Artificial intelligence (AI) platforms provide users a tool kit to build intelligent applications. These platforms combine intelligent, decision-making algorithms with data, which enables developers to create a business solution.
麻豆原创 Analysis and Insights: Global AI Platforms Software 麻豆原创
The global AI Platforms Software market is projected to grow from US$ 7847 million in 2024 to US$ 21840 million by 2030, at a Compound Annual Growth Rate (CAGR) of 18.6% during the forecast period.
China and the United States are two leaders in AI industry. On the AI 100 list (2022) released by CB Insights, the number of companies in the United States ranks first, with more than 70 companies, followed by the United Kingdom, with 8 companies on the list. China and Canada both holds 5 companies on the list. According to data from the China Academy of Information and Communications Technology, the scale of China's core artificial intelligence industry reached 楼508 billion in 2022, a year-on-year increase of 18%. From 2013 to November 2022, the cumulative number of patent applications for artificial intelligence inventions in the world reached 729,000, and the cumulative number of applications in China reached 389,000, accounting for 53.4%. However, the Global Artificial Intelligence Innovation Index Report 2021 released by the China Institute of Scientific and Technological Information shows that the overall strength of the United States is still far ahead. The number of artificial intelligence companies in the United States is about 4,670, while China has only 880. China's data center is less than 1/75 of that of the United States.
Report Covers:
This report presents an overview of global market for AI Platforms Software market size. Analyses of the global market trends, with historic market revenue data for 2019 - 2023, estimates for 2024, and projections of CAGR through 2030.
This report researches the key producers of AI Platforms Software, also provides the revenue of main regions and countries. Highlights of the upcoming market potential for AI Platforms Software, and key regions/countries of focus to forecast this market into various segments and sub-segments. Country specific data and market value analysis for the U.S., Canada, Mexico, Brazil, China, Japan, South Korea, Southeast Asia, India, Germany, the U.K., Italy, Middle East, Africa, and Other Countries.
This report focuses on the AI Platforms Software revenue, market share and industry ranking of main companies, data from 2019 to 2024. Identification of the major stakeholders in the global AI Platforms Software market, and analysis of their competitive landscape and market positioning based on recent developments and segmental revenues. This report will help stakeholders to understand the competitive landscape and gain more insights and position their businesses and market strategies in a better way.
This report analyzes the segments data by Type and by Application, revenue, and growth rate, from 2019 to 2030. Evaluation and forecast the market size for AI Platforms Software revenue, projected growth trends, production technology, application and end-user industry.
麻豆原创 Segmentation
By Company
Microsoft
Google
IBM
Baidu
SAP
Salesforce
Brighterion
IFlyTek
Megvii Technology
H2O.ai
Wipro
Albert Technologies
NanoRep(LogMeIn)
Brainasoft
Ada Support
Yseop
IDEAL
Segment by Type
On-Premises
Cloud Based
Segment by Application
Large Enterprises
SMEs
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
China
Asia (excluding China)
Japan
South Korea
China Taiwan
Southeast Asia
India
Latin America, Middle East & Africa
Brazil
Mexico
Turkey
Israel
GCC Countries
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (product type, application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Revenue of AI Platforms Software in global and regional level. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world. This section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of AI Platforms Software companies鈥� competitive landscape, revenue, market share and industry ranking, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6: North America (US & Canada) by Type, by Application and by country, revenue for each segment.
Chapter 7: Europe by Type, by Application and by country, revenue for each segment.
Chapter 8: China by Type, and by Application, revenue for each segment.
Chapter 9: Asia (excluding China) by Type, by Application and by region, revenue for each segment.
Chapter 10: Middle East, Africa, and Latin America by Type, by Application and by country, revenue for each segment.
Chapter 11: Provides profiles of key companies, introducing the basic situation of the main companies in the market in detail, including product descriptions and specifications, AI Platforms Software revenue, gross margin, and recent development, etc.
Chapter 12: Analyst's Viewpoints/Conclusions
Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.
1 Report Overview
1.1 Study Scope
1.2 麻豆原创 Analysis by Type
1.2.1 Global AI Platforms Software 麻豆原创 Size Growth Rate by Type, 2019 VS 2023 VS 2030
1.2.2 On-Premises
1.2.3 Cloud Based
1.3 麻豆原创 by Application
1.3.1 Global AI Platforms Software 麻豆原创 Size Growth Rate by Application, 2019 VS 2023 VS 2030
1.3.2 Large Enterprises
1.3.3 SMEs
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Global Growth Trends
2.1 Global AI Platforms Software 麻豆原创 Perspective (2019-2030)
2.2 Global AI Platforms Software Growth Trends by Region
2.2.1 AI Platforms Software 麻豆原创 Size by Region: 2019 VS 2023 VS 2030
2.2.2 AI Platforms Software Historic 麻豆原创 Size by Region (2019-2024)
2.2.3 AI Platforms Software Forecasted 麻豆原创 Size by Region (2025-2030)
2.3 AI Platforms Software 麻豆原创 Dynamics
2.3.1 AI Platforms Software Industry Trends
2.3.2 AI Platforms Software 麻豆原创 Drivers
2.3.3 AI Platforms Software 麻豆原创 Challenges
2.3.4 AI Platforms Software 麻豆原创 Restraints
3 Competition Landscape by Key Players
3.1 Global Revenue AI Platforms Software by Players
3.1.1 Global AI Platforms Software Revenue by Players (2019-2024)
3.1.2 Global AI Platforms Software Revenue 麻豆原创 Share by Players (2019-2024)
3.2 Global AI Platforms Software 麻豆原创 Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players of AI Platforms Software, Ranking by Revenue, 2022 VS 2023 VS 2024
3.4 Global AI Platforms Software 麻豆原创 Concentration Ratio
3.4.1 Global AI Platforms Software 麻豆原创 Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by AI Platforms Software Revenue in 2023
3.5 Global Key Players of AI Platforms Software Head office and Area Served
3.6 Global Key Players of AI Platforms Software, Product and Application
3.7 Global Key Players of AI Platforms Software, Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 AI Platforms Software Breakdown Data by Type
4.1 Global AI Platforms Software Historic 麻豆原创 Size by Type (2019-2024)
4.2 Global AI Platforms Software Forecasted 麻豆原创 Size by Type (2025-2030)
5 AI Platforms Software Breakdown Data by Application
5.1 Global AI Platforms Software Historic 麻豆原创 Size by Application (2019-2024)
5.2 Global AI Platforms Software Forecasted 麻豆原创 Size by Application (2025-2030)
6 North America
6.1 North America AI Platforms Software 麻豆原创 Size (2019-2030)
6.2 North America AI Platforms Software 麻豆原创 Size by Type
6.2.1 North America AI Platforms Software 麻豆原创 Size by Type (2019-2024)
6.2.2 North America AI Platforms Software 麻豆原创 Size by Type (2025-2030)
6.2.3 North America AI Platforms Software 麻豆原创 Share by Type (2019-2030)
6.3 North America AI Platforms Software 麻豆原创 Size by Application
6.3.1 North America AI Platforms Software 麻豆原创 Size by Application (2019-2024)
6.3.2 North America AI Platforms Software 麻豆原创 Size by Application (2025-2030)
6.3.3 North America AI Platforms Software 麻豆原创 Share by Application (2019-2030)
6.4 North America AI Platforms Software 麻豆原创 Size by Country
6.4.1 North America AI Platforms Software 麻豆原创 Size by Country: 2019 VS 2023 VS 2030
6.4.2 North America AI Platforms Software 麻豆原创 Size by Country (2019-2024)
6.4.3 North America AI Platforms Software 麻豆原创 Size by Country (2025-2030)
6.4.4 U.S.
6.4.5 Canada
7 Europe
7.1 Europe AI Platforms Software 麻豆原创 Size (2019-2030)
7.2 Europe AI Platforms Software 麻豆原创 Size by Type
7.2.1 Europe AI Platforms Software 麻豆原创 Size by Type (2019-2024)
7.2.2 Europe AI Platforms Software 麻豆原创 Size by Type (2025-2030)
7.2.3 Europe AI Platforms Software 麻豆原创 Share by Type (2019-2030)
7.3 Europe AI Platforms Software 麻豆原创 Size by Application
7.3.1 Europe AI Platforms Software 麻豆原创 Size by Application (2019-2024)
7.3.2 Europe AI Platforms Software 麻豆原创 Size by Application (2025-2030)
7.3.3 Europe AI Platforms Software 麻豆原创 Share by Application (2019-2030)
7.4 Europe AI Platforms Software 麻豆原创 Size by Country
7.4.1 Europe AI Platforms Software 麻豆原创 Size by Country: 2019 VS 2023 VS 2030
7.4.2 Europe AI Platforms Software 麻豆原创 Size by Country (2019-2024)
7.4.3 Europe AI Platforms Software 麻豆原创 Size by Country (2025-2030)
7.4.3 Germany
7.4.4 France
7.4.5 U.K.
7.4.6 Italy
7.4.7 Russia
7.4.8 Nordic Countries
8 China
8.1 China AI Platforms Software 麻豆原创 Size (2019-2030)
8.2 China AI Platforms Software 麻豆原创 Size by Type
8.2.1 China AI Platforms Software 麻豆原创 Size by Type (2019-2024)
8.2.2 China AI Platforms Software 麻豆原创 Size by Type (2025-2030)
8.2.3 China AI Platforms Software 麻豆原创 Share by Type (2019-2030)
8.3 China AI Platforms Software 麻豆原创 Size by Application
8.3.1 China AI Platforms Software 麻豆原创 Size by Application (2019-2024)
8.3.2 China AI Platforms Software 麻豆原创 Size by Application (2025-2030)
8.3.3 China AI Platforms Software 麻豆原创 Share by Application (2019-2030)
9 Asia (excluding China)
9.1 Asia AI Platforms Software 麻豆原创 Size (2019-2030)
9.2 Asia AI Platforms Software 麻豆原创 Size by Type
9.2.1 Asia AI Platforms Software 麻豆原创 Size by Type (2019-2024)
9.2.2 Asia AI Platforms Software 麻豆原创 Size by Type (2025-2030)
9.2.3 Asia AI Platforms Software 麻豆原创 Share by Type (2019-2030)
9.3 Asia AI Platforms Software 麻豆原创 Size by Application
9.3.1 Asia AI Platforms Software 麻豆原创 Size by Application (2019-2024)
9.3.2 Asia AI Platforms Software 麻豆原创 Size by Application (2025-2030)
9.3.3 Asia AI Platforms Software 麻豆原创 Share by Application (2019-2030)
9.4 Asia AI Platforms Software 麻豆原创 Size by Region
9.4.1 Asia AI Platforms Software 麻豆原创 Size by Region: 2019 VS 2023 VS 2030
9.4.2 Asia AI Platforms Software 麻豆原创 Size by Region (2019-2024)
9.4.3 Asia AI Platforms Software 麻豆原创 Size by Region (2025-2030)
9.4.4 Japan
9.4.5 South Korea
9.4.6 China Taiwan
9.4.7 Southeast Asia
9.4.8 India
9.4.9 Australia
10 Middle East, Africa, and Latin America
10.1 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Size (2019-2030)
10.2 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Size by Type
10.2.1 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Size by Type (2019-2024)
10.2.2 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Size by Type (2025-2030)
10.2.3 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Share by Type (2019-2030)
10.3 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Size by Application
10.3.1 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Size by Application (2019-2024)
10.3.2 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Size by Application (2025-2030)
10.3.3 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Share by Application (2019-2030)
10.4 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Size by Country
10.4.1 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Size by Country: 2019 VS 2023 VS 2030
10.4.2 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Size by Country (2019-2024)
10.4.3 Middle East, Africa, and Latin America AI Platforms Software 麻豆原创 Size by Country (2025-2030)
10.4.4 Brazil
10.4.5 Mexico
10.4.6 Turkey
10.4.7 Saudi Arabia
10.4.8 Israel
10.4.9 GCC Countries
11 Key Players Profiles
11.1 Microsoft
11.1.1 Microsoft Company Details
11.1.2 Microsoft Business Overview
11.1.3 Microsoft AI Platforms Software Introduction
11.1.4 Microsoft Revenue in AI Platforms Software Business (2019-2024)
11.1.5 Microsoft Recent Developments
11.2 Google
11.2.1 Google Company Details
11.2.2 Google Business Overview
11.2.3 Google AI Platforms Software Introduction
11.2.4 Google Revenue in AI Platforms Software Business (2019-2024)
11.2.5 Google Recent Developments
11.3 IBM
11.3.1 IBM Company Details
11.3.2 IBM Business Overview
11.3.3 IBM AI Platforms Software Introduction
11.3.4 IBM Revenue in AI Platforms Software Business (2019-2024)
11.3.5 IBM Recent Developments
11.4 Baidu
11.4.1 Baidu Company Details
11.4.2 Baidu Business Overview
11.4.3 Baidu AI Platforms Software Introduction
11.4.4 Baidu Revenue in AI Platforms Software Business (2019-2024)
11.4.5 Baidu Recent Developments
11.5 SAP
11.5.1 SAP Company Details
11.5.2 SAP Business Overview
11.5.3 SAP AI Platforms Software Introduction
11.5.4 SAP Revenue in AI Platforms Software Business (2019-2024)
11.5.5 SAP Recent Developments
11.6 Salesforce
11.6.1 Salesforce Company Details
11.6.2 Salesforce Business Overview
11.6.3 Salesforce AI Platforms Software Introduction
11.6.4 Salesforce Revenue in AI Platforms Software Business (2019-2024)
11.6.5 Salesforce Recent Developments
11.7 Brighterion
11.7.1 Brighterion Company Details
11.7.2 Brighterion Business Overview
11.7.3 Brighterion AI Platforms Software Introduction
11.7.4 Brighterion Revenue in AI Platforms Software Business (2019-2024)
11.7.5 Brighterion Recent Developments
11.8 IFlyTek
11.8.1 IFlyTek Company Details
11.8.2 IFlyTek Business Overview
11.8.3 IFlyTek AI Platforms Software Introduction
11.8.4 IFlyTek Revenue in AI Platforms Software Business (2019-2024)
11.8.5 IFlyTek Recent Developments
11.9 Megvii Technology
11.9.1 Megvii Technology Company Details
11.9.2 Megvii Technology Business Overview
11.9.3 Megvii Technology AI Platforms Software Introduction
11.9.4 Megvii Technology Revenue in AI Platforms Software Business (2019-2024)
11.9.5 Megvii Technology Recent Developments
11.10 H2O.ai
11.10.1 H2O.ai Company Details
11.10.2 H2O.ai Business Overview
11.10.3 H2O.ai AI Platforms Software Introduction
11.10.4 H2O.ai Revenue in AI Platforms Software Business (2019-2024)
11.10.5 H2O.ai Recent Developments
11.11 Wipro
11.11.1 Wipro Company Details
11.11.2 Wipro Business Overview
11.11.3 Wipro AI Platforms Software Introduction
11.11.4 Wipro Revenue in AI Platforms Software Business (2019-2024)
11.11.5 Wipro Recent Developments
11.12 Albert Technologies
11.12.1 Albert Technologies Company Details
11.12.2 Albert Technologies Business Overview
11.12.3 Albert Technologies AI Platforms Software Introduction
11.12.4 Albert Technologies Revenue in AI Platforms Software Business (2019-2024)
11.12.5 Albert Technologies Recent Developments
11.13 NanoRep(LogMeIn)
11.13.1 NanoRep(LogMeIn) Company Details
11.13.2 NanoRep(LogMeIn) Business Overview
11.13.3 NanoRep(LogMeIn) AI Platforms Software Introduction
11.13.4 NanoRep(LogMeIn) Revenue in AI Platforms Software Business (2019-2024)
11.13.5 NanoRep(LogMeIn) Recent Developments
11.14 Brainasoft
11.14.1 Brainasoft Company Details
11.14.2 Brainasoft Business Overview
11.14.3 Brainasoft AI Platforms Software Introduction
11.14.4 Brainasoft Revenue in AI Platforms Software Business (2019-2024)
11.14.5 Brainasoft Recent Developments
11.15 Ada Support
11.15.1 Ada Support Company Details
11.15.2 Ada Support Business Overview
11.15.3 Ada Support AI Platforms Software Introduction
11.15.4 Ada Support Revenue in AI Platforms Software Business (2019-2024)
11.15.5 Ada Support Recent Developments
11.16 Yseop
11.16.1 Yseop Company Details
11.16.2 Yseop Business Overview
11.16.3 Yseop AI Platforms Software Introduction
11.16.4 Yseop Revenue in AI Platforms Software Business (2019-2024)
11.16.5 Yseop Recent Developments
11.17 IDEAL
11.17.1 IDEAL Company Details
11.17.2 IDEAL Business Overview
11.17.3 IDEAL AI Platforms Software Introduction
11.17.4 IDEAL Revenue in AI Platforms Software Business (2019-2024)
11.17.5 IDEAL Recent Developments
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details
Microsoft
Google
IBM
Baidu
SAP
Salesforce
Brighterion
IFlyTek
Megvii Technology
H2O.ai
Wipro
Albert Technologies
NanoRep(LogMeIn)
Brainasoft
Ada Support
Yseop
IDEAL
听
听
*If Applicable.
