Generative AI Cybersecurity Market

Generative AI Cybersecurity Market - Global Forecast to 2030

Report Code: UC 6470 Jun, 2024, by marketsandmarkets.com

The generative AI cybersecurity market is undergoing rapid expansions, with projections indicating a substantial increase in market size. Estimates suggest a notable expansion from its value of USD 2.5 billion in 2024 to USD 14.5 billion by 2030, reflecting a robust CAGR of 34.0% over the forecast period. The generative AI cybersecurity market has experienced significant growth driven by the escalating sophistication of cyber threats and the increasing need for advanced, adaptive defense mechanisms. The demand for generative AI solutions has surged as organizations grapple with the expanding attack surface and the evolving nature of cyberattacks. These systems leverage machine learning and deep neural networks to autonomously detect, analyze, and respond to previously unseen threats in real time. The ability of generative AI to learn from vast datasets and adapt its defense strategies has made it a crucial component in safeguarding sensitive information and critical infrastructure.

Generative AI Cybersecurity Market

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Market Dynamics

Driver: Increasing sophistication and frequency of cyber threats

The escalating frequency and complexity of cyber threats serve as a potent driver for the generative AI cybersecurity market. With the persistent evolution of attack techniques, conventional cybersecurity measures often struggle to keep pace. Generative AI, powered by machine learning and deep neural networks, addresses this challenge by autonomously learning from historical data, identifying patterns, and adapting its defense strategies in real time. This dynamic capability positions generative AI as a crucial driver in cybersecurity, offering organizations a proactive and intelligent defense mechanism against novel and sophisticated cyber threats.

Restraint: Ethical and privacy-related issues with generative AI models

Despite its transformative potential, the generative AI cybersecurity market faces notable restraints regarding ethical and privacy concerns. As generative AI systems process vast amounts of sensitive data, questions arise regarding accountability, transparency, and the potential introduction of unintended biases. The opacity of some deep learning models raises ethical considerations, making it imperative for the industry to address these concerns and establish frameworks for responsible and transparent use of generative AI in cybersecurity. Navigating this ethical landscape is crucial for fostering trust and ensuring the widespread adoption of generative AI solutions.

Opportunity: Rising affinity of enterprises toward generative AI-infused cybersecurity solutions

The ongoing wave of digital transformation across industries presents a substantial opportunity for the generative AI cybersecurity market. As organizations embrace digitization, IoT, and cloud technologies, the attack surface expands, necessitating advanced cybersecurity measures. Generative AI, with its capacity to analyze vast and diverse datasets, emerges as a key enabler in providing proactive and adaptive security solutions. This creates a significant market opportunity for innovators to develop and deploy generative AI cybersecurity solutions that cater to the evolving needs of businesses in the digital era, offering robust protection against a spectrum of cyber threats.

Challenge:Compatibility issues with legacy cybersecurity systems

Interoperability and integration challenges pose a notable hurdle for the generative AI cybersecurity market. Achieving seamless integration of generative AI solutions with existing cybersecurity infrastructure and ensuring compatibility across diverse systems can be intricate. The challenge lies in creating a cohesive and unified cybersecurity strategy that effectively leverages generative AI without introducing disruptions or vulnerabilities in the existing security ecosystem. Overcoming these integration challenges requires collaborative efforts between AI developers, cybersecurity experts, and organizations to ensure a harmonious implementation of generative AI in cybersecurity frameworks across various industries

Generative AI Cybersecurity Market Ecosystem

Generative AI Cybersecurity Market

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By offering, generative AI cybersecurity software segment to account for a significant market size during forecast period.

The generative AI cybersecurity software segment has experienced robust growth fueled by the escalating sophistication of cyber threats and the imperative for advanced defense mechanisms. As organizations confront an evolving threat landscape, there is an increasing reliance on generative AI-powered solutions to detect, analyze, and mitigate complex and previously unseen security risks. These software applications leverage machine learning algorithms and deep neural networks to adapt autonomously to emerging threats in real-time, providing a proactive and dynamic defense posture. The growing digital transformation across industries further amplifies the demand for generative AI cybersecurity software, the expansion of attack surfaces, and the need for resilient security measures.

By security type, the endpoint security segment is slated to witness an impressive growth rate during the forecast period.

The growth of generative AI cybersecurity in the endpoint security segment has been remarkable, driven by the imperative to fortify defenses against increasingly sophisticated and targeted cyber threats. As organizations witness a surge in remote work and diverse endpoints, the demand for advanced cybersecurity measures has escalated. Generative AI, with its capacity to autonomously learn and adapt to evolving threats, has become a linchpin in endpoint security strategies. These solutions offer real-time threat detection, behavior analysis, and dynamic response mechanisms, providing a proactive shield against malware, ransomware, and other malicious activities at the individual device level.

The Asia Pacific region is set to experience market expansion over the forecast period.

The growth of generative AI cybersecurity across the Asia-Pacific (APAC) region has been notable, driven by a combination of factors that underscore the increasing awareness of cybersecurity challenges and the rapid digital transformation in the area. As APAC nations embrace advanced technologies and witness a surge in online activities, the region becomes a prime target for cyber threats. Generative AI cybersecurity solutions are gaining traction due to their ability to offer sophisticated threat detection, automated response mechanisms, and adaptability to diverse cyber landscapes. Governments, enterprises, and organizations across APAC are recognizing the importance of leveraging generative AI to bolster their cybersecurity postures, especially in the face of advanced and evolving cyber threats that traditional security measures may struggle to address effectively.

The unique challenges presented by the APAC region's diversity of languages, cultures, and regulatory environments further emphasize the need for advanced, adaptive cybersecurity measures. Generative AI technologies, with their ability to learn and adapt across varied contexts, are well-suited to address these challenges. The growth of the generative AI cybersecurity market in APAC is characterized by increased investments, collaborations between technology providers and local enterprises, and a growing emphasis on regulatory frameworks to ensure responsible and secure deployment of these advanced cybersecurity solutions across the region.

Key Market Players

The generative AI cybersecurity solution and service providers have implemented various organic and inorganic growth strategies, such as new product launches, product upgrades, partnerships, agreements, business expansions, and mergers and acquisitions, to strengthen their offerings in the market. Some major players in the generative AI cybersecurity market include SentinelOne (US), Cisco (US), Trend Micro (Japan), NVIDIA (US), and Intel (US), along with SMEs and startups such as CrowdStrike (US), Checkmarx (Israel), Elastic NV (Netherlands), Tenable (US), and Recorded Future (US).

Recent Developments:

  • In December 2023, NVIDIA was reported to have achieved a noteworthy 20% improvement in an AI model's proficiency in detecting phishing attempts – through generative AI. Through continuous training and refinement, the generative AI-based model became more adept at discerning sophisticated attacks, leading to a reduction in false positives.
  • In October 2023, BlackBerry Limited unveiled a new generative AI-powered assistant designed for Security Operations Center (SOC) teams. This enterprise-grade solution is a SOC Analyst, offering cyber threat analysis and support using Generative AI. Integrated within BlackBerry's Cylance AI platform, the solution anticipates customer needs, delivering proactive information without manual queries and significantly reducing research time.
  • In May 2023, CrowdStrike launched CrowdStrike Charlotte AI, an innovative generative AI security analyst designed to simplify security operations for users of all expertise levels. As an intelligent security analyst within an organization, Charlotte AI offers real-time insights into the security posture, empowering cybersecurity professionals to make quicker, informed decisions by leveraging the rich, real-time data from the Falcon platform.

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TABLE OF CONTENTS
 
1 INTRODUCTION 
    1.1. OBJECTIVES OF THE STUDY 
    1.2. MARKET DEFINITION 
           1.2.1. INCLUSIONS AND EXCLUSIONS
    1.3. MARKET SCOPE 
           1.3.1. MARKET SEGMENTATION
           1.3.2. REGIONS COVERED
           1.3.3. YEARS CONSIDERED FOR THE STUDY
    1.4. CURRENCY CONSIDERED 
    1.5. STAKEHOLDERS 
 
2 RESEARCH METHODOLOGY 
    2.1. RESEARCH DATA 
           2.1.1. SECONDARY DATA
           2.1.2. PRIMARY DATA
                    2.1.2.1. BREAKUP OF PRIMARY PROFILES
                    2.1.2.2. KEY INDUSTRY INSIGHTS
    2.2. MARKET BREAKUP AND DATA TRIANGULATION 
    2.3. MARKET SIZE ESTIMATION 
           2.3.1. TOP-DOWN APPROACH
           2.3.2. BOTTOM-UP APPROACH
    2.4. MARKET FORECAST 
    2.5. ASSUMPTIONS FOR THE STUDY 
    2.6. LIMITATIONS OF THE STUDY 
    2.7. IMPLICATIONS OF RECESSION ON THE GLOBAL GENERATIVE AI CYBERSECURITY MARKET 
 
3 EXECUTIVE SUMMARY 
 
4 PREMIUM INSIGHTS 
    4.1. ATTRACTIVE OPPORTUNITIES IN THE GLOBAL GENERATIVE AI CYBERSECURITY MARKET 
    4.2. GENERATIVE AI CYBERSECURITY MARKET, BY OFFERING, 2024 VS. 2030 
    4.3. GENERATIVE AI CYBERSECURITY MARKET, BY SECURITY TYPE, 2024 VS. 2030 
    4.4. GENERATIVE AI CYBERSECURITY MARKET, BY VERTICAL, 2024 VS. 2030 
    4.5. GENERATIVE AI CYBERSECURITY MARKET, BY REGION 
 
5 MARKET OVERVIEW 
    5.1. INTRODUCTION 
    5.2. MARKET DYNAMICS 
           5.2.1. DRIVERS
           5.2.2. RESTRAINTS
           5.2.3. OPPORTUNITIES
           5.2.4. CHALLENGES
    5.3. EVOLUTION OF GENERATIVE AI CYBERSECURITY 
    5.4. SUPPLY/VALUE CHAIN ANALYSIS 
    5.5. ECOSYSTEM ANALYSIS 
    5.6. INVESTMENT LANDSCAPE 
    5.7. GENERATIVE AI CYBERSECURITY: BEST PRACTICES 
    5.8. CASE STUDY ANALYSIS 
           5.8.1. CASE STUDY 1
           5.8.2. CASE STUDY 2
           5.8.3. CASE STUDY 3
    5.9. TECHNOLOGY ANALYSIS 
           5.9.1. KEY TECHNOLOGIES
           5.9.2. ADJACENT TECHNOLOGIES
           5.9.3. COMPLIMENTARY TECHNOLOGIES
           5.10. TARIFF AND REGULATORY LANDSCAPE
                    5.10.1. TARIFF RELATED TO GENERATIVE AI CYBERSECURITY SOLUTIONS
                    5.10.2. REGULATORY BODIES, GOVERNMENT AGENCIES AND OTHER ORGANIZATIONS
                               5.10.2.1. NORTH AMERICA
                               5.10.2.2. EUROPE
                               5.10.2.3. ASIA PACIFIC
                               5.10.2.4. MIDDLE EAST AND AFRICA
                               5.10.2.5. LATIN AMERICA
           5.11. PATENT ANALYSIS
                    5.11.1. METHODOLOGY
                    5.11.2. PATENTS FILED, BY DOCUMENT TYPE, 2013–2023
                    5.11.3. INNOVATION AND PATENT APPLICATIONS
                               5.11.3.1. TOP APPLICANTS
           5.12. PRICING ANALYSIS
                    5.12.1. AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY SOFTWARE
                    5.12.2. INDICATIVE PRICING ANALYSIS, BY GENERATIVE AI CYBERSECURITY VENDORS
           5.13. TRADE ANALYSIS
           5.14. KEY CONFERENCES AND EVENTS, 2024-2025
           5.15. PORTER FIVE FORCES ANALYSIS
                    5.15.1. THREAT FROM NEW ENTRANTS
                    5.15.2. THREAT OF SUBSTITUTES
                    5.15.3. BARGAINING POWER OF SUPPLIERS
                    5.15.4. BARGAINING POWER OF BUYERS
                    5.15.5. INTENSITY OF COMPETITION RIVALRY
           5.16. GENERATIVE AI CYBERSECURITY TECHNOLOGY ROADMAP
                    5.16.1. SHORT-TERM ROADMAP (1–5 YEARS)
                    5.16.2. LONG-TERM ROADMAP (5+ YEARS)
           5.17. GENERATIVE AI CYBERSECURITY BUSINESS MODELS
           5.18. TRENDS/DISRUPTIONS IMPACTING BUYER/CLIENTS OF GENERATIVE AI CYBERSECURITY MARKET
           5.19. KEY STAKEHOLDERS AND BUYING CRITERIA
                    5.19.1. KEY STAKEHOLDERS IN BUYING PROCESS
                    5.19.2. BUYING CRITERIA
 
6 GENERATIVE AI CYBERSECURITY MARKET, BY OFFERING 
    6.1. INTRODUCTION 
           6.1.1. OFFERING: GENERATIVE AI CYBERSECURITY MARKET DRIVERS
    6.2. SOFTWARE 
           6.2.1. THREAT DETECTION & RESPONSE SOFTWARE
                    6.2.1.1. ADVERSARIAL MACHINE LEARNING TOOLS
                    6.2.1.2. THREAT ACTOR SIMULATION TOOLS
                    6.2.1.3. THREAT INTELLIGENCE DATA ANALYSIS TOOLSOTHERS
                    6.2.1.4. REAL-TIME THREAT DETECTION TOOLS
                    6.2.1.5. OTHERS
           6.2.2. PHISHING & MALWARE DETECTION SOFTWARE
                    6.2.2.1. PHISHING SIMULATION TOOLS
                    6.2.2.2. PHISHING BEHAVIORAL ANALYSIS TOOLS
                    6.2.2.3. MALWARE SIGNATURE GENERATION TOOLS
                    6.2.2.4. SANDBOX ANALYSIS TOOLS
                    6.2.2.5. ADVERSARIAL MALWARE DETECTION TOOLS
                    6.2.2.6. OTHERS
           6.2.3. IDENTITY AND ACCESS MANAGEMENT (IAM)
                    6.2.3.1. IDENTITY GOVERNANCE AND ADMINISTRATION (IGA) TOOLS
                    6.2.3.2. SINGLE SIGN-ON (SSO) TOOLS
                    6.2.3.3. MULTI-FACTOR AUTHENTICATION (MFA) TOOLS
                    6.2.3.4. PRIVILEGED ACCESS MANAGEMENT (PAM) TOOLS
                    6.2.3.5. ACCESS POLICY ENFORCEMENT TOOLS
                    6.2.3.6. OTHERS
           6.2.4. DATA LOSS PREVENTION (DLP)
                    6.2.4.1. CONTENT DISCOVERY AND CLASSIFICATION TOOLS
                    6.2.4.2. ENDPOINT DLP TOOLS
                    6.2.4.3. NETWORK DLP TOOLS
                    6.2.4.4. CLOUD-BASED DLP TOOLS
                    6.2.4.5. DATA TOKENIZATION TOOLS
                    6.2.4.6. ENCRYPTION & DATA MASKING TOOLS
                    6.2.4.7. OTHERS
           6.2.5. OTHER SOFTWARE
    6.3. HARDWARE 
           6.3.1. GRAPHICS PROCESSING UNIT (GPUs)
           6.3.2. TENSOR PROCESSING UNITS (TPUs)
           6.3.3. APPLICATION-SPECIFIC INTEGRATED CIRCUITS (ASICs)
           6.3.4. FIELD-PROGRAMMABLE GATE ARRAYS (FPGAs)
           6.3.5. OTHER HARDWARE
    6.4. SERVICES 
           6.4.1. PROFESSIONAL SERVICES
                    6.4.1.1. TRAINING & CONSULTING SERVICES
                    6.4.1.2. SYSTEM INTEGRATION & IMPLEMENTATION SERVICES
                    6.4.1.3. SUPPORT & MAINTENANCE SERVICES
           6.4.2. MANAGED SERVICES
 
7 GENERATIVE AI CYBERSECURITY MARKET, BY SECURITY TYPE 
    7.1. INTRODUCTION 
           7.1.1. TECHNOLOGY: GENERATIVE AI CYBERSECURITY MARKET DRIVERS
    7.2. NETWORK SECURITY 
           7.2.1. THREAT DETECTION
           7.2.2. ADVERSARIAL DEFENSE
           7.2.3. NETWORK TRAFFIC ANALYSIS
           7.2.4. INTRUSION PREVENTION SYSTEMS
           7.2.5. DNS SECURITY
           7.2.6. OTHERS
    7.3. ENDPOINT SECURITY 
           7.3.1. ANOMALY DETECTION ON ENDPOINTS
           7.3.2. MALWARE DETECTION
           7.3.3. ENDPOINT BEHAVIOR ANALYSIS
           7.3.4. MEMORY-BASED THREAT DETECTION
           7.3.5. FILE ANOMALY DETECTION
           7.3.6. OTHERS
    7.4. CLOUD SECURITY 
           7.4.1. CONTAINER SECURITY
           7.4.2. CLOUD ENVIRONMENT THREAT INTELLIGENCE
           7.4.3. SERVERLESS SECURITY
           7.4.4. CLOUD WORKLOAD PROTECTION PLATFORMS (CWPP)
           7.4.5. OTHERS
    7.5. APPLICATION SECURITY 
           7.5.1. ADVERSARIAL TESTING
           7.5.2. APPLICATION-LEVEL THREAT MODELING
           7.5.3. SECURE SOFTWARE DEVELOPMENT
           7.5.4. API SECURITY
           7.5.5. OTHERS
    7.6. OTHER SECURITY TYPES 
 
8 GENERATIVE AI CYBERSECURITY MARKET, BY VERTICAL 
    8.1. INTRODUCTION 
           8.1.1. VERTICAL: MARKET DRIVERS
    8.2. BFSI 
    8.3. IT & ITeS 
    8.4. HEALTHCARE & LIFE SCIENCES 
    8.5. RETAIL & E-COMMERCE 
    8.6. MANUFACTURING 
    8.7. TELECOMMUNICATIONS 
    8.8. ENERGY & UTILITIES 
    8.9. MEDIA & ENTERTAINMENT 
    8.10. TRANSPORTATION & LOGISTICS
    8.11. OTHER VERTICALS  
 
9 GENERATIVE AI CYBERSECURITY MARKET, BY REGION 
    9.1. INTRODUCTION 
    9.2. NORTH AMERICA 
           9.2.1. NORTH AMERICA: GENERATIVE AI CYBERSECURITY MARKET DRIVERS
           9.2.2. NORTH AMERICA: IMPACT OF RECESSION
           9.2.3. UNITED STATES
           9.2.4. CANADA
    9.3. EUROPE 
           9.3.1. EUROPE: GENERATIVE AI CYBERSECURITY MARKET DRIVERS
           9.3.2. EUROPE: IMPACT OF RECESSION
           9.3.3. UK
           9.3.4. GERMANY
           9.3.5. FRANCE
           9.3.6. ITALY
           9.3.7. SPAIN
           9.3.8. NETHERLANDS
           9.3.9. REST OF EUROPE
    9.4. ASIA PACIFIC 
           9.4.1. ASIA PACIFIC: GENERATIVE AI CYBERSECURITY MARKET DRIVERS
           9.4.2. ASIA PACIFIC: IMPACT OF RECESSION
           9.4.3. CHINA
           9.4.4. INDIA
           9.4.5. JAPAN
           9.4.6. SOUTH KOREA
           9.4.7. SINGAPORE
           9.4.8. AUSTRALIA & NEW ZEALAND
           9.4.9. REST OF ASIA PACIFIC
    9.5. MDDLE EAST AND AFRICA 
           9.5.1. MDDLE EAST AND AFRICA: GENERATIVE AI CYBERSECURITY MARKET DRIVERS
           9.5.2. MDDLE EAST AND AFRICA: IMPACT OF RECESSION
           9.5.3. GCC
           9.5.4. SOUTH AFRICA
           9.5.5. EGYPT
           9.5.6. TURKEY
           9.5.7. REST OF MDDLE EAST AND AFRICA
    9.6. LATIN AMERICA 
           9.6.1. LATIN AMERICA: GENERATIVE AI CYBERSECURITY MARKET DRIVERS
           9.6.2. LATIN AMERICA: IMPACT OF RECESSION
           9.6.3. BRAZIL
           9.6.4. MEXICO
           9.6.5. ARGENTINA
           9.6.6. REST OF LATIN AMERICA
 
10 COMPETITIVE LANDSCAPE 
     10.1. OVERVIEW 
     10.2. STRATEGIES ADOPTED BY KEY PLAYERS 
     10.3. BUSINESS SEGMENT REVENUE ANALYSIS 
               10.3.1. BUSINESS SEGMENT REVENUE ANALYSIS
     10.4. MARKET SHARE ANALYSIS 
     10.5. BRAND/PRODUCT COMPARATIVE ANALYSIS 
     10.6. COMPANY EVALUATION MATRIX, 2023 
               10.6.1. STARS
               10.6.2. EMERGING LEADERS
               10.6.3. PERVASIVE PLAYERS
               10.6.4. PARTICIPANTS
               10.6.5. COMPANY FOOTPRINT
     10.7. START-UP/SME EVALUATION MATRIX, 2023 
               10.7.1. PROGRESSIVE COMPANIES
               10.7.2. RESPONSIVE COMPANIES
               10.7.3. DYNAMIC COMPANIES
               10.7.4. STARTING BLOCKS
               10.7.5. COMPETITIVE BENCHMARKING
     10.8. VALUATION AND FINANCIAL METRICS OF KEY GENERATIVE AI CYBERSECURITY VENDORS 
     10.9. COMPETITIVE SCENARIO AND TRENDS 
               10.9.1. PRODUCT LAUNCHES AND ENHANCEMENTS
               10.9.2. DEALS
               10.9.3. OTHERS
 
11 COMPANY PROFILES 
     11.1. INTRODUCTION 
     11.2. KEY PLAYERS 
               11.2.1. SENTINELONE 
               11.2.2. CISCO
               11.2.3. TREND MICRO
               11.2.4. NVIDIA
               11.2.5. INTEL
               11.2.6. AMD
               11.2.7. GOOGLE
               11.2.8. VERACODE
               11.2.9. SECURITYSCOREGUARD
               11.2.10. QUALCOMM
               11.2.11. MICROSOFT 
               11.2.12. ZSCALER
               11.2.13. XENONSTACK 
     11.3. OTHER PLAYERS 
               11.3.1. SYNK LTD.
               11.3.2. SPLUNK
               11.3.3. CROWDSTRIKE
               11.3.4. CHECKMARX
               11.3.5. ELASTIC NV
               11.3.6. TENABLE
               11.3.7. RECORDED FUTURE AI 
               11.3.8. TALON
               11.3.9. BIGID
               11.3.10. FLASHPOINT 
               11.3.11. GRAPHCORE
               11.3.12. SLASHNEXT
               11.3.13. GITHUB
 

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