表紙
市場調查報告書
商品編碼
1057440

聯絡中心人工智能 (AI) 的現狀

The State of Artificial Intelligence in Contact Centers

出版日期: | 出版商: DMG Consulting LLC | 英文 | 商品交期: 最快1-2個工作天內

價格
  • 全貌
  • 簡介
  • 目錄
簡介

通過將人工智能技術 (AI) 融入聯絡中心和客戶體驗解決方案,服務行業正在以前所未有的速度進行創新和改進。儘管在服務環境中仍處於起步階段,但 AI 正在展示其在提高質量、生產力和員工敬業度的同時增強 CX 的能力。

本報告調查了聯絡中心人工智能 (AI) 的現狀,分析了 AI 如何提高聯絡中心性能、AI 及其底層技術,以及如何增強聯絡中心系統和應用程序。人工智能用例。

示例

目錄

第 1 章執行摘要

第二章介紹

第三章聯絡中心人工智能(AI)的定義與解釋

  • 規則與AI對比
  • 自動化在人工智能世界中的位置
  • 數據是人工智能計劃成功的關鍵

第4章AI在強化CX中的作用

第 5 章聯絡中心的 AI 視覺

  • 對聯絡中心 AI 中心運營的影響

第 6 章聯絡中心 AI 兼容應用程序

  • 支持人工智能的系統和應用聯絡中心產品組合
  • 用於聯絡中心的支持人工智能的系統和應用程序
    • 智能虛擬代理/交互式人工智能
    • 交互(語音和文本)分析
    • 分析質量控制
    • 虛擬助手
  • 針對聯絡中心的 AI 系統和應用程序
    • 錄音
    • 實時指導
    • 預測行為路由
    • 預測分析
  • 用於聯絡中心的新 AI 系統和應用程序
    • 勞動管理
    • 客戶旅程分析
    • 客戶關係管理
    • 聯絡中心績效管理
    • 自動來電分配器
    • 撥號器/廣告系列管理
  • 為聯絡中心的人工智能係統和應用做出貢獻
    • 機器人流程自動化
    • 智能採用
    • 桌面分析
    • 知識管理
    • 語音生物識別
    • 客戶評價/調查

第7章聯絡中心AI之旅

  • 聯絡中心成熟度模型
    • 反應式聯絡中心 (2021)
    • 響應式聯絡中心 (2022-2025)
    • 實時聯絡中心 (2026-2030)
    • 主動聯絡中心 (2031-2035)
    • 預測聯絡中心 (2036)
  • 人工智能在聯絡中心的作用和貢獻

第8章最終考慮

附錄 A:AI 術語和技術

關於 DMG 諮詢有限公司

目錄

DMG Consulting LLC's special report on ‘The State of Artificial Intelligence in the Contact Center’ analyzes how artificial intelligence (AI) can be applied to transform the customer experience (CX), drive a new era in servicing, and significantly improve the performance of contact centers. It explains AI, its underlying technologies and how it enhances contact center systems and applications. The Report provides use cases for AI today and looks ahead to discuss the exciting future of this technology, also analyzing the value proposition and payback for its adoption in each application.

The inclusion of AI technology in contact center and CX solutions is driving the most rapid pace of innovation and improvement ever seen in the service sector. Artificial intelligence is being added to all of the systems and applications used by contact center agents. It has already introduced a basic form of human-like understanding and intelligence into self-service solutions and is on its way to delivering practical and quantifiable improvements to many other applications. Although in the early days of use by service environments, AI is demonstrating its ability to enhance the CX while improving quality, productivity and employee engagement.

AI is already making important contributions to many facets of the service experience. Computer vision is being used to "see" and make recommendations for action based on visual input. Machine learning is detecting patterns in massive data sets to identify tasks and activities that can be handled better with intelligent automation. Speech analytics is delivering valuable insights based on its ability to structure customer conversations and understand callers' wants and needs. Next-best-action capabilities guide agents to achieve optimal outcomes in the first contact. And predictive behavioral routing is identifying customers' conversation styles and matching them with the best-fit agent.

Artificial intelligence is an expanding group of technologies that, when supported by an appropriate data repository, can discern patterns and emulate human reasoning and behaviors. Once the processing steps for each type of customer inquiry or transaction are recognized, AI can enhance, or possibly fully automate, the handling and resolution of future transactions. This frees up agents to perform higher-value and more complex activities. At least 50% of contact center tasks are repetitive, so this means that applying AI technology to resolve them will be beneficial for customers, agents and the company's bottom line.

This Report also provides a maturity model for the service experience in contact centers, looking ahead to the next 15 years. It describes how AI can and should be used, application by application, to enhance contact center performance and provides recommendations and best practices for implementing AI-enabled solutions. It provides both a strategic perspective and tactical guidance to help companies realize the maximum benefits from their AI initiatives.

SAMPLE VIEW

Key Reasons to Buy This Report:

  • Explanation of what AI means and how it works in contact center systems and applications, including the distinction between AI and rules-based solutions; the synergies and benefits of AI-enabled automation; and essential role of data in powering AI initiatives
  • How AI is fundamental in enhancing the CX due to its ability to decipher customer expectations and deliver this information to agents
  • An explanation of DMG's concept of a centralized contact center "AI hub/brain" and its operational contributions and benefits
  • An analysis of the maturity and impact of AI in 20 of the most commonly used contact center solutions, plotted by quadrant - AI-enabled, targeted AI, emerging AI, and contributing AI
  • An in-depth review and analysis of how AI is being applied in each of the top 20 contact center solutions, including a discussion of how it enhances each one, current and future use cases, as well as the value proposition and benefits
  • A contact center maturity model that looks 15 years into the future to enable contact center leaders to appreciate how they are perceived today and their next steps in the service continuum
  • A visionary examination of the massive potential of AI to revolutionize contact centers and the service experience in the future

Table of Contents

I. Executive Summary

II. Introduction

III. Contact Center AI Defined and Explained

  • III.1 Rules vs. AI
  • III.2 Where Automation Fits in the World of AI
  • III.3 Data is a Key to the Success of AI Initiatives

IV. The Role of AI in Enhancing the CX

V. The Vision for AI in Contact Centers

  • V.1 Operational Impact of the AI Hub in Contact Centers

VI. Contact Center AI-Enabled Applications

  • VI.1 Contact Center Portfolio of AI-Enabled Systems and Applications
  • VI.2 AI-Enabled Systems and Applications for Contact Centers
    • VI.2.1 Intelligent Virtual Agent/Conversational AI
    • VI.2.2 Interaction (Speech and Text) Analytics
    • VI.2.3 Analytics-Enabled Quality Management
    • VI.2.4 Virtual Assistant
  • VI.3 Targeted AI Systems and Applications for Contact Centers
    • VI.3.1 Transcription
    • VI.3.2 Real-Time Guidance
    • VI.3.3 Predictive Behavioral Routing
    • VI.3.4 Predictive Analytics
  • VI.4 Emerging AI Systems and Applications for Contact Centers
    • VI.4.1 Workforce Management
    • VI.4.2 Customer Journey Analytics
    • VI.4.3 Customer Relationship Management
    • VI.4.4 Contact Center Performance Management
    • VI.4.5 Automatic Call Distributor
    • VI.4.6 Dialer/Campaign Management
  • VI.5 Contributing AI Systems and Applications for Contact Centers
    • VI.5.1 Robotic Process Automation
    • VI.5.2 Intelligent Hiring
    • VI.5.3 Desktop Analytics
    • VI.5.4 Knowledge Management
    • VI.5.5 Voice Biometrics
    • VI.5.6 Voice-of-the-Customer/Surveying

VII The Contact Center AI Journey

  • VII.1 The Contact Center Maturity Model
    • VII.1.1 Reactive Contact Centers, 2021
    • VII.1.2 Responsive Contact Centers, 2022 - 2025
    • VII.1.3 Real-Time Contact Centers, 2026 - 2030
    • VII.1.4 Proactive Contact Centers, 2031 - 2035
    • VII.1.5 Predictive Contact Centers, 2036
  • VII.2 Role and Contributions of AI in Contact Centers

VIII. Final Thoughts

Appendix A: AI Terms and Technologies

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