INFORMATION & COMMUNICATION TECHNOLOGY
Global Generative AI Cybersecurity Market - Industry Trends and Forecast to 2032
REPORT OVERVIEW
Global Generative AI Cybersecurity Market, By Offering (Software and Services), Generative AI-Based Cybersecurity Solutions (Threat Detection and Intelligence Software, Risk Assessment Software, Exposure Management Software, Phishing Simulation and Prevention Software, Remediation Guidance Software, Threat Hunting Platforms, and Code Analysis Software), Cybersecurity Solutions for Generative AI (Generative AI Training Data Security Software, Generative AI Model Security Software, Generative AI Infrastructure Security Software, and Generative AI Application Security Software), Security Type (Generative AI Training Data Security Software, Generative AI Model Security Software, Generative AI Infrastructure Security Software, and Generative AI Application Security Software), End Use (Generative AI-Based Cybersecurity End-Users and Cybersecurity for Generative AI End-Users), Region (North America, Europe, Asia-Pacific, South America, Middle East and Africa) – Industry Trends and Forecast to 2032.
Market Insights
The global Generative AI Cybersecurity market size is valued to be USD xx million in 2023 and is expected to reach USD xx million by 2032, and it is expected to register a CAGR of xx% over the forecast period 2024-2032.
The global Generative AI cybersecurity market is an emerging segment leveraging artificial intelligence (AI) techniques such as machine learning (ML) to enhance various aspects of threat detection, response, and overall cybersecurity posture. Generative AI systems are designed to simulate or generate new data based on patterns and examples in the data they are trained on.
The respective global report analyses market trends, consumer behaviour and industry dynamics to guide towards entry into new markets with ease. Also, it assists in tailoring market specific and related products and services to meet the needs, preferences, and expectations of target audience by delving into their psychology. The report also specializes with comprehensive and extensive competitive analysis which offers useful insights into competitor strengths, weaknesses, opportunities, and threats. The respective report offers exclusive insights into the potential impact of disruptive developments and technologies that are expected to completely transform corporate operations. The context includes tailor-made research solutions to create a stronger footprint in their particular industries thereby offering dedicated customized solutions according to the client needs which helps in addressing unique business challenges with more simplified and efficient decision-making solutions.
Market Dynamics
DRIVERS
- Increasing sophistication of cyber threats
- Rapid growth in data volumes
RESTRAINTS
- Cost of implementation and maintenance
- Complexity and integration issues
OPPORTUNITIES
- AI-driven innovation and research
- Privacy-preserving AI techniques
CHALLENGES
- Adversarial AI and evolving threat landscape
- Performance and scalability
SEGMENTATION
- Offering
- Software
- Type
- Generative AI-Based Cybersecurity Solutions
- Cybersecurity Solutions for Generative AI
- Deployment Mode
- Cloud
- On-Premises
- Services
- Professional Services
- Training and Consulting Services
- System Integration and Deployment Services
- Support and Maintenance Services
- Managed Services
- Generative AI-Based Cybersecurity Solutions
- Threat Detection and Intelligence Software
- Automated Threat Analysis
- Security Information and Event Management
- AI-Native Security Analysis
- Threat Correlation
- Risk Assessment Software
- Automated Risk Insights
- Impact Analysis
- Risk Intelligence
- Compliance Automation
- Others
- Exposure Management Software
- Vulnerability Analysis
- Exposure Prioritization
- Automated Exposure Detection
- Incident Response
- Others
- Phishing Simulation and Prevention Software
- Phishing Simulation Campaigns
- Phishing Attack Analysis
- Deepfake Detection
- Fraud Prevention
- Social Engineering Detection
- Remediation Guidance Software
- Automated Remediation
- Interactive Remediation Support
- Proactive Threat Management
- Compliance Remediations
- Others
- Threat Hunting Platforms
- Real-Time Threat Analysis
- Natural Language Query Interface
- Behaviour Analysis
- Response Automation
- Others
- Code Analysis Software
- Code Snippet Analysis
- Source Code Protection
- Vulnerability Detection
- Automated Code Review
- Compliance Checks
- Cybersecurity Solutions for Generative AI
- Generative AI Training Data Security Software
- Data Integrity Verification
- Secure Data Augmentation
- Automated Data Cleaning
- Data Quality Monitoring
- Data Anonymization
- Generative AI Model Security Software
- Model Integrity
- Impact Analysis
- Adversarial Training and Testing
- Secure Model Training Environments
- Model Drift and Bias Detection
- Robustness Testing
- Generative AI Infrastructure Security Software
- Continuous Monitoring
- Automated Security Patching
- Secure API Management
- Real-Time Threat Detections
- Security Audits
- Generative AI Application Security Software
- Prompt Injection Security
- Data Leakage Prevention
- User Authentication and Access Control
- Monitoring and Anomaly Detection
- Ethical AI Governance
- Security Type
- Generative AI Training Data Security Software
- Data Loss Prevention
- Data Usage Monitoring
- Data Compliance and Governance
- Data Encryption
- Data Masking and Tokenization
- Access Control
- Generative AI Model Security Software
- Network Traffic Analysis
- Secure Access Service Edge (SASE)
- Zero Trust Network Access
- Firewalls
- Intrusion Detection/Prevention Systems (IDS/IPS)
- VPN and Secure Tunneling
- Generative AI Infrastructure Security Software
- Endpoint Detection and Response (EDR)
- Endpoint Protection Platforms
- Generative AI Application Security Software
- Static Application Security Testing (SAST)
- Dynamic Application Security Testing (DAST)
- LLM Security
- Runtime Protection
- Incident Response and Recovery
- Governance, Risk and Compliance
- End Use
- Generative AI-Based Cybersecurity End-Users
- BFSI
- IT and ITeS
- Telecommunications
- Government and Defense
- Healthcare and Life Sciences
- Manufacturing
- Media and Entertainment
- Retail and E-Commerce
- Energy and Utilities
- Automotive, Transportation and Logistics
- Others
- Cybersecurity for Generative AI End-Users
- Cloud Hyper Scalers
- Managed Security Service Providers
- Generative AI Providers
- Foundation Model/LLM Developers
- Data Annotators
- Content Creation Platform Providers
- Generative AI-as-a-Service Providers
The respective global report is completely customizable specific to regions (North America, Europe, Asia-Pacific, South America, Middle East and Africa), countries, and segments as per the client requirements.
REGIONAL SEGMENTATION
- North America
- U.S.
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- U.K.
- France
- Italy
- Spain
- Russia
- The Netherlands
- Belgium
- Turkey
- Rest of Europe
- Asia-Pacific
- China
- India
- Japan
- South Korea
- Singapore
- Malaysia
- Australia
- Thailand
- Philippines
- Rest of Asia-Pacific
- South America
- Brazil
- Argentina
- Chile
- Colombia
- Rest of South America
- Middle East and Africa
- Kingdom of Saudi Arabia
- South Africa
- U.A.E.
- Egypt
- Rest of Middle East and Africa
KEY MARKET PLAYERS
- Microsoft
- IBM
- NVIDIA
- Trend Micro
- XenonStack
- VirusTotal
- TrojAI
- MOSTLY AI
- Sophos
- Sangfor
Table OF CONTENTS
- SECTION 1 - INTRODUCTION
- 1.1 Taxonomy
- 1.2 Market Overview
- 1.3 Currency and Limitations
- 1.3.1 Currency
- 1.3.2 Limitations
- 1.4 Key Competitors
- SECTION 2 - RESEARCH METHODOLOGY
- 2.1 Research Approach
- 2.2 Data Collection and Validation
- 2.2.1 Secondary Research
- 2.2.2 Primary Research
- 2.3 Market Assessment
- 2.3.1 Market Size Estimation
- 2.3.2 Bottom-up Approach
- 2.3.3 Top-down Approach
- 2.3.4 Growth Forecast
- 2.4 Market Study Assumptions
- 2.5 Data Sources
- SECTION 3 - EXECUTIVE SUMMARY
- 3.1 Global Generative AI Cybersecurity Market, by Offering
- 3.2 Global Generative AI Cybersecurity Market, by Generative AI-Based Cybersecurity Solutions
- 3.3 Global Generative AI Cybersecurity Market, by Cybersecurity Solutions for Generative AI
- 3.4 Global Generative AI Cybersecurity Market, by Security Type
- 3.5 Global Generative AI Cybersecurity Market, by End Use
- 3.6 Global Generative AI Cybersecurity Market, by Geography
- 3.7 Market Position Grid
- SECTION 4 - PREMIUM INSIGHTS
- 4.1 Regulatory Framework
- 4.1.1 Standards
- 4.1.2 Regulatory Landscape
- 4.2 Value Chain Analysis
- 4.3 Supply Chain Analysis
- 4.4 COVID-19 Impact
- 4.5 Russia-Ukraine War Impact
- 4.6 PORTER's Five Force Analysis
- 4.7 PESTLE Analysis
- 4.8 SWOT Analysis
- 4.9 Go to Market Strategy
- 4.10 Opportunity Orbit
- 4.11 Multivariate Modelling
- 4.12 Pricing Analysis
- SECTION 5 - MARKET DYNAMICS
- 5.1 Trends
- 5.1.1 Behavioral analytics and anomaly detection
- 5.1.2 Automated incident response
- 5.1.3 Trend 3
- 5.2 Drivers
- 5.2.1 Increasing sophistication of cyber threats
- 5.2.2 Rapid growth in data volumes
- 5.2.3 Driver 3
- 5.2.4 Driver 4
- 5.3 Restraints
- 5.3.1 Cost of implementation and maintenance
- 5.3.2 Complexity and integration issues
- 5.3.3 Restraint 3
- 5.4 Opportunities
- 5.4.1 AI-driven innovation and research
- 5.4.2 Privacy-preserving AI techniques
- 5.4.3 Opportunity 3
- 5.4.4 Opportunity 4
- 5.5 Challenges
- 5.5.1 Adversarial AI and evolving threat landscape
- 5.5.2 Performance and scalability
- 5.5.3 Challenge 3
- SECTION 6 - GLOBAL GENERATIVE AI CYBERSECURITY MARKET, BY OFFERING
- 6.1 Offering Summary
- 6.2 Market Attractive Index
- 6.3 Global Generative AI Cybersecurity Market, by Offering (2019-2032)
- SECTION 7 - GLOBAL GENERATIVE AI CYBERSECURITY MARKET, BY GENERATIVE AI-BASED CYBERSECURITY SOLUTIONS
- 7.1 Generative AI-Based Cybersecurity Solutions Summary
- 7.2 Market Attractive Index
- 7.3 Global Generative AI Cybersecurity Market, by Generative AI-Based Cybersecurity Solutions (2019-2032)
- SECTION 8 - GLOBAL GENERATIVE AI CYBERSECURITY MARKET, BY CYBERSECURITY SOLUTIONS FOR GENERATIVE AI
- 8.1 Cybersecurity Solutions for Generative AI Summary
- 8.2 Market Attractive Index
- 8.3 Global Generative AI Cybersecurity Market, by Cybersecurity Solutions for Generative AI (2019-2032)
- SECTION 9 - GLOBAL GENERATIVE AI CYBERSECURITY MARKET, BY SECURITY TYPE
- 9.1 Security Type Summary
- 9.2 Market Attractive Index
- 9.3 Global Generative AI Cybersecurity Market, by Security Type (2019-2032)
- SECTION 10 - GLOBAL GENERATIVE AI CYBERSECURITY MARKET, BY END USE
- 10.1 End Use Summary
- 10.2 Market Attractive Index
- 10.3 Global Generative AI Cybersecurity Market, by End Use (2019-2032)
- SECTION 11 - GLOBAL GENERATIVE AI CYBERSECURITY MARKET, BY GEOGRAPHY
- 11.1 Regional Summary
- 11.2 Market Attractive Index
- 11.3 Global Generative AI Cybersecurity Market, by Geography (2019-2032)
- SECTION 12 - NORTH AMERICA GENERATIVE AI CYBERSECURITY MARKET
- 12.1 North America Summary
- 12.2 Market Attractive Index
- 12.3 North America Generative AI Cybersecurity Market, by Offering (2019-2032)
- 12.4 North America Generative AI Cybersecurity Market, by Generative AI-Based Cybersecurity Solutions (2019-2032)
- 12.5 North America Generative AI Cybersecurity Market, by Cybersecurity Solutions for Generative AI (2019-2032)
- 12.6 North America Generative AI Cybersecurity Market, by Security Type (2019-2032)
- 12.7 North America Generative AI Cybersecurity Market, by End Use (2019-2032)
- 12.8 North America Generative AI Cybersecurity Market, by Country (2019-2032)
- 12.8.1 U.S.
- 12.8.2 Canada
- 12.8.3 Mexico
- 12.8.4 Rest of North America
- SECTION 13 - EUROPE GENERATIVE AI CYBERSECURITY MARKET
- 13.1 Europe Summary
- 13.2 Market Attractive Index
- 13.3 Europe Generative AI Cybersecurity Market, by Offering (2019-2032)
- 13.4 Europe Generative AI Cybersecurity Market, by Generative AI-Based Cybersecurity Solutions (2019-2032)
- 13.5 Europe Generative AI Cybersecurity Market, by Cybersecurity Solutions for Generative AI (2019-2032)
- 13.6 Europe Generative AI Cybersecurity Market, by Security Type (2019-2032)
- 13.7 Europe Generative AI Cybersecurity Market, by End Use (2019-2032)
- 13.8 Europe Generative AI Cybersecurity Market, by Country (2019-2032)
- 13.8.1 Germany
- 13.8.2 U.K.
- 13.8.3 France
- 13.8.4 Italy
- 13.8.5 Spain
- 13.8.6 Russia
- 13.8.7 The Netherlands
- 13.8.8 Belgium
- 13.8.9 Turkey
- 13.8.10 Rest of Europe
- SECTION 14 - ASIA-PACIFIC GENERATIVE AI CYBERSECURITY MARKET
- 14.1 Asia-Pacific Summary
- 14.2 Market Attractive Index
- 14.3 Asia-Pacific Generative AI Cybersecurity Market, by Offering (2019-2032)
- 14.4 Asia-Pacific Generative AI Cybersecurity Market, by Generative AI-Based Cybersecurity Solutions (2019-2032)
- 14.5 Asia-Pacific Generative AI Cybersecurity Market, by Cybersecurity Solutions for Generative AI (2019-2032)
- 14.6 Asia-Pacific Generative AI Cybersecurity Market, by Security Type (2019-2032)
- 14.7 Asia-Pacific Generative AI Cybersecurity Market, by End Use (2019-2032)
- 14.8 Asia-Pacific Generative AI Cybersecurity Market, by Country (2019-2032)
- 14.8.1 China
- 14.8.2 India
- 14.8.3 Japan
- 14.8.4 South Korea
- 14.8.5 Singapore
- 14.8.6 Malaysia
- 14.8.7 Australia
- 14.8.8 Thailand
- 14.8.9 Philippines
- 14.8.10 Rest of Asia-Pacific
- SECTION 15 - SOUTH AMERICA GENERATIVE AI CYBERSECURITY MARKET
- 15.1 South America Summary
- 15.2 Market Attractive Index
- 15.3 South America Generative AI Cybersecurity Market, by Offering (2019-2032)
- 15.4 South America Generative AI Cybersecurity Market, by Generative AI-Based Cybersecurity Solutions (2019-2032)
- 15.5 South America Generative AI Cybersecurity Market, by Cybersecurity Solutions for Generative AI (2019-2032)
- 15.6 South America Generative AI Cybersecurity Market, by Security Type (2019-2032)
- 15.7 South America Generative AI Cybersecurity Market, by End Use (2019-2032)
- 15.8 South America Generative AI Cybersecurity Market, by Country (2019-2032)
- 15.8.1 Brazil
- 15.8.2 Argentina
- 15.8.3 Chile
- 15.8.4 Colombia
- 15.8.5 Rest of South America
- SECTION 16 - MIDDLE EAST AND AFRICA GENERATIVE AI CYBERSECURITY MARKET
- 16.1 Middle East and Africa Summary
- 16.2 Market Attractive Index
- 16.3 Middle East and Africa Generative AI Cybersecurity Market, by Offering (2019-2032)
- 16.4 Middle East and Africa Generative AI Cybersecurity Market, by Generative AI-Based Cybersecurity Solutions (2019-2032)
- 16.5 Middle East and Africa Generative AI Cybersecurity Market, by Cybersecurity Solutions for Generative AI (2019-2032)
- 16.6 Middle East and Africa Generative AI Cybersecurity Market, by Security Type (2019-2032)
- 16.7 Middle East and Africa Generative AI Cybersecurity Market, by End Use (2019-2032)
- 16.8 Middle East and Africa Generative AI Cybersecurity Market, by Country (2019-2032)
- 16.8.1 Kingdom of Saudi Arabia
- 16.8.2 South Africa
- 16.8.3 U.A.E.
- 16.8.4 Egypt
- 16.8.5 Rest of Middle East and Africa
- SECTION 17 - COMPANY SHARE ANALYSIS
- 17.1 Global Generative AI Cybersecurity Market, Company Share Analysis
- 17.2 North America Generative AI Cybersecurity Market, Company Share Analysis
- 17.3 Europe Generative AI Cybersecurity Market, Company Share Analysis
- 17.4 Asia-Pacific Generative AI Cybersecurity Market, Company Share Analysis
- SECTION 18 - COMPANY PROFILES
- 18.1 Microsoft
- 18.1.1 Company Snapshot
- 18.1.2 Financial Overview
- 18.1.3 Product Portfolio
- 18.1.4 Recent Developments
- 18.2 IBM
- 18.2.1 Company Snapshot
- 18.2.2 Financial Overview
- 18.2.3 Product Portfolio
- 18.2.4 Recent Developments
- 18.3 NVIDIA
- 18.3.1 Company Snapshot
- 18.3.2 Financial Overview
- 18.3.3 Product Portfolio
- 18.3.4 Recent Developments
- 18.4 Trend Micro
- 18.4.1 Company Snapshot
- 18.4.2 Financial Overview
- 18.4.3 Product Portfolio
- 18.4.4 Recent Developments
- 18.5 XenonStack
- 18.5.1 Company Snapshot
- 18.5.2 Financial Overview
- 18.5.3 Product Portfolio
- 18.5.4 Recent Developments
- 18.6 VirusTotal
- 18.6.1 Company Snapshot
- 18.6.2 Financial Overview
- 18.6.3 Product Portfolio
- 18.6.4 Recent Developments
- 18.7 TrojAI
- 18.7.1 Company Snapshot
- 18.7.2 Financial Overview
- 18.7.3 Product Portfolio
- 18.7.4 Recent Developments
- 18.8 MOSTLY AI
- 18.8.1 Company Snapshot
- 18.8.2 Financial Overview
- 18.8.3 Product Portfolio
- 18.8.4 Recent Developments
- 18.9 Sophos
- 18.9.1 Company Snapshot
- 18.9.2 Financial Overview
- 18.9.3 Product Portfolio
- 18.9.4 Recent Developments
- 18.10 Sangfor
- 18.10.1 Company Snapshot
- 18.10.2 Financial Overview
- 18.10.3 Product Portfolio
- 18.10.4 Recent Developments
- SECTION 19 - RELATED REPORTS
- SECTION 20 - DISCLAIMER
RESEARCH METHODOLOGY
The research methodology employed in Uniprism Market Research involves four basic steps namely research and data collection, data pre-processing, modeling and forecasting, quality assurance and output.
RESEARCH AND DATA COLLECTION
A tripod model research technique is followed for research and data collection in which various approaches such as primary research, secondary research, and product mapping are considered.
Primary research basically involves the process of conducting personalized interviews with market related professionals of major market players, investors, distributors, vendors and many more.
The secondary research include data published by government, annual reports, press releases, investor presentations of companies, white papers, certified publications, annual manufacturing limit of the respective industries related to the market, production consumption analysis of certain products respective to the market and many more.
Below mention are few of the sources which we have considered while estimating the market size:
For instance,
- Research articles published on Technium
- Science and MDPI
- Research publications by government approved associations and societies
Product mapping means the process of mapping the list of products that a key player contributes to the market as well as estimating the revenue of those products in order to define the Global Company share analysis of the respective Global Company in global, regional, and country level markets.
DATA PRE-PROCESSING
The term "data pre-processing" refers to the collection of procedures and methods used to clean, modify, and make ready for analysis the raw data gathered during research and data collection. The completion of this phase is necessary to guarantee that the data are reliable, consistent, and appropriate for statistical analysis and other data-driven tasks. The data pre-processing ensures that the information gathered from research and data collection is comparable and expressed in standard units, by the integration of missing data pointers and algorithmic approaches.
MODELING AND FORECASTING
The process of developing mathematical, statistical, or computational representations of real-world occurrences or relationships is known as modelling. These models are intended to replicate and explain market interactions, interdependence, and dynamics. These models are used by Uniprism Market Research to acquire a better knowledge of numerous market characteristics such as customer preferences, pricing elasticity, competition dynamics, and more. Depending on the individual study aims, many types of models are utilized, such as regression models, econometric models, decision tree models, and machine learning models.
Forecasting is the process of predicting future market conditions, trends, and occurrences using past data and models. Forecasting is used by Uniprism Market Research to estimate future sales, demand for products or services, market growth, and other important performance metrics. Forecasting accurately can assist organizations in making educated decisions about resource allocation, pricing, inventory management, and marketing tactics.
We create standardized bottom-up or top-down models that scale by leveraging data science and machine learning technology. All our market models consider the unique market characteristics of each country. Forecasting is based on major market indicators and a combination of traditional methodologies, such as exponential smoothing, time series analysis, regression analysis, and more modern techniques such as machine learning algorithms are all forecasting methodologies. The method chosen is determined on the nature of the data and the specific forecasting aims.
QUALITY ASSURANCE AND OUTPUT
Quality assurance and output involves the process of validation, adjustments, further publications of key market indicators. Extensive plausibility and consistency tests are performed on derived time series to ensure the high degree of quality of our market analysis. This quality assurance procedure also includes rigorous inspection, validation, and editing by an experienced management team to assure the dependability of the published data.