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市場調查報告書

通訊部門·商業部門·各種用途·引進處的AI:IoT·資料分析·虛擬私人助手 (2016-2021年)

Artificial Intelligence in Communications, Applications, and Commerce: Internet of Things (IoT), Data Analytics, and Virtual Private Assistants 2016 - 2021

出版商 Mind Commerce 商品編碼 366046
出版日期 內容資訊 英文 314 Pages
商品交期: 最快1-2個工作天內
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通訊部門·商業部門·各種用途·引進處的AI:IoT·資料分析·虛擬私人助手 (2016-2021年) Artificial Intelligence in Communications, Applications, and Commerce: Internet of Things (IoT), Data Analytics, and Virtual Private Assistants 2016 - 2021
出版日期: 2016年08月09日 內容資訊: 英文 314 Pages
簡介

本報告套裝提供,通訊部門,商業部門,各種用途·引進處的人工智能 (AI)的市場機會調查,提供您主要的技術部門和概要,主要的適用領域,終端用戶產業·地區等各種部門的市場成長預測,彙整供應商生態系統,市場影響因素分析,IoT環境的重要性,巨量資料及分析的重要性,虛擬個人助手 (VPA)的技術及市場展望,主要的引進·利用案例,主要經營者,建議等資料。

人工智能 (AI)·機器學習 (ML)·認知式運算:通訊·各種適用處·內容·貿易各部門市場展望·預測 (2016-2021年)

第1章 簡介

第2章 摘要整理

第3章 概要

  • 關於AI
  • 市場定義
  • AI的發展的過程
  • AI的主要特徵
  • 機器學習
  • 認知式運算

第4章 全球AI市場

  • 全球市場的預測
  • AI市場預測:各技術
    • 資料探勘
    • 機器知覺
    • 模式認識
    • 智慧型決策支持系統
    • 自然語言處理
  • AI市場預測:主要的各適用領域
    • 行銷·商務上的決策
    • 職場的自動化
    • 預測的分析·預測
    • 詐騙檢測·分類
  • AI市場預測:各產業
    • 網際網路相關服務·產品
    • 金融服務
    • 醫療·生物資訊學
    • 製造·重工業
    • 通訊
  • 地區市場預測

第5章 AI產業分析

  • 供應商的生態系統
  • 主要的M&A
  • AI擴大的障礙與課題
  • AI的市場機會·成長推進因素
  • 新興領域:AI和數位安全

巨量資料及IoT的AI和ML:資料擷取·分析·決策的市場 (2016-2021年)

第1章 簡介

第2章 AI的技術與市場

  • AI和ML
  • AI的各種類型
  • 企業的AI·ML的利用
  • AI技術
    • ML
    • 自然語言處理
    • 影像處理
    • 語音辨識
    • 人工神經網
    • Deep學習
    • 其他
  • AI及ML的技術目標
  • AI方法
  • AI工具
  • AI的成果
  • 神經網和AI
  • Deep學習和AI
  • 預測分析和AI
  • IoT和巨量資料分析
  • IoT和AI
  • 消費者取向IoT·巨量資料分析·AI
  • IIoT·巨量資料分析·ML
  • AI和認知式運算
  • 超人類主義和AI

第3章 巨量資料·IoT的AI及ML

  • 「ML Everywhere」
  • ML API和巨量資料的發展
  • Ultra-Scale 分析和AI
  • 演算法的商務崛起
  • 雲端託管機器情報
  • ML的矛盾
  • 價值鏈分析

第4章 AI及ML的用途與服務

  • 情報性能監控
  • 基礎設施監測
  • 精密模式的生成
  • 建議引擎
  • 塊環鏈和加密技術
  • 企業應用
  • 情境察覺
  • 客戶回饋
  • 自動駕駛車
  • 詐騙偵測系統
  • 個人化醫療和醫療服務
  • 預測資料建模
  • 智慧機器
  • 網路安全 解決方案
  • 自規則代理商
  • 智慧型助手
  • 智慧型決策支援系統
  • 風險管理
  • 資料探勘&經營管理
  • 智慧型機器人工學
  • Fintech (金融科技)
  • 機器情報

第5章 由於AI支援的預測分析的市場:展望·預測

  • 全球市場的預測
    • 全球市場收益預測
    • 終端用戶產業上生產率的預測
    • 系統&硬體設備市場預測
    • 認知式運算市場預測
    • 商務內容創造
    • 經濟交易
    • Robo-Boss and Worker Supervision
    • 大樓安全系統
    • 商務分析軟體
    • 智慧機器與其引進
    • 自助服務虛擬發現·資料普及工具
  • 地區市場預測
    • 收益預測:各地區
    • 北美
    • 歐洲
    • 亞太地區
    • 中東·非洲
    • 南美

第6章 AI支援連網型設備的引進預測

  • 全球引進預測
  • 引進預測:各地區

第7章 企業分析

  • AI倡議·收購策略
  • 巨量資料·分析·IoT的企業與解決方案

第8章 總論·建議

虛擬個人助手 (VPA) 和智慧顧問:自主代理商和智慧機器技術·環境用戶體驗的市場

第1章 簡介

第2章 VPA技術的推進因素

第3章 VPA的成長推進因素

第4章 VPA的生態系統的影響

第5章 VPA的解決方案·利用案例

第6章 VPA市場預測

  • 全球市場規模
  • 市場規模:各地區
  • 市場規模:核心各技術
  • 市場規模:各終端用戶
  • 按市場規模:自規則代理商
  • 市場規模:生態系統各企業
  • 市場規模:不同商業模式
  • 企業的VPA的引進

第7章 附錄

  • AI
  • ML
目錄

Overview:

Artificial Intelligence is increasingly integrated in many areas including Internet search, entertainment, commerce applications, content optimization, and robotics. The long-term prospect for these technologies is that they will become embedded in many different other technologies and provide autonomous decision making on behalf of humans, both directly, and indirectly through many processes, products, and services. AI will anticipated to have an ever increasing role in ICT including both traditional telecommunications as well as many communications enabled applications and digital commerce.

Fast growing AI technologies for consumer facing industries include chat bots and Virtual Personal Assistants (VPA) and smart advisors. These technologies leverage autonomous agents to enable an ambient user experience for applications, services, and enhanced commerce. On the enterprise side, more than 50% of IT organizations are experimenting with AI in various forms such as Machine Learning, Deep Learning, Computer Vision, Image Recognition, Voice Recognition, Artificial Neural Networks, and more.

This research provide a comprehensive assessment of the market opportunities for AI in communications, applications, and commerce. The research also analyzes the role of AI in emerging Internet of Things (IoT) market segments as well as related unstructured data and analytics. The research includes an evaluation of the technologies and market outlook for VPA. Forecasts for each segment are provided for 2016 to 2021. All purchases of Mind Commerce reports includes time with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This needs to be used within three months of purchasing the report.

Target Audience:

  • Telecom service providers
  • Digital commerce companies
  • Artificial Intelligence companies
  • Big Data and analytics companies
  • Robotics and automation companies
  • Cloud and Internet of Things companies

Table of Contents

Artificial Intelligence, Machine Learning, and Cognitive Computing: Market and Outlook for Communications, Applications, Content and Commerce 2016 - 2021

1. Introduction

  • 1.1. Research Background
  • 1.2. Scope of the Research
  • 1.3. Organizations in Report

2. Executive Summary

3. Overview

  • 3.1. Introduction to Artificial Intelligence
  • 3.2. Market Definitions
    • 3.2.1. Client
    • 3.2.2. Intelligent Software Agent
    • 3.2.3. Problem Solving
    • 3.2.4. Algorithms
  • 3.3. History of Artificial Intelligence
  • 3.4. Key Characteristics of Artificial Intelligence
    • 3.4.1. Reasoning and Problem Solving
    • 3.4.2. Knowledge Representation and Knowledge Engineering
    • 3.4.3. Planning
    • 3.4.4. Natural Language Processing
    • 3.4.5. Machine Perception
    • 3.4.6. Motion and Manipulation
  • 3.4.7. Data Mining
  • 3.5. Machine Learning
    • 3.5.1. Deep Learning
  • 3.6. Cognitive Computing

4. The Global Artificial Intelligence Marketplace

  • 4.1. Global Markets for Artificial Intelligence 2016-2021
  • 4.2. Artificial Intelligence Markets by Technologies 2016-2021
    • 4.2.1. Markets for Data Mining Technology in Artificial Intelligence 2016-2021
    • 4.2.2. Markets for Machine Perception Technology in Artificial Intelligence 2016-2021
    • 4.2.3. Markets for Pattern Recognition Technology in Artificial Intelligence 2016-2021
    • 4.2.4. Markets for Intelligent Decision Support Systems Technology in AI 2016-2021
    • 4.2.5. Markets for Natural Language Processing Technology in AI 2016-2021
  • 4.3. Markets for AI by Key Application Areas 2016-2021
    • 4.3.1. AI Markets for Marketing and Business Decision Making 2016-2021
    • 4.3.2. AI Markets for Workplace Automation 2016-2021
    • 4.3.3. AI Markets for Predictive Analysis and Forecast 2016-2021
    • 4.3.4. AI Markets for Fraud Detection and Classification 2016-2021
  • 4.4. Market for AI by Key Industry Verticals 2016-2021
    • 4.4.1. AI Market for Internet related Services and Products 2016-2021
    • 4.4.2. AI Markets for Financial Services 2016-2021
    • 4.4.3. AI Market for Medical and Bio-Informatics 2016-2021
    • 4.4.4. AI Market for Manufacturing and Heavy Industry 2016-2021
    • 4.4.5. AI Market for Telecommunications 2016-2021
  • 4.5. Regional Markets for AI 2016-2021

5. AI Industry Analysis

  • 5.1. Vendor Ecosystem in AI
  • 5.2. Key Mergers and Acquisitions in AI
    • 5.2.1. Google acquires various Companies in AI
    • 5.2.2. IBM Acquisition of Companies Working in AI
    • 5.2.3. Facebook Acquisition of Companies working in AI
    • 5.2.4. Microsoft Acquisition of Companies Working in AI
    • 5.2.5. Apple Acquisition of Companies Working in AI
  • 5.3. Limitations and Challenges for Expansion of Artificial Intelligence
  • 5.4. Artificial Intelligence Opportunities and Drivers
  • 5.5. An Emerging Area: Artificial Intelligence and Digital Security

Figures

  • Figure 1: Global AI Market Value 2016-2021
  • Figure 2: Overall Artificial Intelligence Functionality
  • Figure 3: Artificial Intelligence Market 2016-2021
  • Figure 4: Artificial Intelligence Market by End user Segment 2016-2021
  • Figure 5: Artificial Intelligence by Sub-category 2016-2021
  • Figure 6: Artificial Intelligence Market by Technologies 2016-2021
  • Figure 7: Market for Data Mining Technology in Artificial Intelligence 2016-2021
  • Figure 8: Market for Machine Perception Technology in Artificial Intelligence 2016-2021
  • Figure 9: Market for Pattern Recognition Technology in Artificial Intelligence 2016-2021
  • Figure 10: Market for Intelligent Decision Support Systems Technology in AI 2016-2021
  • Figure 11: Market for Natural Language Processing Technology in AI 2016-2021
  • Figure 12: Artificial Intelligence Market by Applications 2016-2021
  • Figure 13: AI Market for Marketing and Business Decision Making 2016-2021
  • Figure 14: Artificial Intelligence Market for Workplace Automation 2016-2021
  • Figure 15: Artificial Intelligence Market for Predictive Analysis and Forecast 2016-2021
  • Figure 16: AI Market for Fraud Detection and Classification 2016-2021
  • Figure 17: Artificial Intelligence Markets by Industry: 2016-2021
  • Figure 18: AI Market for Internet Services and Products 2016-2021
  • Figure 19: Artificial Intelligence Market for Financial Services 2016-2021
  • Figure 20: Artificial Intelligence Market for Medical and Bio-informatics 2016-2021
  • Figure 21: AI Market for Manufacturing and Heavy Industry 2016-2021
  • Figure 22: Artificial Intelligence Market for Telecommunications 2016-2021
  • Figure 23: Regional Markets for Artificial Intelligence 2016-2021
  • Figure 24: Artificial Intelligence support of Security in the Internet of Things (IoT)

Tables

  • Table 1: Artificial Intelligence Market 2016-2021
  • Table 2: Artificial Intelligence Market by End user segment 2016-2021
  • Table 3: Artificial Intelligence by Sub-category 2016-2021
  • Table 4: Artificial Intelligence Market by Technologies 2016-2021
  • Table 5: Market for Data Mining Technology in Artificial Intelligence 2016-2021
  • Table 6: Market for Machine Perception Technology in Artificial Intelligence 2016-2021
  • Table 7: Market for Pattern Recognition Technology in Artificial Intelligence 2016-2021
  • Table 8: Market for Intelligent Decision Support Systems Technology in AI 2016-2021
  • Table 9: Market for Natural Language Processing Technology in Artificial Intelligence: 2016-2021
  • Table 10: Artificial Intelligence Market by Applications 2016-2021
  • Table 11: AI Market for Marketing and Business Decision Making 2016-2021
  • Table 12: Artificial Intelligence Market for Workplace Automation 2016-2021
  • Table 13: Artificial Intelligence Market for Predictive Analysis and Forecast 2016-2021
  • Table 14: Artificial Intelligence Market for Fraud Detection and Classification 2016-2021
  • Table 15: Artificial Intelligence Markets by Industry 2016-2021
  • Table 16: Artificial Intelligence Market for Internet Services and Products: 2016-2021
  • Table 17: Artificial Intelligence Market for Financial Services 2016-2021
  • Table 18: Artificial Intelligence Market for Medical and Bio-informatics 2016-2021
  • Table 19: Artificial Intelligence Market for Manufacturing and Heavy Industry 2016-2021
  • Table 20: Artificial Intelligence Market for Telecommunications 2016-2021
  • Table 21: Regional Markets for Artificial Intelligence 2016-2021
  • Table 22: Google Artificial Intelligence Acquisitions
  • Table 23: IBM Artificial Intelligence Acquisitions
  • Table 24: Facebook Artificial Intelligence Acquisitions
  • Table 25: Microsoft in Artificial Intelligence Acquisitions
  • Table 26: Apple Artificial Intelligence Acquisitions

Artificial Intelligence and Machine Learning in Big Data and IoT: The Market for Data Capture, Analytics, and Decision Making 2016-2021

1. Introduction

  • 1.1. Executive Summary
  • 1.2. Research Objectives
  • 1.3. Key Findings
  • 1.4. Target Audience
  • 1.5. Companies in Report

2. Artificial Intelligence Technology and Market

  • 2.1. Artificial Intelligence and Machine Learning
  • 2.2. AI Types
  • 2.3. Use of AI and ML in Enterprise
  • 2.4. Artificial Intelligence Technology
    • 2.4.1. Machine Learning
    • 2.4.2. Natural Language Processing
    • 2.4.3. Image Processing
    • 2.4.4. Voice Recognition
    • 2.4.5. Artificial Neural Network
    • 2.4.6. Deep Learning
    • 2.4.7. Others
  • 2.5. AI and ML Technology Goals
    • 2.5.1. Reasoning
    • 2.5.2. Knowledge Representation
    • 2.5.3. Planning
    • 2.5.4. Learning
    • 2.5.5. Communication
    • 2.5.6. Machine Perception
    • 2.5.7. Motion Manipulation
    • 2.5.8. Social Intelligence
    • 2.5.9. Creativity
    • 2.5.10. Artificial General Intelligence
    • 2.5.11. Computer Vision
    • 2.5.12. Robotics
  • 2.6. AI Approaches
    • 2.6.1. Cybernetics and Brian Simulation
    • 2.6.2. Symbolic
    • 2.6.3. Sub-Symbolic
    • 2.6.4. Statistical
    • 2.6.5. Integration
  • 2.7. AI Tools
    • 2.7.1. Search and Optimization
    • 2.7.2. Logic
    • 2.7.3. Probability
    • 2.7.4. Classifier and Statistics
    • 2.7.5. Neural Network
    • 2.7.6. Deep Feedforward Neural Network
    • 2.7.7. Deep Recurrent Neural Network
    • 2.7.8. Control Theory
    • 2.7.9. Language
  • 2.8. AI Outcomes
  • 2.9. Neural Networks and Artificial Intelligence
  • 2.10. Deep Learning and Artificial Intelligence
  • 2.11. Predictive Analytics and Artificial Intelligence
  • 2.12. Internet of Things and Big Data Analytics
  • 2.13. IoT and Artificial Intelligence
  • 2.14. Consumer IoT, Big Data Analytics, and Artificial Intelligence
  • 2.15. Industrial IoT, Big Data Analytics, and Machine Learning
  • 2.16. Artificial Intelligence and Cognitive Computing
  • 2.17. Transhumanism and Artificial Intelligence

3. Artificial Intelligence and Machine Learning in Big Data and IoT

  • 3.1. Machine Learning Everywhere
    • 3.1.1. Machine Learning as Open Source Technology
    • 3.1.2. Machine Learning and Intelligent Discovery in IoT
    • 3.1.3. Supervised and Unsupervised Machine Learning
    • 3.1.4. Machine Learning as Big Data Analysis Technique
    • 3.1.5. Machine Learning AI Robots
    • 3.1.6. Machine Learning and Data Democratization
  • 3.2. Machine Learning APIs and Big Data Development
    • 3.2.1. Phases of Machine Learning APIs
    • 3.2.2. Machine Learning API Challenges
    • 3.2.3. Top Machine Learning APIs
      • 3.2.3.1. IBM Watson API
      • 3.2.3.2. Microsoft Azure Machine Learning API
      • 3.2.3.3. Google Prediction API
      • 3.2.3.4. Amazon Machine Learning API
      • 3.2.3.5. BigML
      • 3.2.3.6. AT&T Speech API
      • 3.2.3.7. Wit.ai
      • 3.2.3.8. AlchemyAPI
      • 3.2.3.9. Diffbot
      • 3.2.3.10. PredictionIO
    • 3.2.4. Machine Learning API in General Application Environment
  • 3.3. Ultra-Scale Analytics and Artificial Intelligence
  • 3.4. Rise of Algorithmic Business
  • 3.5. Cloud Hosted Machine Intelligence
  • 3.6. Contradiction of Machine Learning
  • 3.7. Value Chain Analysis
    • 3.7.1. AI and Machine Learning Companies
    • 3.7.2. IoT Companies
    • 3.7.3. Big Data Analytics Providers
    • 3.7.4. Connectivity Solution and Infrastructure Providers
    • 3.7.5. Hardware and Equipment Manufacturers
    • 3.7.6. Developers and Data Scientists
    • 3.7.7. End Users

4. Artificial Intelligence and Machine Leaning Applications and Services

  • 4.1. Intelligence Performance Monitoring
  • 4.2. Infrastructure Monitoring
  • 4.3. Generating Accurate Models
  • 4.4. Recommendation Engine
  • 4.5. Block Chain and Crypto Technologies
  • 4.6. Enterprise Applications
  • 4.7. Contextual Awareness
  • 4.8. Customer Feedback
  • 4.9. Self-Driving Cars
  • 4.10. Fraud Detection Systems
  • 4.11. Personalized Medicine and Healthcare Service
  • 4.12. Predictive Data Modelling
  • 4.13. Smart Machines
  • 4.14. Cybersecurity Solutions
  • 4.15. Autonomous Agents
  • 4.16. Intelligent Assistant
  • 4.17. Intelligent Decision Support Systems
  • 4.18. Risk Management
  • 4.19. Data Mining and Management
  • 4.20. Intelligent Robotics
  • 4.21. Financial Technology
  • 4.22. Machine Intelligence

5. AI Powered Predictive Analytics Market Outlook and Forecasts

  • 5.1. Global Market Forecast
    • 5.1.1. Global Market Revenue 2016-2021
      • 5.1.1.1. Market by Type 2016-2021
      • 5.1.1.2. Market by Business Application 2016-2021
      • 5.1.1.3. Market by Core Technology 2016-2021
      • 5.1.1.4. Market by Technology Application 2016-2021
      • 5.1.1.5. Market by Segment 2016-2021
      • 5.1.1.6. Market by Industry Vertical 2016-2021
    • 5.1.2. Productivity in Industry Vertical 2016-2021
    • 5.1.3. System and Hardware Market 2016-2021
    • 5.1.4. Cognitive Computing Market 2016-2021
    • 5.1.5. Business Content Creation
    • 5.1.6. Economic Transactions
    • 5.1.7. Robo-Boss and Worker Supervision
    • 5.1.8. Building Security System
    • 5.1.9. Business Analytics Software
    • 5.1.10. Smart Machine and Employment
    • 5.1.11. Self-Service Visual Discovery and Data Penetration Tools
  • 5.2. Regional Market Forecasts
    • 5.2.1. Revenue by Region 2016-2021
    • 5.2.2. North America Market Forecasts 2016-2021
      • 5.2.2.1. Market by Types
      • 5.2.2.2. Market by Business Application
      • 5.2.2.3. Market by Core Technology
      • 5.2.2.4. Market by Technology Application
      • 5.2.2.5. Market by Segment
      • 5.2.2.6. Market by Industry Verticals
    • 5.2.3. Europe Market Forecasts 2016-2021
      • 5.2.3.1. Market by Types
      • 5.2.3.2. Market by Business Application
      • 5.2.3.3. Market by Core Technology
      • 5.2.3.4. Market by Technology Application
      • 5.2.3.5. Market by Segments
      • 5.2.3.6. Market by Industry Verticals
    • 5.2.4. APAC Market Forecasts 2016-2021
      • 5.2.4.1. Market by Type
      • 5.2.4.2. Market by Business Application
      • 5.2.4.3. Market by Core Technology
      • 5.2.4.4. Market by Technology Application
      • 5.2.4.5. Market by Segments
      • 5.2.4.6. Market by Industry Vertical
    • 5.2.5. ME&A Market Forecasts 2016-2021
      • 5.2.5.1. Market by Type
      • 5.2.5.2. Market by Business Application
      • 5.2.5.3. Market by Core Technology
      • 5.2.5.4. Market by Technology Application
      • 5.2.5.5. Market by Segment
      • 5.2.5.6. Market by Industry Vertical
    • 5.2.6. Latin America Market Forecasts 2016-2021
      • 5.2.6.1. Market by Type
      • 5.2.6.2. Market by Business Application
      • 5.2.6.3. Market by Core Technology
      • 5.2.6.4. Market by Technology Application
      • 5.2.6.5. Market by Segment
      • 5.2.6.6. Market by Industry Vertical

6. AI Supported Connected Device Deployment Forecasts

  • 6.1. Global Deployment Forecast 2016-2021
    • 6.1.1. Deployment by Device and Platform
    • 6.1.2. Deployment by Application Sector
    • 6.1.3. Deployment by Core Technology
    • 6.1.4. Deployment by Technology Applications
    • 6.1.5. Deployment by Segments
    • 6.1.6. Deployment by Industry Verticals
  • 6.2. Regional Deployment Forecasts 2016-2021
    • 6.2.1. Deployment by Region
    • 6.2.2. North America Deployment Forecasts 2016-2021
      • 6.2.2.1. Deployment by Device and Platform
      • 6.2.2.2. Deployment by Application Sector
      • 6.2.2.3. Deployment by Core Technology
      • 6.2.2.4. Deployment by Technology Application
      • 6.2.2.5. Deployment by Segment
      • 6.2.2.6. Deployment by Industry Verticals
    • 6.2.3. Europe Deployment Forecasts 2016-2021
      • 6.2.3.1. Deployment by Device and Platform
      • 6.2.3.2. Deployment by Application Sector
      • 6.2.3.3. Deployment by Core Technology
      • 6.2.3.4. Deployment by Technology Applications
      • 6.2.3.5. Deployment by Segment
      • 6.2.3.6. Deployment by Industry Vertical
    • 6.2.4. APAC Deployment Forecasts 2016-2021
      • 6.2.4.1. Deployment by Device and Platform
      • 6.2.4.2. Deployment by Application Sector
      • 6.2.4.3. Deployment by Core Technology
      • 6.2.4.4. Deployment by Technology Application
      • 6.2.4.5. Deployment by Segment
      • 6.2.4.6. Deployment by Industry Vertical
    • 6.2.5. ME&A Deployment Forecasts 2016-2021
      • 6.2.5.1. Deployment by Device and Platform
      • 6.2.5.2. Deployment by Application Sector
      • 6.2.5.3. Deployment by Core Technology
      • 6.2.5.4. Deployment by Technology Application
      • 6.2.5.5. Deployment by Segment
      • 6.2.5.6. Deployment by Industry Vertical
    • 6.2.6. Latin America Deployment Forecasts 2016-2021
      • 6.2.6.1. Deployment by Device and Platform
      • 6.2.6.2. Deployment by Application Sector
      • 6.2.6.3. Deployment by Core Technology
      • 6.2.6.4. Deployment by Technology Application
      • 6.2.6.5. Deployment by Segment
      • 6.2.6.6. Deployment by Industry Vertical

7. Company Analysis

  • 7.1. AI Initiatives and Acquisition Strategies
    • 7.1.1. Google
    • 7.1.2. Twitter
    • 7.1.3. Microsoft
    • 7.1.4. IBM
    • 7.1.5. Apple
    • 7.1.6. Facebook
    • 7.1.7. Amazon
    • 7.1.8. Skype
    • 7.1.9. Salesforce
    • 7.1.10. Intel
    • 7.1.11. Yahoo
    • 7.1.12. AOL
    • 7.1.13. NVIDIA
    • 7.1.14. x.ai
    • 7.1.15. Tesla
    • 7.1.16. Baidu
    • 7.1.17. H2O.ai
    • 7.1.18. SparkCognition
    • 7.1.19. OpenAI
    • 7.1.20. Inbenta
  • 7.2. Big Data, Analytics, and IoT Companies and Solutions
    • 7.2.1. Tachyus
    • 7.2.2. Sentrian
    • 7.2.3. Maana
    • 7.2.4. Veros Systems
    • 7.2.5. Neura
    • 7.2.6. Augury Systems
    • 7.2.7. Glassbeam
    • 7.2.8. Comfy
    • 7.2.9. mnubo
    • 7.2.10. C-B4
    • 7.2.11. PointGrab
    • 7.2.12. Tellmeplus
    • 7.2.13. Moov
    • 7.2.14. Sentenai
    • 7.2.15. Imagimob
    • 7.2.16. FocusMotion
    • 7.2.17. MoBagel

8. Conclusions and Recommendations

  • 8.1. Recommendations for Data Analytics Providers
  • 8.2. Recommendations for AI and Machine Learning Companies
  • 8.3. Recommendations for IoT Companies and Equipment Manufacturers
  • 8.4. Recommendations for Service Providers
  • 8.5. Recommendations for Enterprise

Figures

  • Figure 1: Artificial Intelligence Technology
  • Figure 2: Sentiment Analysis with Deep Machine Learning
  • Figure 3: Artificial Intelligence (AI) and Predictive Layer System
  • Figure 4: Industrial IoT Landscape and Machine Learning as a Service (MLaaS)
  • Figure 5: Machine Learning Use Case Scenario
  • Figure 6: Artificial Intelligence and Machine Learning Landscape and Impact
  • Figure 7: Global AI Powered Predictive Analytics Market 2016-2021
  • Figure 8: AI Powered Analytics Driven Productivity Gains in Industry Verticals 2016-2021
  • Figure 9: AI Driven System and Hardware Market 2016-2021
  • Figure 10: AI Driven Cognitive Computing Market 2016-2021
  • Figure 11: Business Content Created by AI Powered Smart Machines 2018-2021
  • Figure 12: Worker Supervision by AI Powered Robo-Boss 2018-2021
  • Figure 13: Building Security System by AI Capabilities 2018-2021
  • Figure 14: Business Analytics Software by AI Powered Predictive Analytics 2018-2021
  • Figure 15: AI powered Smart Machines vs. Humans 2018-2021
  • Figure 16: Global AI Connected Devices Deployment 2016-2021

Tables

  • Table 1: Global AI Powered Predictive Analytics Market by Type 2016-2021
  • Table 2: Global AI Powered Predictive Analytics Market by Business Application 2016-2021
  • Table 3: Global AI Powered Predictive Analytics Market by Core Technology 2016-2021
  • Table 4: Global AI Powered Predictive Analytics Market by Technology Applications 2016-2021
  • Table 5: Global AI Powered Predictive Analytics Market by Segment 2016-2021
  • Table 6: Global AI Powered Predictive Analytics Market by Industry Verticals 2016-2021
  • Table 7: Global Economic Transaction by AI Powered Autonomous Software Agents 2018-2021
  • Table 8: AI Self Service Visual Discovery and Data Penetration Tools 2018-2021
  • Table 9: AI Powered Predictive Analytics Market by Region 2016-2021
  • Table 10: North America AI Powered Predictive Analytics Market by Type 2016-2021
  • Table 11: North America AI Powered Predictive Analytics Market by Business Application 2016-2021
  • Table 12: North America AI Powered Predictive Analytics Market by Core Technology 2016-2021
  • Table 13: North America AI Powered Predictive Analytics Market by Technology App 2016-2021
  • Table 14: North America AI Powered Smart & Predictive Analytics Market by Segment 2016-2021
  • Table 15: North America AI Powered Predictive Analytics Market by Industry Vertical 2016-2021
  • Table 16: Europe AI Powered Predictive Analytics Market by Type 2016-2021
  • Table 17: Europe AI Powered Predictive Analytics Market by Business Application 2016-2021
  • Table 18: Europe AI Powered Predictive Analytics Market by Core Technology 2016-2021
  • Table 19: Europe AI Powered Predictive Analytics Market by Technology Application 2016-2021
  • Table 20: Europe AI Powered Predictive Analytics Market by Segment 2016-2021
  • Table 21: Europe AI Powered Predictive Analytics Market by Industry Vertical 2016-2021
  • Table 22: APAC AI Powered Predictive Analytics Market by Type 2016-2021
  • Table 23: APAC AI Powered Predictive Analytics Market by Business Application 2016-2021
  • Table 24: APAC AI Powered Predictive Analytics Market by Core Technology 2016-2021
  • Table 25: APAC AI Powered Predictive Analytics Market by Technology Applications 2016-2021
  • Table 26: APAC AI Powered Predictive Analytics Market by Segment 2016-2021
  • Table 27: APAC AI Powered Predictive Analytics Market by Industry Vertical 2016-2021
  • Table 28: ME&A AI Powered Predictive Analytics Market by Type 2016-2021
  • Table 29: ME&A AI Powered Predictive Analytics Market by Business Application 2016-2021
  • Table 30: ME&A AI Powered Predictive Analytics Market by Core Technology 2016-2021
  • Table 31: ME&A AI Powered Predictive Analytics Market by Technology Application 2016-2021
  • Table 32: ME&A AI Powered Predictive Analytics Market by Segment 2016-2021
  • Table 33: ME&A AI Powered Predictive Analytics Market by Industry Vertical 2016-2021
  • Table 34: Latin America AI Powered Predictive Analytics Market by Type 2016-2021
  • Table 35: Latin America AI Powered Predictive Analytics Market by Business Application 2016-2021
  • Table 36: Latin America AI Powered Predictive Analytics Market by Core Technology 2016-2021
  • Table 37: Latin America AI Powered Predictive Analytics Market by Technology App 2016-2021
  • Table 38: Latin America AI Powered Predictive Analytics Market by Segment 2016-2021
  • Table 39: Latin America AI Powered Predictive Analytics Market by Industry Vertical 2016-2021
  • Table 40: Global Device Deployment by Device Type and Platform 2016-2021
  • Table 41: Global Device Deployment by Application Sector 2016-2021
  • Table 42: Global Device Deployment by Core Technology 2016-2021
  • Table 43: Global Device Deployment by Technology Application 2016-2021
  • Table 44: Global Device Deployment by Segment 2016-2021
  • Table 45: Global Device Deployment by Industry Vertical 2016-2021
  • Table 46: AI Connected Device Deployment by Region 2016-2021
  • Table 47: North America Device Deployment by Device Type and Platform 2016-2021
  • Table 48: North America Device Deployment by Application Sector 2016-2021
  • Table 49: North America Device Deployment by Core Technology 2016-2021
  • Table 50: North America Device Deployment by Technology Application 2016-2021
  • Table 51: North America Device Deployment by Segment 2016-2021
  • Table 52: North America Device Deployment by Industry Vertical 2016-2021
  • Table 53: Europe Device Deployment by Device Type and Platform 2016-2021
  • Table 54: Europe AI Device Deployment by Application Sector 2016-2021
  • Table 55: Europe Device Deployment by Core Technology 2016-2021
  • Table 56: Europe Device Deployment by Technology Application 2016-2021
  • Table 57: Europe Device Deployment by Segment 2016-2021
  • Table 58: Europe Device Deployment by Industry Vertical 2016-2021
  • Table 59: APAC AI Device Deployment by Device Type and Platform 2016-2021
  • Table 60: APAC Device Deployment by Application Sector 2016-2021
  • Table 61: APAC Device Deployment by Core Technology 2016-2021
  • Table 62: APAC Device Deployment by Technology Application 2016-2021
  • Table 63: APAC Device Deployment by Segment 2016-2021
  • Table 64: APAC Device Deployment by Industry Vertical 2016-2021
  • Table 65: ME&A Device Deployment by Device Type and Platform 2016-2021
  • Table 66: ME&A Device Deployment by Application Sector 2016-2021
  • Table 67: ME&A Device Deployment by Core Technology 2016-2021
  • Table 68: ME&A Device Deployment by Technology Application 2016-2021
  • Table 69: ME&A Device Deployment by Segment 2016-2021
  • Table 70: ME&A Device Deployment by Industry Vertical 2016-2021
  • Table 71: Latin America Device Deployment by Device Type and Platform 2016-2021
  • Table 72: Latin America Devices Deployment by Application Sector 2016-2021
  • Table 73: Latin America Device Deployment by Application Sector 2016-2021
  • Table 74: Latin America Device Deployment by Technology Application 2016-2021
  • Table 75: Latin America Device Deployment by Segment 2016-2021
  • Table 76: Latin America Device Deployment by Industry Vertical 2016-2021

Virtual Personal Assistants (VPA) and Smart Advisors: Autonomous Agent and Smart Machine Technology and the Market for Ambient User Experience

1.0. INTRODUCTION

  • 1.1. TECHNOLOGY TREND AND VIRTUAL PRIVATE ASSISTANTS (VPA)
  • 1.2. ENTERPRISE INTELLIGENT ASSISTANTS AND VPA
  • 1.3. WHAT IS VPA?
  • 1.4. BENEFITS OF VPA
  • 1.5. POTENTIAL RISKS

2.0. VPA TECHNOLOGY DRIVERS

  • 2.1. DIGITAL MESH AND AMBIENT USER EXPERIENCE
  • 2.2. SMART MACHINE IMPLEMENTATIONS
  • 2.3. AUTONOMOUS AGENTS AND ADVISORS
  • 2.4. AUTONOMOUS ROBOTS
  • 2.5. SOCIAL ROBOTS
  • 2.6. NATURAL LANGUAGE PROCESSING
  • 2.7. SPEECH RECOGNITION
  • 2.8. INFORMATION OF EVERYTHING
  • 2.9. MACHINE READING COMPREHENSION (MRC)

3.0. VPA GROWTH DRIVERS

  • 3.1. FRIENDLY ASSISTANCE
  • 3.2. QUALITY LIVES
  • 3.3. CUSTOMER MANAGED RELATIONSHIP (CMR)
  • 3.4. PERSONAL CLOUD
  • 3.5. CONTEXTUAL ACTIONS
  • 3.6. API AND MOBILE APPS

4.0. VPA ECOSYSTEM IMPACT

  • 4.1. ECOSYSTEM ANALYSIS
  • 4.2. MASTER CONTROLLER
  • 4.3. CORPORATE ADVERTISING
  • 4.4. CUSTOMER CARE
  • 4.5. ONLINE ADVERTISING
  • 4.6. ONLINE PAYMENT
  • 4.7. AUGMENTED HUMAN REALITY
  • 4.8. BUSINESS MODEL
  • 4.9. END USERS
  • 4.10. INTELLIGENT AGENTS
  • 4.11. AUDIENCES

5.0. VPA SOLUTIONS AND USE CASES

  • 5.1. GOOGLE NOW
  • 5.2. APPLE SIRI
  • 5.3. MICROSOFT CORTANA
  • 5.4. FACEBOOK M
  • 5.5. MYWAVE
  • 5.6. NUANCE
  • 5.7. MOTION.AI
  • 5.8. INDIGO
  • 5.9. DRAGON GO
  • 5.10. VOKUL
  • 5.11. ROBIN
  • 5.12. 24ME
  • 5.13. QUIP
  • 5.14. WUNDERLIST
  • 5.15. SPEAKTOIT
  • 5.16. AMAZON ECHO
  • 5.17. BRAINA
  • 5.18. S VOICE
  • 5.19. ASSISTANT.AI
  • 5.20. VOICE MATE
  • 5.21. BLACKBERRY ASSISTANT
  • 5.22. SILVIA
  • 5.23. HTC HIDI
  • 5.24. IBM WATSON
  • 5.25. CUBIC
  • 5.26. HOUND
  • 5.27. JIBO
  • 5.28. MALUUBA
  • 5.29. MYCROFT
  • 5.30. SIRIUS
  • 5.31. UBI
  • 5.32. VLINGO
  • 5.33. SKYVI
  • 5.34. JEANNIE
  • 5.35. EASILYDO
  • 5.36. VOICE ASSISTANT
  • 5.37. EVI
  • 5.38. OPERATOR
  • 5.39. CHARLIE
  • 5.40. WONDER
  • 5.41. MAGIC
  • 5.42. ALFRED
  • 5.43. RESERVE
  • 5.44. PENNY
  • 5.45. CLARA
  • 5.46. POSTMATES
  • 5.47. JARVIS
  • 5.48. AWESOME
  • 5.49. CLOE
  • 5.50. X.AI
  • 5.51. RILEY
  • 5.52. JULIE DESK
  • 5.53. ZIRTUAL
  • 5.54. DENARRI
  • 5.55. AIVC
  • 5.56. EVA
  • 5.57. ANDY
  • 5.58. HELLO ALFRED
  • 5.59. BUDDY
  • 5.60. GOBUTLER

6.0. VPA MARKET PROJECTIONS THROUGH 2025

  • 6.1. GLOBAL MARKET VALUE
  • 6.2. MARKET VALUE BY REGION
  • 6.3. MARKET VALUE BY CORE TECHNOLOGY
  • 6.4. MARKET VALUE BY END USER
  • 6.5. MARKET VALUE BY AUTONOMOUS AGENTS
  • 6.6. MARKET VALUE BY ECOSYSTEM PLAYERS
  • 6.7. MARKET VALUE BY BUSINESS MODEL
  • 6.8. ENTERPRISE VPA ADOPTION

7.0. APPENDIX ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

  • 7.1. ARTIFICIAL INTELLIGENCE
  • 7.2. MACHINE LEARNING

Figures

  • Figure 1: VPA Ecosystem
  • Figure 2: Google Now Card
  • Figure 3: Apple's Siri Voice Control
  • Figure 4: Microsoft Cortana Usage Diagram
  • Figure 5: Facebook M Interface and Tests

Tables

  • Table 1: VPA Market Value by Geographic Region 2025
  • Table 2: VPA Market Value by Core Technology 2025
  • Table 3: VPA Market Value by Types of End User 2025
  • Table 4: VPA Market Value by Types of Autonomous Agents 2025
  • Table 5: VPA Market Value by Ecosystem Participants 2025
  • Table 6: VPA Market Value by Business Mo
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