Global Generative AI Security 麻豆原创 Research Report 2025

Publication ID:

PB501262405

Publication Date:

January 22, 2025

Pages:

Publisher:

MRRPB5

Countries:

Global [1]

USD 2,900.00

IT Services [2]

Computing & Electronics [3]

Description:

The global market for Generative AI Security was valued at US$ 1024 million in the year 2024 and is projected to reach a revised size of US$ 2840 million by 2031, growing at a CAGR of 12.0% during the forecast period.
Generative AI Security refers to the measures, practices, and technologies employed to ensure the safety, integrity, and confidentiality of generative artificial intelligence (AI) systems. These systems are designed to produce new text, images, code, video, audio, and other content in a human-like fashion. Generative AI has revolutionized various industries, including entertainment, design, and technology, by providing innovative and efficient ways to create content.
North American market for Generative AI Security is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
Asia-Pacific market for Generative AI Security is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The global market for Generative AI Security in Design is estimated to increase from $ million in 2024 to $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The major global companies of Generative AI Security include Google DeepMind, IBM, Microsoft, NVIDIA, Cohere, Sift, Darktrace, CrowdStrike, Fortinet, CyberArk, etc. In 2024, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for Generative AI Security, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Generative AI Security.
The Generative AI Security market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. This report segments the global Generative AI Security market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Generative AI Security companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
麻豆原创 Segmentation
By Company
Google DeepMind
IBM
Microsoft
NVIDIA
Cohere
Sift
Darktrace
CrowdStrike
Fortinet
CyberArk
SentinelOne
Palo Alto Networks
Tencent
Baidu
Segment by Type
Data Privacy and Security
Model Security and Robustness
Others
Segment by Application
Design
Entertainment
Technology
Others
By Region
North America
United States
Canada
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Europe
Germany
France
U.K.
Italy
Russia
Nordic Countries
Rest of Europe
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by 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: Introduces executive summary of global market size, regional market size, 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 Generative AI Security company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size 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 market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. 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.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.

Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.

Table Of Contents:

1 Report Overview
1.1 Study Scope
1.2 麻豆原创 Analysis by Type
1.2.1 Global Generative AI Security 麻豆原创 Size Growth Rate by Type: 2020 VS 2024 VS 2031
1.2.2 Data Privacy and Security
1.2.3 Model Security and Robustness
1.2.4 Others
1.3 麻豆原创 by Application
1.3.1 Global Generative AI Security 麻豆原创 Growth by Application: 2020 VS 2024 VS 2031
1.3.2 Design
1.3.3 Entertainment
1.3.4 Technology
1.3.5 Others
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Global Growth Trends
2.1 Global Generative AI Security 麻豆原创 Perspective (2020-2031)
2.2 Global Generative AI Security Growth Trends by Region
2.2.1 Global Generative AI Security 麻豆原创 Size by Region: 2020 VS 2024 VS 2031
2.2.2 Generative AI Security Historic 麻豆原创 Size by Region (2020-2025)
2.2.3 Generative AI Security Forecasted 麻豆原创 Size by Region (2026-2031)
2.3 Generative AI Security 麻豆原创 Dynamics
2.3.1 Generative AI Security Industry Trends
2.3.2 Generative AI Security 麻豆原创 Drivers
2.3.3 Generative AI Security 麻豆原创 Challenges
2.3.4 Generative AI Security 麻豆原创 Restraints
3 Competition Landscape by Key Players
3.1 Global Top Generative AI Security Players by Revenue
3.1.1 Global Top Generative AI Security Players by Revenue (2020-2025)
3.1.2 Global Generative AI Security Revenue 麻豆原创 Share by Players (2020-2025)
3.2 Global Top Generative AI Security Players by Company Type and 麻豆原创 Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players Ranking by Generative AI Security Revenue
3.4 Global Generative AI Security 麻豆原创 Concentration Ratio
3.4.1 Global Generative AI Security 麻豆原创 Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Generative AI Security Revenue in 2024
3.5 Global Key Players of Generative AI Security Head office and Area Served
3.6 Global Key Players of Generative AI Security, Product and Application
3.7 Global Key Players of Generative AI Security, Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 Generative AI Security Breakdown Data by Type
4.1 Global Generative AI Security Historic 麻豆原创 Size by Type (2020-2025)
4.2 Global Generative AI Security Forecasted 麻豆原创 Size by Type (2026-2031)
5 Generative AI Security Breakdown Data by Application
5.1 Global Generative AI Security Historic 麻豆原创 Size by Application (2020-2025)
5.2 Global Generative AI Security Forecasted 麻豆原创 Size by Application (2026-2031)
6 North America
6.1 North America Generative AI Security 麻豆原创 Size (2020-2031)
6.2 North America Generative AI Security 麻豆原创 Growth Rate by Country: 2020 VS 2024 VS 2031
6.3 North America Generative AI Security 麻豆原创 Size by Country (2020-2025)
6.4 North America Generative AI Security 麻豆原创 Size by Country (2026-2031)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Generative AI Security 麻豆原创 Size (2020-2031)
7.2 Europe Generative AI Security 麻豆原创 Growth Rate by Country: 2020 VS 2024 VS 2031
7.3 Europe Generative AI Security 麻豆原创 Size by Country (2020-2025)
7.4 Europe Generative AI Security 麻豆原创 Size by Country (2026-2031)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Generative AI Security 麻豆原创 Size (2020-2031)
8.2 Asia-Pacific Generative AI Security 麻豆原创 Growth Rate by Region: 2020 VS 2024 VS 2031
8.3 Asia-Pacific Generative AI Security 麻豆原创 Size by Region (2020-2025)
8.4 Asia-Pacific Generative AI Security 麻豆原创 Size by Region (2026-2031)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Generative AI Security 麻豆原创 Size (2020-2031)
9.2 Latin America Generative AI Security 麻豆原创 Growth Rate by Country: 2020 VS 2024 VS 2031
9.3 Latin America Generative AI Security 麻豆原创 Size by Country (2020-2025)
9.4 Latin America Generative AI Security 麻豆原创 Size by Country (2026-2031)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Generative AI Security 麻豆原创 Size (2020-2031)
10.2 Middle East & Africa Generative AI Security 麻豆原创 Growth Rate by Country: 2020 VS 2024 VS 2031
10.3 Middle East & Africa Generative AI Security 麻豆原创 Size by Country (2020-2025)
10.4 Middle East & Africa Generative AI Security 麻豆原创 Size by Country (2026-2031)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Google DeepMind
11.1.1 Google DeepMind Company Details
11.1.2 Google DeepMind Business Overview
11.1.3 Google DeepMind Generative AI Security Introduction
11.1.4 Google DeepMind Revenue in Generative AI Security Business (2020-2025)
11.1.5 Google DeepMind Recent Development
11.2 IBM
11.2.1 IBM Company Details
11.2.2 IBM Business Overview
11.2.3 IBM Generative AI Security Introduction
11.2.4 IBM Revenue in Generative AI Security Business (2020-2025)
11.2.5 IBM Recent Development
11.3 Microsoft
11.3.1 Microsoft Company Details
11.3.2 Microsoft Business Overview
11.3.3 Microsoft Generative AI Security Introduction
11.3.4 Microsoft Revenue in Generative AI Security Business (2020-2025)
11.3.5 Microsoft Recent Development
11.4 NVIDIA
11.4.1 NVIDIA Company Details
11.4.2 NVIDIA Business Overview
11.4.3 NVIDIA Generative AI Security Introduction
11.4.4 NVIDIA Revenue in Generative AI Security Business (2020-2025)
11.4.5 NVIDIA Recent Development
11.5 Cohere
11.5.1 Cohere Company Details
11.5.2 Cohere Business Overview
11.5.3 Cohere Generative AI Security Introduction
11.5.4 Cohere Revenue in Generative AI Security Business (2020-2025)
11.5.5 Cohere Recent Development
11.6 Sift
11.6.1 Sift Company Details
11.6.2 Sift Business Overview
11.6.3 Sift Generative AI Security Introduction
11.6.4 Sift Revenue in Generative AI Security Business (2020-2025)
11.6.5 Sift Recent Development
11.7 Darktrace
11.7.1 Darktrace Company Details
11.7.2 Darktrace Business Overview
11.7.3 Darktrace Generative AI Security Introduction
11.7.4 Darktrace Revenue in Generative AI Security Business (2020-2025)
11.7.5 Darktrace Recent Development
11.8 CrowdStrike
11.8.1 CrowdStrike Company Details
11.8.2 CrowdStrike Business Overview
11.8.3 CrowdStrike Generative AI Security Introduction
11.8.4 CrowdStrike Revenue in Generative AI Security Business (2020-2025)
11.8.5 CrowdStrike Recent Development
11.9 Fortinet
11.9.1 Fortinet Company Details
11.9.2 Fortinet Business Overview
11.9.3 Fortinet Generative AI Security Introduction
11.9.4 Fortinet Revenue in Generative AI Security Business (2020-2025)
11.9.5 Fortinet Recent Development
11.10 CyberArk
11.10.1 CyberArk Company Details
11.10.2 CyberArk Business Overview
11.10.3 CyberArk Generative AI Security Introduction
11.10.4 CyberArk Revenue in Generative AI Security Business (2020-2025)
11.10.5 CyberArk Recent Development
11.11 SentinelOne
11.11.1 SentinelOne Company Details
11.11.2 SentinelOne Business Overview
11.11.3 SentinelOne Generative AI Security Introduction
11.11.4 SentinelOne Revenue in Generative AI Security Business (2020-2025)
11.11.5 SentinelOne Recent Development
11.12 Palo Alto Networks
11.12.1 Palo Alto Networks Company Details
11.12.2 Palo Alto Networks Business Overview
11.12.3 Palo Alto Networks Generative AI Security Introduction
11.12.4 Palo Alto Networks Revenue in Generative AI Security Business (2020-2025)
11.12.5 Palo Alto Networks Recent Development
11.13 Tencent
11.13.1 Tencent Company Details
11.13.2 Tencent Business Overview
11.13.3 Tencent Generative AI Security Introduction
11.13.4 Tencent Revenue in Generative AI Security Business (2020-2025)
11.13.5 Tencent Recent Development
11.14 Baidu
11.14.1 Baidu Company Details
11.14.2 Baidu Business Overview
11.14.3 Baidu Generative AI Security Introduction
11.14.4 Baidu Revenue in Generative AI Security Business (2020-2025)
11.14.5 Baidu Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.1.1 Research Programs/Design
13.1.1.2 麻豆原创 Size Estimation
13.1.1.3 麻豆原创 Breakdown and Data Triangulation
13.1.2 Data Source
13.1.2.1 Secondary Sources
13.1.2.2 Primary Sources
13.2 Author Details
13.3 Disclaimer

Companies Mentioned:

Google DeepMind
IBM
Microsoft
NVIDIA
Cohere
Sift
Darktrace
CrowdStrike
Fortinet
CyberArk
SentinelOne
Palo Alto Networks
Tencent
Baidu

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