Game X - Phase II builds on the success of Phase I, where we demonstrated “zero-wait, zero-touch, zero-trouble” operations and a 30% reduction in OpEx through intent-driven autonomy, to address one of the most significant market shifts of the decade: the explosive rise of AI workloads. As AI becomes a top IT investment priority and is projected to dominate global network traffic, CSPs must evolve beyond pure connectivity. Phase II introduces a new vertical, Artificial Intelligence Network Services, positioning service providers as essential enablers in the multi-trillion-dollar AI economy. Leveraging TMF921 Intent Management APIs, digital twin–based planning, and advanced closed-loop automation, the Catalyst defines a new category of services optimized for AI-driven applications and agent traffic—particularly across distributed training, inference, and WAN AI flows. In particular, we will focus on the “Model-as-a-Service" set of products as described in TMF GB1085. With “Model-as-a-Service", the service provider is able to become a true gateway for inference traffic, tapping into the large AI Cloud Infrastructure spending from B2B customers. At the heart of Phase II is a Two-Layer Agentic Architecture. The Demand Layer represents customer-side with two actors: the IT department who sets the interconnection intent (sovereignty, budget) and the AI agents themselves run by developers. These AI Agents require certain level of SLA both from the network (bandwidth, latency, packet drop) and the LLM layers (availability, time to frist token, etc.). . The Supply Layer represents the CSP’s autonomous network, dynamically provisioning AI-optimized slices and compute resources. TMF921 acts as the universal translation layer connecting intent to action, enabling AI applications to request outcomes (“EU sovereign GPT-OSS-120b with low latency”) that the network autonomously fulfills through zero-touch orchestration. No agentic implementation could be put into production without a governance and security layer. For this phase of the proyect, we introduce a governance layer that ensures the compliance of the different agets at the Supply Layer and provides the respective security checks. A new “Agentic Assurance” closed loops continuously monitor AI KPIs, adapt configurations, and preserve model performance—delivering superior customer experience and operational efficiency. By integrating autonomous operations with AI workload needs, Game X Phase II shows how CSPs can claim a differentiated role in the AI value chain, offering hyper-personalized, monetizable services instead of remaining best-effort transport providers. The Catalyst will define new AI service ontologies and introduce AI-focused KPIs to measure success, demonstrating how service providers can reuse TM Forum standards and autonomous capabilities to unlock new revenue, deliver predictable performance for critical AI applications, and secure a strategic position in the evolving AI market. TMF Resources: TMF921 Intent Management TMF915 API Component Suite for AI Management IG1218 Autonomous Networks Business Requirements and Framework IG1252 Autonomous Network Levels Evaluation Methodology IG1253 Intent in Autonomous Networks IG1256 Autonomous Network Effectiveness Indicators GB1059: Autonomous Network Levels Evaluation Guidebook GB900 ODA Blueprint GB1027_Zero_Touch_Partnering_Reference_Architecture_v1.0.0