Global Artificial Intelligence Systems Spending Market Size, Status and Forecast 2019-2025

Artificial Intelligence System (AIS) was a distributed computing project undertaken by Intelligence Realm with the long-term goal of simulating the human brain in real time, complete with artificial consciousness and artificial general intelligence. They claimed to have found, in research, the “mechanisms of knowledge representation in the brain which is equivalent to finding artificial intelligence”, before moving into the developmental phase.
On the basis of technologies, deep learning segement takes the biggest share of the global artificial intelligence system spending market, accounting for almost 50% in 2017. But the natural language processing segement is expected to see a CAGR of 41.33% between 2017 and 2025.
In 2018, the global Artificial Intelligence Systems Spending market size was xx million US$ and it is expected to reach xx million US$ by the end of 2025, with a CAGR of xx% during 2019-2025.

This report focuses on the global Artificial Intelligence Systems Spending status, future forecast, growth opportunity, key market and key players. The study objectives are to present the Artificial Intelligence Systems Spending development in United States, Europe and China.

The key players covered in this study
Google
Microsoft
Facebook
IBM
Apple
Amazon
Intel
Infosys
Wipro
Salesforce
Ipsoft
Anki
Cognitive Scale
Ayasdi
Appier
OpenText
Nuance Communication
Digital Reasoning Systems
AIBrain
Palantir Technologies

Market analysis by product type
Deep Learning
Machine Learning
Natural Language Processing
Machine Vision
AGI
ASI

Market analysis by market
BFSI
Discrete & Process Manufacturing
Healthcare
Retail
Wholesale
Professional & Consumer
Service
Transportation
Others

Market analysis by Region
United States
Europe
China
Japan
Southeast Asia
India
Central & South America

The study objectives of this report are:
To analyze global Artificial Intelligence Systems Spending status, future forecast, growth opportunity, key market and key players.
To present the Artificial Intelligence Systems Spending development in United States, Europe and China.
To strategically profile the key players and comprehensively analyze their development plan and strategies.
To define, describe and forecast the market by product type, market and key regions.

In this study, the years considered to estimate the market size of Artificial Intelligence Systems Spending are as follows:
History Year: 2018-2019
Base Year: 2018
Estimated Year: 2019
Forecast Year 2019 to 2025
For the data information by region, company, type and application, 2018 is considered as the base year. Whenever data information was unavailable for the base year, the prior year has been considered.

Table of Contents

1 Report Overview
1.1 Study Scope
1.2 Key Market Segments
1.3 Players Covered
1.4 Market Analysis by Type

1.4.2 Deep Learning
1.4.3 Machine Learning
1.4.4 Natural Language Processing
1.4.5 Machine Vision
1.4.6 AGI
1.4.7 ASI
1.5 Market by Application
1.5.1 Global Artificial Intelligence Systems Spending Market Share by Application (2018-2025)
1.5.2 BFSI
1.5.3 Discrete & Process Manufacturing
1.5.4 Healthcare
1.5.5 Retail
1.5.6 Wholesale
1.5.7 Professional & Consumer
1.5.8 Service
1.5.9 Transportation
1.5.10 Others
1.6 Study Objectives
1.7 Years Considered

2 Executive Summary
2.1 Artificial Intelligence Systems Spending Market Size
2.2 Artificial Intelligence Systems Spending Growth Trends by Regions
2.2.1 Artificial Intelligence Systems Spending Market Size by Regions (2018-2025)
2.2.2 Artificial Intelligence Systems Spending Market Share by Regions (2018-2025)
2.3 Industry Trends
2.3.1 Market Top Trends
2.3.2 Market Use Cases

3 Key Players
3.1 Artificial Intelligence Systems Spending Revenue by Manufacturers (2018-2019)
3.2 Artificial Intelligence Systems Spending Key Players Head office and Area Served
3.3 Key Players Artificial Intelligence Systems Spending Product/Solution/Service
3.4 Date of Enter into Artificial Intelligence Systems Spending Market
3.5 Key Players Artificial Intelligence Systems Spending Funding/Investment Analysis
3.6 Global Key Players Artificial Intelligence Systems Spending Valuation & Market Capitalization
3.7 Mergers & Acquisitions, Expansion Plans

4 Breakdown Data by Type and Application
4.1 Global Artificial Intelligence Systems Spending Market Size by Type (2018-2025)
4.2 Global Artificial Intelligence Systems Spending Market Size by Application (2017-2025)

5 United States
5.1 United States Artificial Intelligence Systems Spending Market Size (2018-2025)
5.2 Artificial Intelligence Systems Spending Key Players in United States
5.3 United States Artificial Intelligence Systems Spending Market Size by Type
5.4 United States Artificial Intelligence Systems Spending Market Size by Application

6 Europe
6.1 Europe Artificial Intelligence Systems Spending Market Size (2018-2025)
6.2 Artificial Intelligence Systems Spending Key Players in Europe
6.3 Europe Artificial Intelligence Systems Spending Market Size by Type
6.4 Europe Artificial Intelligence Systems Spending Market Size by Application

7 China
7.1 China Artificial Intelligence Systems Spending Market Size (2018-2025)
7.2 Artificial Intelligence Systems Spending Key Players in China
7.3 China Artificial Intelligence Systems Spending Market Size by Type
7.4 China Artificial Intelligence Systems Spending Market Size by Application

8 Rest of World
8.1 Japan
8.1.1 Japan Artificial Intelligence Systems Spending Market Analysis
8.1.2 Key Players in
8.2 Southeast Asia
8.2.1 Southeast Asia Artificial Intelligence Systems Spending Market Analysis
8.2.2 Key Players in Southeast Asia
8.3 India
8.3.1 India Artificial Intelligence Systems Spending Market Analysis
8.3.2 Key Players in India

9 International Players Profiles
9.1 Google
9.1.1 Google Company Details
9.1.2 Company Description and Business Overview
9.1.3 Artificial Intelligence Systems Spending Introduction
9.1.4 Google Revenue in Artificial Intelligence Systems Spending Business (2018-2019)
9.1.5 Google Recent Development
9.2 Microsoft
9.2.1 Microsoft Company Details
9.2.2 Company Description and Business Overview
9.2.3 Artificial Intelligence Systems Spending Introduction
9.2.4 Microsoft Revenue in Artificial Intelligence Systems Spending Business (2018-2019)
9.2.5 Microsoft Recent Development
9.3 Facebook
9.3.1 Facebook Company Details
9.3.2 Company Description and Business Overview
9.3.3 Artificial Intelligence Systems Spending Introduction
9.3.4 Facebook Revenue in Artificial Intelligence Systems Spending Business (2018-2019)
9.3.5 Facebook Recent Development
9.4 IBM
9.4.1 IBM Company Details
9.4.2 Company Description and Business Overview
9.4.3 Artificial Intelligence Systems Spending Introduction
9.4.4 IBM Revenue in Artificial Intelligence Systems Spending Business (2018-2019)
9.4.5 IBM Recent Development
9.5 Apple
9.5.1 Apple Company Details
9.5.2 Company Description and Business Overview
9.5.3 Artificial Intelligence Systems Spending Introduction
9.5.4 Apple Revenue in Artificial Intelligence Systems Spending Business (2017-2018)
9.5.5 Apple Recent Development
9.6 Amazon
9.6.1 Amazon Company Details
9.6.2 Company Description and Business Overview
9.6.3 Artificial Intelligence Systems Spending Introduction
9.6.4 Amazon Revenue in Artificial Intelligence Systems Spending Business (2017-2018)
9.6.5 Amazon Recent Development
9.7 Intel
9.7.1 Intel Company Details
9.7.2 Company Description and Business Overview
9.7.3 Artificial Intelligence Systems Spending Introduction
9.7.4 Intel Revenue in Artificial Intelligence Systems Spending Business (2018-2019)
9.7.5 Intel Recent Development
9.8 Infosys
9.8.1 Infosys Company Details
9.8.2 Company Description and Business Overview
9.8.3 Artificial Intelligence Systems Spending Introduction
9.8.4 Infosys Revenue in Artificial Intelligence Systems Spending Business (2018-2019)
9.8.5 Infosys Recent Development
9.9 Wipro
9.9.1 Wipro Company Details
9.9.2 Company Description and Business Overview
9.9.3 Artificial Intelligence Systems Spending Introduction
9.9.4 Wipro Revenue in Artificial Intelligence Systems Spending Business (2018-2019)
9.9.5 Wipro Recent Development
9.10 Salesforce
9.10.1 Salesforce Company Details
9.10.2 Company Description and Business Overview
9.10.3 Artificial Intelligence Systems Spending Introduction
9.10.4 Salesforce Revenue in Artificial Intelligence Systems Spending Business (2018-2019)
9.10.5 Salesforce Recent Development
9.11 Ipsoft
9.12 Anki
9.13 Cognitive Scale
9.14 Ayasdi
9.15 Appier
9.16 OpenText
9.17 Nuance Communication
9.18 Digital Reasoning Systems
9.19 AIBrain
9.20 Palantir Technologies

10 Market Dynamics
10.1 Drivers
10.2 Opportunities
10.3 Challenges
10.4 Market Ecosystem
10.5 Market Value Chain Analysis

11 Key Findings in This Report

12 Appendix
12.1 Research Methodology
12.1.1 Methodology/Research Approach
12.1.1.1 Research Programs/Design
12.1.1.2 Market Size Estimation
12.1.1.3 Market Breakdown and Data Triangulation
12.1.2 Data Source
12.1.2.1 Secondary Sources
12.1.2.2 Primary Sources
12.2 Disclaimer
12.3 Author Details

1.1 Methodology/Research Approach

Our research methodology implements a mix of primary as well as secondary research. Our projects are initiated with secondary research, where we refer to a variety of sources including trade databases; government published documents, investor presentations, company annual reports, white papers, and paid databases.

1.1.1 Research Programs/Design

1.1.2 Market Size Estimation

Post the initial data mining stage, we gather our findings and analyse them, filtering out relevant insights. These are evaluated across teams and by our in-house SMEs. Along with data mining, we also initiate the primary research phase in which we interact with companies operating within the market space.

To evaluate the wholeness of the market, we interact (via email or telephone) with players who are responsible in adding value to the final product. Additionally, we interact with related industries to understand the external factors that can drive/hamper a market. We also make it a point to evaluate various economic parameters, which typically, have an impact on the purchasing choices of individuals as well as companies.

Post these stages, data are cross-verified with the companies that operate in a market space. It is important for us to study these companies in detail, to understand their existing performance and future strategies which will define the market in the coming years.

All this data is collected and evaluated by our analysts. Post the preparation of the report and data analysis, the findings are presented to our in-house experts who then eliminate discrepancies (if any).

  • The key players in the industry and markets have been identified through extensive secondary research.
  • The industry’s supply chain and market size, in terms of value, have been determined through primary and secondary research processes.
  • All percentage shares splits, and breakdowns have been determined using secondary sources and verified through primary sources.

1.2 Data Source

1.2.1 Secondary Sources

In the secondary research process, various secondary sources, such as D&B Hoovers, Bloomberg BusinessWeek, and Factiva, have been referred to, for identifying and collecting information for this study. Secondary sources included annual reports, press releases, and investor presentations of companies; whitepapers, certified publications, and articles by recognized authors; gold standard and silver standard websites; regulatory bodies; trade directories; and databases.

List of secondary sources include but are not limited to:

  • Academic Journals
  • Census.gov
  • Bloomberg
  • Company Annual Report
  • Hoovers

1.2.1.1 Preliminary data mining

Raw market data is obtained and collated on a broad front. Data is continuously filtered to ensure that only validated and authenticated sources are considered. In addition, data is also mined from a host of reports in our repository, as well as a number of reputed paid databases. For comprehensive understanding of the market, it is essential to understand the complete value chain and in order to facilitate this; we collect data from raw material suppliers, distributors as well as buyers.

Technical issues and trends are obtained from surveys, technical symposia and trade journals. Technical data is also gathered from intellectual property perspective, focusing on white space and freedom of movement. Industry dynamics with respect to drivers, restraints, pricing trends are also gathered. As a result, the material developed contains a wide range of original data that is then further cross-validated and authenticated with published sources.

1.2.2 Primary Sources

This is the final step in estimating and forecasting for our reports. Exhaustive primary interviews are conducted, on face to face as well as over the phone to validate our findings and assumptions used to obtain them. Interviewees are approached from leading companies across the value chain including suppliers, technology providers, domain experts and buyers so as to ensure a holistic and unbiased picture of the market. These interviews are conducted across the globe, with language barriers overcome with the aid of local staff and interpreters. Primary interviews not only help in data validation, but also provide critical insights into the market, current business scenario and future expectations and enhance the quality of our reports. All our estimates and forecast are verified through exhaustive primary research with Key Industry Participants (KIPs) which typically include:

  • Market leading companies
  • Raw material suppliers
  • Product distributors
  • Buyers

The key objectives of primary research are as follows:

  • To validate our data in terms of accuracy and acceptability
  • To gain an insight in to the current market and future expectations

1.2.3 Statistical model

Our market estimates and forecasts are derived through simulation models. A unique model is created customized for each study. Gathered information for market dynamics, technology landscape, application development and pricing trends is fed into the model and analyzed simultaneously. These factors are studied on a comparative basis, and their impact over the forecast period is quantified with the help of correlation, regression and time series analysis. Market forecasting is performed via a combination of economic tools, technological analysis, and industry experience and domain expertise.

Econometric models are generally used for short-term forecasting, while technological market models are used for long-term forecasting. These are based on an amalgamation of technology landscape, regulatory frameworks, economic outlook and business principles. A bottom-up approach to market estimation is preferred, with key regional markets analyzed as separate entities and integration of data to obtain global estimates. This is critical for a deep understanding of the industry as well as ensuring minimal errors. Some of the parameters considered for forecasting include:

  • Market drivers and restrains, along with their current and expected impact
  • Raw material scenario and supply v/s price trends
  • Regulatory scenario and expected developments
  • Current capacity and expected capacity additions up to 2026

We assign weights to these parameters and quantify their market impact using weighted average analysis, to derive an expected market growth rate.

1.2.4 Data Triangulation

After arriving at the overall market size using the market size estimation processes as explained above, the market was split into several segments and sub segments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and sub segment, the data triangulation and market breakdown procedures were employed, wherever applicable. The data was triangulated by studying several factors and trends from both the demand and supply sides.

1.2.5 Report Objectives

  • To define, describe, and forecast the market by segmentations, and region
  • To provide detailed information about the major factors (drivers, restraints, opportunities, and challenges) influencing the growth of the market
  • To analyze the sub-segments with respect to individual growth trends, prospects, and contributions to the total market
  • To analyze opportunities in the market for stakeholders and provide the competitive landscape of the market
  • To forecast the revenues of the market segments with respect to the major regions, such as North America, Europe, Asia Pacific (APAC), and RoW
  • To profile the key players and comprehensively analyze their recent developments and positioning in the market
  • To analyze competitive developments, such as mergers and acquisitions, new product developments, and Research and Development (R&D) activities, in the market
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Specs
Release date:September 26, 2019
Last updated:January 1, 1970
File Type:PDF
Category:Machinery & Equipment
Number Of Pages:100-150
Specs
Release date:September 26, 2019
Last updated:January 1, 1970
File Type:PDF
Category:Machinery & Equipment
Number Of Pages:100-150

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