2025年新一代智能运营_代理型AI驱动通信服务提供商运营模式转型白皮书_106页_15mb

Whitepaper Summary: New-generation Intelligent Operations

Objective:
Explore how telco CSPs can implement autonomous operations (AO) and autonomous networks (AN) using AI and human-machine collaboration to achieve operational efficiency and enhanced customer experience.

1. Industry Landscape

CSPs face increasing operational complexity due to technologies like 5G, IoT, and cloud-native architectures. AI-driven automation is critical for reducing costs, improving reliability, and meeting evolving customer expectations. Key technological enablers include:

• Autonomous Networks (AN): TM Forum's six-level taxonomy ranging from assisted O&M to fully autonomous systems.
• Autonomous Operations (AO): Focuses on business process automation with closed-loop decision-making.
• Core Technologies: Digital Twin Networks (DTNs), Generative AI (GenAI), Expected Demand Not Served (EDNS).

2. E.O.T. Framework (Evaluate, Operate, Transfer)

A systematic approach to digital operations transformation:

• Evaluate (Strategy Alignment): Decode corporate strategy into measurable business objectives using models like AOMM and VOF.
• Operate (Solution Design & Implementation): Design value streams, implement business-aligned solutions, and ensure continuous improvement.
• Transfer (Knowledge Sharing): Institutionalize operational knowledge and scale successful practices.

VOF (Value Operations Framework):

• Maps operational metrics (OPM) and KPIs to business values (R.I.S.E.: Revenue, Innovation, Satisfaction, Efficiency).

3. Transformation Journey to Autonomous Operations

• Key Stages:
  • Break down operational silos (monitoring, ticketing, workflows).
  • Evolve from reactive to proactive, predictive operations.
  • Leverage Agentic AI: Enables workflows to autonomously analyze and execute tasks.
• Platform Evolution:
  • Digital Twins: Provide end-to-end service lifecycle visibility.
  • Agent-Centric Systems: Modular microservices, API-driven architectures.

4. Case Studies (Operators: China Mobile, HKT, Telkomsel, STC)

• Shared Outcomes:
  • Substantial reduction in MTTR (e.g., 30-50%)
  • Increased automation (up to 99.5% of operations tasks resolved automatically)
  • Enhanced customer satisfaction (NPS improvement, reduced complaints)
    Strategies varied by region but emphasized cloud-native platforms and GenAI integration.

### Note: This summary adheres strictly to the provided content, skipping examples, case study details, and any unstated interpretations. Each section directly mirrors the module structure from the original document.