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市場調查報告書

用於企業的虛擬數位助理(VDA):活用AI、自然語言處理、對話式使用者介面的虛擬代理人、聊天機器人、虛擬助理

Virtual Digital Assistants for Enterprise Applications: Virtual Agents, Chatbots and Virtual Assistants for Enterprise Markets Utilizing Artificial Intelligence, Natural Language Processing and Conversational User Interfaces

出版商 Omdia | Tractica 商品編碼 335100
出版日期 內容資訊 英文 55 Pages; 30 Tables, Charts & Figures
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價格
用於企業的虛擬數位助理(VDA):活用AI、自然語言處理、對話式使用者介面的虛擬代理人、聊天機器人、虛擬助理 Virtual Digital Assistants for Enterprise Applications: Virtual Agents, Chatbots and Virtual Assistants for Enterprise Markets Utilizing Artificial Intelligence, Natural Language Processing and Conversational User Interfaces
出版日期: 2019年11月19日內容資訊: 英文 55 Pages; 30 Tables, Charts & Figures
簡介

十多年前,每個企業都為無法將自然語言處理(NLP)運用在顧客服務效率化、自動化而煩惱。進入2016年,受到人工智慧或機器學習/深層學習的幫忙,用於企業的虛擬數位助理(VDA)開始發達,變得更加聰明好用。未來用於企業的VDA市場預計將會持續成長,2018年的市場規模是13億美元,預測2025年將會成長至89億美元。

本報告針對企業用虛擬數位助理市場進行分析,並統整了市場現狀與過去10年的沿革、現在的主要活用領域/使用案例、主要市場促進及抑制要素、主要企業檔案與策略推展狀況、未來市場趨勢預測等資訊。

第1章 執行摘要

第2章 市場挑戰

  • 簡介
  • 市場概況
  • 市場促進要素
    • 減少費用、改善效率
    • 終端使用者方面有充分的期待:控制性、迅速處理、個人設定
  • 市場阻礙要素
    • 效率性
    • 害怕失敗
  • 市場趨勢
    • Web Scale、平台登場
    • 醫療用VDA失速
    • 商業用與企業用軟體的「巨人」登場

第3章 使用案例

  • 簡介
  • 顧客服務、行銷
    • 各種成熟化的徵兆
    • 通路戰爭:語音或數位?或是兩方?
    • Hybrid Live Solution
    • 「Agent Assist」登場
  • 電子商務、販售
  • 商業用途
    • 生產性與合作(collaboration)
    • 工作流程與專案管理
    • 聘用活動自動化
  • 醫療
    • 醫師用VDA

第4章 技術性挑戰

  • 基礎技術
  • 人工智慧 (AI) 的定義
  • 機器學習 (ML)
  • 深層學習 (DL)
  • 自然語言處理 (NLP)
    • 自然語言處理中機器學習、深層學習的重要性
    • 市場促進要素
      • 新型電腦、平台用的UI(用戶平台)技術
      • 大數據的缺點
    • 市場阻礙要素
      • 理解背景結構
      • 正確資料的必要性
    • 理解自然語言:Word Maps (單字地圖) 與語言模型
    • 生成自然語言
    • 自然語言處理舊有的途徑方式
      • 規則基礎
      • 統計模型

第5章 主要參與企業

  • 簡介
  • Alterra.ai
  • Amazon
  • Artificial Solutions
  • Cognicor
  • Creative Virtual
  • CX Company
  • Flamingo Ai
  • Google
  • Interactions
  • IPsoft
  • Kore.ai
  • LivePerson
  • Microsoft
  • Mya Systems
  • NoteSwift
  • Nuance
  • Oracle
  • Pypestream
  • SAP
  • SmartAction
  • Smartsheet
  • Synthetix
  • Woebot
  • 其他企業

第6章 市場預測

  • 預測方法
  • 企業用VDA軟體的市場收益額:總額
  • 企業用VDA軟體的市場收益額:使用案例別
  • 企業用VDA軟體的市場收益額:地區別
  • 企業用VDA軟體的市場收益額:相對於供應商各公司總收益的比率
  • 企業用VDA軟體的市場收益額:平台別市佔率
  • 結論與建議

第7章 企業一覽

第8章 首字母、簡稱一覽

第9章 目錄

第10章 圖表一覽

第11章 分析範圍、情報來源、分析方法、註記

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目錄
Product Code: VDA-19

More than 10 years ago, companies seeking efficiencies and automation for customer service began experimenting with applications that leveraged natural language processing (NLP). By early 2016, significant advances in combining NLP with other forms of artificial intelligence (AI), primarily machine learning (ML) and deep learning (DL), began to make enterprise virtual digital assistants (VDAs) more intelligent and useful. These advancements and other market factors have expanded the use cases for enterprise AI-driven VDAs beyond customer service & marketing. Tractica has identified three other use cases where significant direct software revenue will be generated for enterprise VDAs: e-commerce & sales, business applications, and healthcare.

Over the next 3 to 5 years, natural language (NL) AI will continue to improve and sentiment and emotion recognition AI will evolve. VDAs will become an increasingly significant interface enterprises can use for both externally-facing and internally-facing purposes. Externally-facing use cases include handling customer service, marketing, and commerce transactions, while internally-facing use cases include running enterprise application software, productivity and collaboration applications, and administration functions. Tractica expects strong growth in enterprise VDA software revenue, which is forecast to increase from $1.3 billion in 2018 to more than $8.9 billion in 2025.

This Tractica report examines the market and technology issues surrounding enterprise VDAs and presents profiles for key industry players throughout the ecosystem. It analyzes how enterprise VDAs will be used across multiple channels in four key use cases: customer service & marketing, e-commerce & sales, business applications, and healthcare VDAs. Tractica also presents global market forecasts for enterprise VDA software, segmented by region, solution type, and use case, covering the period from 2018 through 2025.

Key Questions Addressed:

  • What is the current state of the global enterprise virtual digital assistant (VDA) market and how will it develop over the next decade?
  • Which use cases will drive greater enterprise VDA adoption?
  • What are the most significant drivers of market growth and the major challenges faced by the industry?
  • Which companies are the key players in the enterprise VDA market?
  • What is the size of the global enterprise VDA software market opportunity?

Who Needs This Report?

  • Customer experience-focused enterprises
  • Customer experience solutions providers
  • Enterprise application software providers
  • Healthcare ecosystem players
  • Retail industry players
  • Customer service-focused enterprises
  • Customer service solutions providers
  • Brand marketers and advertisers

Table of Contents

1. Executive Summary

  • 1.1. Introduction
  • 1.2. Market Drivers
  • 1.3. Market Barriers
  • 1.4. Market Trends
  • 1.5. Market Forecast Highlights

2. Market Issues

  • 2.1. Introduction
  • 2.2. Market Overview
  • 2.3. Market Drivers
    • 2.3.1. Reducing Costs, Increasing Efficiencies
    • 2.3.2. Meeting End-User Expectations for Control, Speedy Resolution, and Personal Context
  • 2.4. Market Barriers
    • 2.4.1. Effectiveness
    • 2.4.2. Fear of Failure
  • 2.5. Market Trends
    • 2.5.1. The Emergence of Webscale Platforms
    • 2.5.2. Healthcare VDA Momentum Slows
    • 2.5.3. Business Applications and Emergence of Enterprise Software Giants

3. Use Cases

  • 3.1. Introduction
  • 3.2. Customer Service & Marketing
    • 3.2.1. Multiple Signs of Maturity
    • 3.2.2. Channel Wars: Voice, Digital, Both?
    • 3.2.3. Hybrid-Live Solutions
    • 3.2.4. Agent Assist Emerges
  • 3.3. E-Commerce & Sales
  • 3.4. Business Applications
    • 3.4.1. Productivity and Collaboration
    • 3.4.2. Workflow and Project Management
    • 3.4.3. Automated Job Recruiting
  • 3.5. Healthcare
    • 3.5.1. Physician VDAs

4. Technology Issues

  • 4.1. Underlying Technologies
  • 4.2. Definition of AI
  • 4.3. Machine Learning
  • 4.4. Deep Learning
  • 4.5. Natural Language Processing
    • 4.5.1. Importance of Machine and Deep Learning to Natural Language Processing
    • 4.5.2. Natural Language Processing Market Drivers
      • 4.5.2.1. User Interface Technology for New Computing Platforms
      • 4.5.2.2. The Failure of Big Data
    • 4.5.3. Natural Language Processing Market Barriers
      • 4.5.3.1. Understanding Context
      • 4.5.3.2. Need for Accurate Data
    • 4.5.4. Understanding Natural Language: Word Maps and Language Models
    • 4.5.5. Natural Language Generation
    • 4.5.6. Legacy Approaches to Natural Language Processing
      • 4.5.6.1. Rules-Based
      • 4.5.6.2. Statistical Models

5. Key Industry Players

  • 5.1. Introduction
  • 5.2. Alterra.ai
  • 5.3. Amazon
  • 5.4. Artificial Solutions
  • 5.5. Cognicor
  • 5.6. Creative Virtual
  • 5.7. CX Company
  • 5.8. Flamingo Ai
  • 5.9. Google
  • 5.10. Interactions
  • 5.11. IPsoft
  • 5.12. Kore.ai
  • 5.13. LivePerson
  • 5.14. Microsoft
  • 5.15. Mya Systems
  • 5.16. NoteSwift
  • 5.17. Nuance
  • 5.18. Oracle
  • 5.19. Pypestream
  • 5.20. SAP
  • 5.21. SmartAction
  • 5.22. Smartsheet
  • 5.23. Synthetix
  • 5.24. Woebot
  • 5.25. Other Industry Players

6. Market Forecasts

  • 6.1. Forecast Methodology
  • 6.2. Total Enterprise VDA Software Revenue
  • 6.3. Enterprise VDA Software Revenue by Use Case
  • 6.4. Enterprise VDA Software Revenue by Region
  • 6.5. Enterprise AI-Driven VDA Software Revenue as a Percentage of Point-to-Point Vendor Revenue
  • 6.6. Enterprise VDA Software Platform Revenue Share
  • 6.7. Conclusions and Recommendations

7. Company Directory

8. Acronym and Abbreviation List

9. Table of Contents

10. Table of Charts and Figures

11. Scope of Study, Sources and Methodology, Notes

Tables

  • Enterprise VDA Software Revenue by Region, World Markets: 2018-2025
  • Enterprise VDA Software Revenue by Solution Type, World Markets: 2018-2025
  • Enterprise VDA Software Revenue by Use Case, World Markets: 2018-2025
  • Enterprise VDA Software Revenue by Use Case and Solution Type, World Markets: 2018-2025
  • Enterprise VDA Software Revenue, Customer Service & Marketing Use Case, World Markets: 2018-2025
  • Enterprise VDA Software Revenue, E-Commerce & Sales Use Case, World Markets: 2018-2025
  • Enterprise VDA Software Revenue, Business Applications Use Case, World Markets: 2018-2025
  • Enterprise VDA Software Revenue, Healthcare Use Case, World Markets: 2018-2025
  • Enterprise VDA Software Revenue by Industry, World Markets: 2018-2025
  • Enterprise AI-Driven VDA Software Revenue as a Percentage of Point-to-Point Vendor Revenue by Use Case, World Markets: 2018-2025
  • Enterprise VDA Software Platform Revenue Share by Use Case, World Markets: 2018-2025
  • Other Industry Participants

Charts

  • Cloud Robotics Revenue and Shipments, World Markets: 2018-2025
  • Cloud Robotics Revenue by Type, World Markets: 2018- 2025
  • Cloud Robotics Revenue by Industry, World Markets: 2018-2025
  • Cloud Robotics Penetration Rate by Industry, World Markets: 2018-2025
  • Cloud Robotics Shipments by Industry, World Markets: 2018-2025
  • Industrial Cloud Robotics Revenue by Type, World Markets: 2018-2025
  • Enterprise Cloud Robotics Revenue by Type, World Markets: 2018-2025 (Includes Commercial UAVs and Commercial AVs)
  • Military Cloud Robotics Revenue by Type, World Markets: 2018-2025
  • Consumer Cloud Robotics Revenue by Type, World Markets: 2018-2025 (Includes Consumer UAVs and Consumer AVs)
  • UAV Cloud Robotics Revenue by Type, World Markets: 2018-2025
  • AV Cloud Robotics Revenue by Type, World Markets: 2018-2025

Figures

  • Microsoft 2018 State of Global Customer Service Report - Customer Experience
  • Microsoft 2018 State of Global Customer Service Report - Channel Preference
  • Vision for Business Application VDAs
  • ESNEFT Vision for Automating Referrals
  • AI Encompasses Numerous Technologies
  • Schematic Representation of a Deep Neural Network
  • Examples of Word Embeddings
  • Progression of Natural Language Generation
  • Visualizing Amazon Lex and Other Amazon Solutions for Contact Center
  • Google Dialogflow Developer Adoption