Research on the application scenarios and trends of AI in empowering telecom user complaint management

doi:10.12267/j.issn.2096-5931.2025.12.008

Abstract

Abstract:

As users’ expectations for telecommunications services continue to rise, a key challenge for the industry is to strengthen its complaint resolution capabilities and consistently meet the people’s growing demand for high-quality service. The application of AI technology can significantly enhance the quality of user complaint services, improve the efficiency of complaint handling, and reshape the complaint service model. By reviewing the main application scenarios of AI in the telecommunications complaint domain, the key challenges currently faced in its implementation, and its future trends, the study aims to offer insights into how technological means can be leveraged to improve telecommunications user service capabilities.

Key words: AI, telecom user complaints, intelligent decision-making, intelligent agent.

CLC Number:

TP183
F626

XIN Xing, WU Jun, WANG Haiyan, ZHANG Yang, GUO Wei. Research on the application scenarios and trends of AI in empowering telecom user complaint management[J]. Information and Communications Technology and Policy, 2025, 51(12): 57-62.

Add to citation manager EndNote|Ris|BibTeX

URL:

http://ictp.caict.ac.cn/EN/10.12267/j.issn.2096-5931.2025.12.008

http://ictp.caict.ac.cn/EN/Y2025/V51/I12/57

技术类别	核心功能	关键技术组成
多模态交互与内容解析	实现用户语音、文本等信息的自动识别、理解与拟人化交互	自动语音识别、自然语言处理、大语言模型、文本转语音
知识构建与自动执行	将企业知识结构化,并自动化执行标准业务流程	知识图谱、机器人流程自动化
数据分析与智能生成	从数据中挖掘洞察,并生成高质量、合规的文本内容	检索增强生成、时序预测算法、聚类算法

技术类别	核心功能	关键技术组成
多模态交互与内容解析	实现用户语音、文本等信息的自动识别、理解与拟人化交互	自动语音识别、自然语言处理、大语言模型、文本转语音
知识构建与自动执行	将企业知识结构化,并自动化执行标准业务流程	知识图谱、机器人流程自动化
数据分析与智能生成	从数据中挖掘洞察,并生成高质量、合规的文本内容	检索增强生成、时序预测算法、聚类算法

应用类别	核心特征	典型应用场景
承接流程类	流程自动化、规则标准化、人工替代	智能语音机器人、工单智能派发、智能回访外呼、数字员工
辅助提升类	人机协同、实时赋能、效率提升	智能坐席助手、自动填单、话术推荐、案例推送
质检监管类	过程管控、数据驱动、质量改进	全量智能质检、情感轨迹分析、智能报告生成
预警治理类	预警预测、根源治理、资源优化	投诉预警预测、热点聚类挖掘、区域热点分析

应用类别	核心特征	典型应用场景
承接流程类	流程自动化、规则标准化、人工替代	智能语音机器人、工单智能派发、智能回访外呼、数字员工
辅助提升类	人机协同、实时赋能、效率提升	智能坐席助手、自动填单、话术推荐、案例推送
质检监管类	过程管控、数据驱动、质量改进	全量智能质检、情感轨迹分析、智能报告生成
预警治理类	预警预测、根源治理、资源优化	投诉预警预测、热点聚类挖掘、区域热点分析

[1]	余晓晖. 推动“人工智能+政务”深度融合赋能政务领域数智转型升级[EB/OL]. (2025-10-10)[2025-10-26]. https://www.cac.gov.cn/2025-10/10/c_1761819470255103.htm.
[2]	朱婷婷, 贠杰. 从浅层结合走向深度融合: 数字政府场景化应用的优化路径[J]. 电子政务, 2025(2): 2-16.
[3]	王勃. AI赋能运营商云业务机遇、挑战与应对之策[J]. 通信世界, 2025(7): 34-35.
[4]	胡晓峰. AI赋能客服热线的用户体验优化与个性化服务机制探索[J]. 中国电子商情, 2025(15): 121-123.
[5]	中国信息通信研究院. 智能体技术和应用研究报告(2025)[R], 2025.

Research on the application scenarios and trends of AI in empowering telecom user complaint management

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 2

References 5

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	LONG Haiquan, WANG Shaoshuai, LI Ke. Research on “AI+” empowering IPv6 network management and technical solutions [J]. Information and Communications Technology and Policy, 2025, 51(8): 10-14.
[2]	LI Tengda, ZHU Ziyu, HAN Ziqi. Key technologies and typical applications of “AI+” empowered embodied intelligence robots [J]. Information and Communications Technology and Policy, 2025, 51(8): 15-25.
[3]	WU Yingying, SONG Ping, REN Lu. The necessity and implementation path of China’s “AI+” initiative [J]. Information and Communications Technology and Policy, 2025, 51(8): 2-9.
[4]	YAN Jiangyi, LI Sun, FAN Wei, CAO Feng. Research on the mechanism of action and practical path of the new generation of data annotation industry on the innovation of the “AI+” paradigm [J]. Information and Communications Technology and Policy, 2025, 51(8): 26-34.
[5]	HU Wenjuan, YAN Zhaokun, MENG Danni, XU Shan, JIANG Bocheng, XU Lijiao, CHEN Guangtuo, ZHANG Yi. Exploring the path of empowering the natural gas industry with “AI+” [J]. Information and Communications Technology and Policy, 2025, 51(8): 35-41.
[6]	DONG Hao, ZHOU Jingcai. Research on key technologies of artificial intelligence for research and development [J]. Information and Communications Technology and Policy, 2025, 51(8): 42-49.
[7]	WANG Rui, ZUO Kairui, JIANG Yiwei. Achievements, problems and suggestions of integrated development of AI and information communication industry [J]. Information and Communications Technology and Policy, 2025, 51(8): 50-54.
[8]	WU Chongqing, YANG Sizhe, NING Tingyong, HU Yongbo. Exploration of domain-specific large model applications in Shanghai’s digital government [J]. Information and Communications Technology and Policy, 2025, 51(8): 78-83.
[9]	HE Lizhen, WANG Zhentao. Energy and AI co-evolution: from computing power revolution to sustainable development pathways [J]. Information and Communications Technology and Policy, 2025, 51(6): 15-20.
[10]	ZHAO Junsheng. Large AI models bring new digital vitality to the energy sector [J]. Information and Communications Technology and Policy, 2025, 51(6): 2-7.
[11]	YUE Jinjiang, NING Tingyong. Applications of AI in solid-state hydrogen storage materials [J]. Information and Communications Technology and Policy, 2025, 51(6): 21-26.
[12]	LIU Wei, LI Zhaoyang, SHI Haichao. Research on the policy system and application challenges of AI-driven energy transformation [J]. Information and Communications Technology and Policy, 2025, 51(6): 27-32.
[13]	GE Jian, NIU Xiaoyan, BI Ran, HUANG Yongtao. Low-carbon AI: research on green training and inference optimization methods for large model [J]. Information and Communications Technology and Policy, 2025, 51(6): 44-51.
[14]	HUANG Shuwei, JIN Feng, CHEN Jiwei, ZHAO Chongyan. AI empowers intelligent and innovative development in mine production [J]. Information and Communications Technology and Policy, 2025, 51(6): 8-14.
[15]	LU Tianfeng, TAO Xiangren, JING Haomeng. Research on the construction of product carbon footprint in the park based on integration of identity resolution and blockchain [J]. Information and Communications Technology and Policy, 2025, 51(5): 2-11.