiency. By transforming sustainability from a reporting activity into a real-time operational capability, PRISM-AI enables communications service providers (CSPs) to improve network performance, reduce costs, and lower carbon emissions simultaneously. At the heart of the innovation is a powerful new approach that uses a single power-domain IoT signal to deliver multiple business outcomes. Telemetry from batteries, rectifiers, cooling systems, and energy consumption not only predicts degradation-based faults before they impact services, but also identifies opportunities for energy optimisation. This eliminates the traditional separation between network operations and ESG initiatives, allowing operators to use the same data source to improve reliability, reduce waste, and achieve measurable sustainability gains. PRISM-AI Phase III also introduces end-to-end multi-domain correlation across Power, Transmission, Edge Cloud and IP networks, addressing one of the biggest operational challenges facing modern NOCs. Instead of generating dozens of disconnected alarms for a single underlying issue, the solution correlates events across domains to identify a single root cause and accurately determine service impact. This significantly reduces alarm noise, accelerates root-cause identification, shortens repair times, and enables operators to move from reactive firefighting towards proactive, autonomous operations with greater confidence and control. The solution is completed by policy-governed Agentic AI, delivering trusted automation with full auditability and regulatory readiness. Autonomous actions are executed through controlled, least-privilege AI agents operating within defined policies and supported by immutable traceability. The result is a practical and trustworthy pathway towards higher Autonomous Networks maturity, where CSPs can reduce operational costs, achieve 15-25% energy savings, lower carbon emissions, minimise SLA breaches, and strengthen customer trust through a single coordinated investment that advances reliability, sustainability, and autonomy together.