生成式人工智慧：营运商的策略

本报告调查了营运商的新一代人工智慧策略，并总结了用例、实施挑战、实施策略和主要公司的概况。

实际好处：

• 比较生成式 AI 在通讯领域的用例，并制定考虑风险和机会的实施策略
• 透过在资料管理、成本、安全性和实施等关键领域进行规划，应对使用生成式 AI 的常见挑战
• 评估网路自动化市场影响与长期支持

关键问题的答案：

• 什么样的生成式人工智慧策略正在获得电信业的支持？
• 应该为网路管理开发生成式人工智慧，还是保留给客户服务和业务营运？
• 从模型类型选择到资料最佳实践，成功的营运商的生成式 AI 策略的关键组成部分是什么？
• 在推动自动化方面，生成式人工智慧与传统人工智慧有何关係？

研究亮点：

• 将生成式人工智慧的市场趋势解释为风险函数
• 详细分析了通讯网路中生成式人工智慧的优点和挑战
• 基于人工智慧的自动化的三个阶段分析

目录

执行摘要

建议

人工智慧世代及其使用

• 用例：适用性
• 市场：应用与趋势
• 市场趋势解读
• 生成式人工智慧为营运商带来的好处
• 简化营运
• 效能提升

赋值

• 与业务策略不一致
• 投资专用模型
• 使用公共模型时保护客户数据
• 产生的 AI 模型的资料管理
• 建立可解释的模型
• 实施时间表

使用策略

• 选择一个用例
• 选择型号类型
• 组织适应

对市场的影响

主要公司简介

• 通讯服务提供者
• 基础设施供应商

Actionable Benefits:

• Compare generative Artificial Intelligence (AI) use cases for telecommunications and build an application strategy that appreciates risks and opportunities.
• Preempt common challenges to generative AI usage, planning in key areas such as data management, cost, security, and implementation.
• Assess market impact and long-term support for network automation.

Critical Questions Answered:

• Which generative AI strategies are gaining traction in telecommunications?
• Should generative AI be developed for network management, or reserved for customer care and business operations?
• What are the main components of a successful telco generative AI strategy-from selecting a model type to data best practices?
• How does generative AI relate to traditional AI in advancing automation?

Research Highlights:

• Interpretation of market trends in generative AI as a function of risk.
• Detailed breakdowns of the benefits and challenges of generative AI for the telco network.
• Analysis of AI-based automation in three progressive stages.

Who Should Read This?

• Planners within telco organizations forming a generative AI strategy.
• Innovation leaders for Communication Service Providers (CSPs) who need to address the challenges of generative AI implementation.
• Business executives for CSPs who need to calibrate generative AI plans with broader company culture and strategy.
• Decision-makers for organizations that offer telco solutions for generative AI (e.g., platforms, data) to assess opportunities in the network.

Table of Contents

Executive Summary

Recommendations

Generative AI and Its Use

• Use Cases: Applicability
• Markets: Applications and Trends
• Interpretation of Market Trends
• Generative AI's Telco Benefits
• Operational Streamlining
• Performance Improvements

Challenges

• Misalignment with Business Strategy
• Investing in Proprietary Models
• Protecting Customer Data While Using Public Models
• Managing Data for Generative AI Models
• Building Explainable Models
• Implementation Time Frame

Strategies for Use

• Use Case Selection
• Model Type Selection
• Organizational Adaptations

Market Impact

Profiles of Select Commercial Entities

• Communication Service Providers
• Infrastructure Vendors