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市場調查報告書

工業AI市場調查:2020-2025年

Industrial AI Market Report 2020-2025

出版商 IoT Analytics GmbH 商品編碼 918080
出版日期 內容資訊 英文 146 Pages
商品交期: 最快1-2個工作天內
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工業AI市場調查:2020-2025年 Industrial AI Market Report 2020-2025
出版日期: 2019年12月09日內容資訊: 英文 146 Pages
簡介

本報告含括工業AI市場,提供劇增的物聯網 (IoT)的利用案例相關詳細分析,工業AI是什麼,工業AI供應商的實例和工業AI的案例研究,工業AI市場概況,企業從工業AI投資獲得的好處,市場成長的推動要素、趨勢、課題等相關彙整。

第1章 人工智能 (AI)的簡介

第2章 工業AI技術

第3章 工業AI的利用案例

第4章 市場規模、展望

第5章 競爭情形

第6章 AI實施的展望

第7章 趨勢、課題

目錄

This Industrial AI market report details the fastest growing use case for the Internet of Things.

FIND OUT:

  • The Industrial AI market split by AI hardware, AI software, and AI services
  • How the market is developing across 26 industries (ISIC classification)
  • The regional market split for 2018 to 2025 with country level breakdowns (plus top 5 country deep-dives)
  • How Industrial AI solutions are being implemented today across 12 detailed use case categories and 33 sub use cases
  • How the 12 leading Industrial AI companies compare and how they fit into the landscape of 300+ Industrial AI technology vendors
  • The end user perspective on Industrial AI adoption, return-on-investment, current & future budgets available
  • The characteristics & benefits of Industrial AI at the Edge with real world examples
  • What the 9 Industrial AI best practices are related to first steps, data, and analytics
  • What the 11 biggest trends for Industrial AI are
  • What the 9 biggest challenges are

QUESTIONS ANSWERED IN THIS REPORT:

  • What is Industrial AI? ( i.e., a Industrial AI definition)
  • What are the examples of Industrial AI vendors and Industrial AI case studies?
  • How does the Industrial AI market look like (i.e., overview by regions, offering type, industries)?
  • Which benefits are companies seeing from their Industrial AI investments?
  • What are the market drivers, trends & challenges in Industrial AI space?

AT A GLANCE

Industrial AI is emerging as new hot topic for the Internet of Things (IoT) . By the end of 2019, the Global Industrial AI market is estimated at just under $15B and expected to grow at a CAGR of 31% to become a $72.5B market by 2025.

This report examines the 3 main types of Machine Learning techniques employed in Industrial AI solutions.

The research included taking a deep-dive in AI hardware examining 11 key technologies.

12 main industrial AI use case categories and 33 sub use cases were identified.

The report breaks down the Global Industrial AI market by offering type across 3 technology areas: AI hardware, AI software, AI services.

A comprehensive set of Industrial AI use cases were analysed for this research and the report includes a break down of the market by use case.

The report breaks down the Global Industrial AI market by region & offering type.

The report examines current and expected spending for Industrial AI solutions in greater detail across 26 industry segments and breaks down the Global Industrial AI market by region & industry.

The report breaks down the Global Industrial AI market by vendor.

Furthermore, the report describes the top 11 industry trends and 9 main challenges affecting Industrial AI. The report also comes with a detailed Database of 300+ Industrial AI vendors and an additional Database of 110+ detailed Industrial AI projects.

DEFINITION OF INDUSTRIAL AI

Industrial AI = “AI relating to the physical operations and systems of an industrial enterprise”. AI-driven systems can automate and reinvent fundamental industrial processes e.g., from product development and manufacturing to supply-chain and field operations.

For this report the following slide presents the definition of Industrial AI used in the analysis.

SELECTED COMPANIES FROM THE INDUSTRIAL AI REPORT

Accenture, Alibaba, Amazon AWS, AMD, C3, Cognizant, Google, IBM, Intel, Microsoft, Nvidia, SAP, SAS, Sparkcognition, TCS, Texas Instruments, Uptake, Zenodys +300 more.

Table of Contents

  • 1. Introduction to Artificial Intelligence
  • 2. Industrial AI Technology
  • 3. Industrial AI use cases
  • 4. Market Sizing & outlook
  • 5. Competitive landscape
  • 6. AI implementaion perspective
  • 7. Trends & Challenges
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