新一代智能运营：代理型AI驱动转型

CONTRIBUTING INDIVIDUALSContributors andcontributing companiesCONTRIBUTING COMPANIESChina MobileXie Hongtao, Cai Xuhui, Li Ji, Chen Xi, Liu Pengfei, Xin Mingqin, Dong Wei, Yang Ce,Yan Yabo, Yu Qing, Wang Jiang, Zheng Qing, Zhang Shipeng, Yang Guangda, Zhang Wei,Wang Deng, Fan Zhiyu, Yan Qiqi, Tan Rong, Sun Xiao, Suo Yun, Zhou Yifei, Cheng Yun,Xu Jian, Yang Xu, Xu BinHKTTom Pang, Michael Yue, Fung Kam-ShingJazzMuhammad Latif Hussain, Mohammad Waqas IqbalOmantelBasel Hameed Mundanadath Poyil, Aziza Najeeb Khamis Al Zadjali, Fawad HameedAndicha Brilian, Luthfi AuzanSTCMohammed E. Alzaaidi, Nawaf K. Alkhateeb, Rakkad A. AlanaziTelkomselTrihan Marsudi, Hery Widjayanto, Amri Khoirul Fath, A. Moelky Furqon, JendrohartonoUnitelBat-Erene G., Ganchimeg D.Vodafone TürkiyeSerkan Cebi, Veysi Doster, Hasan Arslan, Gorkem Azder, Yilmaz Polat, Murat Erdim, Cağdaş TomanHuaweiLucas Lu,Ye Rongchun (Kevin Ye), Jiao Dongfeng (Frank Jiao), Hou Yuzhou, Ouyang Yongjian(Henry Au Yeung), Lan Yu, Yang Shengdong, Jin kaixu, Yu Yefu, Goh Khiang Chew, Charlene Wong,Peter Lam, Liu Wenxuan, Li Kunwu, Yang Zhicheng, Xin Long, Jia Jianhui, Huang Shuo,Muhammad Ozeir Khan, Fahad Alam Khan, Bambang Budiharto, Ramesha Muninagappa,Ma Feng (Jimmy), Yang XiaopingTM ForumRichard WebbGraphics throughout supplied by Huawei or contributing companies unless otherwise stated. IOH contentsExecutive summarySection 1. Industry landscape: service-centric operations1.1.1 Summary: enhancing service-centric operations with AI and value metrics1.1.2 Transformation frameworks and tools: AN, AO maturity models, VOF1.1.3 Core technological features: DTN, GenAI, EDNS1.2 Industry landscape: AI is dynamically disrupting service-centric operations1.2.1 AI driving automation acceleration1.2.2 GenAI use cases coming to market1.2.3 Agentic AI1.3 Service-centric operations: CSP transformation trends and new use cases1.3.1 From digital telco to digital techco: characteristics of service-centric operations1.3.2 Automation drivers and high-value scenarios1.3.3 Improvement indicators1.4 Key challenges on the transformation journey1.4.1 Operational challenges: network and service complexity1.4.2 AI challenges: network and operational readiness and data challenges1.4.3 Intelligent operations digital transformation frameworkSection 2. Objectives for an E.O.T. framework2.1.1 Challenges encountered in digital transformation2.1.2 Towards high value service-centric operation2.1.3 High value service-centric operating model2.2 Realizing high value service-centric operating model through value streams2.3 Introduction to E.O.T. digital operations transformation framework2.3.1 Evaluate stage of E.O.T.2.3.1.1 Decoding of enterprise strategy into smart business objectives2.3.1.2 Business capability model2.3.1.3 Manifesting values: a value operations framework (VOF) approach2.3.1.4 Differentiating the cause (OPM) and effects (KPI)2.3.1.5 Business values manifestation2.3.2 Operate stage of E.O.T.2.3.2.1 Business-aligned solution design for digital operations2.3.2.2 Project implementation2.3.3 Transfer stage of E.O.T.2.3.3.1 Transfer of operations2.3.3.2 Continual improvement 77810111111121213141415161718181819212121232323242929313232331219 contents©TM Forum 2025. The entire contents of this publication are protected by copyright. All rights reserved. The views and opinions expressed in this whitepaper are provided in the contributors’ personal capacities and may not reflect the views of their companies. While all care has been taken in preparationof this paper, no responsibility for any loss occasioned to any person acting or refraining from any action as a result of any material in this publicationcan be accepted by the editors, contributors or publisher.Section 3. The transformation journey to autonomous operations3.1.1 Recap of whitepaper 1.0: key challenges of service-centric transformation3.1.2 Recap of whitepaper 2.0: key characteristics of aservice-centric transformation path3.2.1 New characteristics introduced in whitepaper 3.03.2.2 “Workflow” vs “agent”3.2.3 Reviewing the transformation journey since whitepaper 1.03.3.1 Copilot / AI agent framework, methodology & components3.3.2 Operation process re-engineering3.3.3 Platform architecture evolution3.3.4 New technologies enabling copilot / AI agent3.4.1 Reference implementation & key technical challenges of aunified data foundation3.4.2 Flexible adaption to general-purpose large models &domain-specific large models3.4.3 The importance of a knowledge center in enabling autonomousagents and the correlation between data, intelligence and knowledge3.5.1 Toolchain as a key part of the autonomous agent3.6.1 ‘To the Consumer’ service and network assurance: introducingautonomous agent technology to maximize machine self-closed-loopand minimize human intervention3.6.2 ‘To the Home’ service and network assurance: fast locationof optical cable breakpoint to support rapid service recovery3.6.3 ‘To the Business’ service and network assurance: