This Catalyst delivers a trusted, AI-driven operational foundation that enables communications service providers (CSPs) to move from fragmented, manual network operations to closed-loop, autonomous resource and network management. Today, misalignment between physical infrastructure, digital asset records, and field execution creates operational risk, wasted resources, safety exposure, and a fundamental barrier to autonomy. Traditional audits and inspections are labor-intensive, error-prone, and impossible to scale as networks grow. The solution connects physical assets, digital systems, and frontline operations into a continuous cognitive loop. Using AI-powered visual inspection, multimodal data analysis, digital employees, and intelligent workflows, CSPs can automatically identify, validate, optimize, and retire network resources while embedding safety and governance directly into daily operations. Advanced image correction, stitching, and object recognition enable accurate, scalable verification of real-world assets, sustaining physical-to-digital consistency above 99% and resource accuracy above 95%, while dramatically reducing manual inspection effort. Innovation lies not only in the use of AI vision, but in how it is operationalized. AI capabilities are packaged as reusable, API-driven “digital employees” and integrated into provisioning, maintenance, and inspection workflows, enabling real-time decision-making, automated remediation, and accountability through closed-loop execution. The solution also extends asset governance to systematically manage idle and underutilized resources, improving reuse, accelerating retirement, and reducing capital waste. Proactive, AI-enabled safety governance further transforms frontline safety from a reactive compliance activity into a measurable, preventive capability. Aligned with TM Forum Open Digital Architecture (ODA) and closed-loop operational principles, the modular and replicable approach is production-proven and scalable across regions and use cases. Success is measured through sustained asset accuracy, reduced manual audits, faster remediation cycles, improved safety performance, and expanded automation coverage. Ultimately, the Catalyst shows how trusted asset data, embedded AI, and closed-loop governance form the cognitive foundation required to safely scale automation and advance toward truly autonomous network operations.