生成式人工智慧：營運商的策略

本報告調查了營運商的新一代人工智慧策略，並總結了用例、實施挑戰、實施策略和主要公司的概況。

實際好處：

• 比較生成式 AI 在通訊領域的用例，並制定考慮風險和機會的實施策略
• 透過在資料管理、成本、安全性和實施等關鍵領域進行規劃，應對使用生成式 AI 的常見挑戰
• 評估網路自動化市場影響與長期支持

關鍵問題的答案：

• 什麼樣的生成式人工智慧策略正在獲得電信業的支持？
• 應該為網路管理開發生成式人工智慧，還是保留給客戶服務和業務營運？
• 從模型類型選擇到資料最佳實踐，成功的營運商的生成式 AI 策略的關鍵組成部分是什麼？
• 在推動自動化方面，生成式人工智慧與傳統人工智慧有何關係？

研究亮點：

• 將生成式人工智慧的市場趨勢解釋為風險函數
• 詳細分析了通訊網路中生成式人工智慧的優點和挑戰
• 基於人工智慧的自動化的三個階段分析

目錄

執行摘要

建議

人工智慧世代及其使用

• 用例：適用性
• 市場：應用與趨勢
• 市場趨勢解讀
• 生成式人工智慧為營運商帶來的好處
• 簡化營運
• 效能提升

賦值

• 與業務策略不一致
• 投資專用模型
• 使用公共模型時保護客戶數據
• 產生的 AI 模型的資料管理
• 建立可解釋的模型
• 實施時間表

使用策略

• 選擇一個用例
• 選擇型號類型
• 組織適應

對市場的影響

主要公司簡介

• 通訊服務提供者
• 基礎設施供應商

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