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GB/T 45907-2025: Artificial intelligence - Service capability maturity assessment
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GB/T 45907-2025: Artificial intelligence - Service capability maturity assessment

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ICS 35.240 CCSL70 National Standard of the People's Republic of China Artificial Intelligence Service Capability Maturity Assessment Released on June 30, 2025 Implementation on June 30, 2025 State Administration for Market Regulation The National Standardization Administration issued

Table of Contents

Preface III 1 Scope 1 2 Normative references 1 3 Terms and Definitions 1 4 Abbreviations 1 5 Service Capability Framework 2 5.1 Overview 2 5.2 Basic Abilities 3 5.3 Business Capabilities 4 6 Maturity Levels and Assessment Scores 5 6.1 Maturity Level 5 6.2 Maturity Assessment Score 6 7 Maturity Assessment Methods 13 7.1 Competency Item Weights 13 7.2 Calculation method 13 7.3 Maturity Level Determination 14 Appendix A (Informative) Weights of Some Scenario Capabilities 15 A.1 Home Smart Device Scenario 15 A.2 Smart Medical Diagnosis and Treatment Scenarios 17 A.3 Predictive Maintenance Scenarios for Industrial Equipment 19 Preface This document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for standardization work Part 1.Structure and drafting rules for standardization documents". Drafting is required. Please note that some of the contents of this document may involve patents. The issuing organization of this document does not assume the responsibility for identifying patents. This document was proposed and coordinated by the National Technical Committee for Information Technology Standardization (SAC/TC28). This document was drafted by. China Electronics Technology Standardization Institute, Xiaomi Communications Technology Co., Ltd., Guangzhou CESI Standards Testing Institute Co., Ltd., Inspur Cloud Information Technology Co., Ltd., Harbin Institute of Technology, Beijing Zhongshu Ruizhi Technology Co., Ltd., Shanghai SenseTime Intelligent Technology Co., Ltd., Hangzhou Hikvision Digital Technology Co., Ltd., Institute of Automation, Chinese Academy of Sciences, Institute of Software, Chinese Academy of Sciences, Inspur Software Technology Co., Ltd., Tencent Technology (Shenzhen) Co., Ltd., China Electronics Standardization Association, Inspur Electronic Information Industry Co., Ltd., Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Yuyang Information Technology (Shanghai) Co., Ltd., Weilin Information Technology Development (Shanghai) Co., Ltd., Midea Group (Shanghai) Co., Ltd., and the Fifth Electronic Research Institute of the Ministry of Industry and Information Technology. The main drafters of this document are. Xu Yang, Ma Shanshan, Ma Chenghao, Ye Heng, Zhu Yajun, Zhou Juejia, Zhou Gang, Zheng Jiajia, Yang Muyun, Han Han, Wu Geng, Peng Jianfeng, Zhu Guibo, Meng Lingzhong, Yang Yuze, Lu Shun, Nie Jiandi, Shen Zhiyue, Sun Chuanxing, Huang Xiancui, Li Zhaochuan, Wang Gongming, Dai Wei, Chen Qingshuai, Zhao Mengfang, Huang Shenghua, Di Heliang, Pu Jiangbo, Zhu Zhaoying, Weng Jialiang, Cai Yasen, and Huang Linyi. Artificial Intelligence Service Capability Maturity Assessment 1 Scope This document proposes an AI service capability framework, specifies maturity levels and assessment scores, and describes the assessment methodology. This document is applicable to the maturity assessment of the AI service capabilities provided by service providers, as well as the capability domains, Individual assessment of competency items. 2 Normative references The contents of the following documents constitute the essential clauses of this document through normative references in this document. For referenced documents without a date, only the version corresponding to that date applies to this document; for referenced documents without a date, the latest version (including all amendments) applies to This document. GB/T 41867 Information Technology and Artificial Intelligence Terminology 3 Terms and Definitions The terms and definitions defined in GB/T 41867 and the following apply to this document. 3.1 capabilitysub-item Several characteristic indicators that constitute maturity in the capability subdomain. 3.2 The weight factor of the corresponding capability sub-item in the evaluation of the capability sub-domain. 3.3 service availability The ratio of the service access time to the total service time after the service customer initiates a service request. Note. Availability is calculated as the ratio of the sum of the service available time to the sum of the predefined time periods in a series of predefined time periods. Service unavailable time. 3.4 Artificial intelligence services can provide basic capabilities such as storage, computing, data structured processing and decision-making, machine learning, and intelligent voice, automatic It has business capabilities such as natural language understanding, intelligent dialogue, and intelligent image and video analysis. 4 Abbreviations The following abbreviations apply to this document. ...