Generative AI Cybersecurity Research Report 2025-2030: $35.5 Bn Market to Grow Rapidly, Driven by Rising AI Supply Chain Attacks, Secure Model Execution Demand, Expansion of Model-as-a-Service - GlobeNewswire

Dublin, Nov. 04, 2025 (GLOBE NEWSWIRE) -- The "Generative AI Cybersecurity Market by Generative AI-based Cybersecurity (SIEM, Risk Assessment, Threat Intelligence), Cybersecurity Software for Generative AI (AI Model Security), Security Type (Data Encryption, Access Control) - Global Forecast to 2031" report has been added to ResearchAndMarkets.com's offering. The generative AI cybersecurity market is anticipated to witness a compound annual growth rate (CAGR) of 26.5% over the forecast period, reaching USD 35.50 billion by 2031 from an estimated USD 8.65 billion in 2025. The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall generative AI cybersecurity market and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the market's pulse and provides information on key market drivers, restraints, challenges, and opportunities. The market is driven by the rise in AI supply chain attacks targeting third-party model repositories, APIs, and plugins, which is pushing enterprises to adopt model provenance verification and code signing to secure AI assets. Additionally, the growing use of model-as-a-service in multi-tenant cloud environments is increasing demand for confidential computing and secure enclave execution to protect sensitive AI workloads. However, the market also faces a significant restraint as malicious actors exploit generative AI to automate phishing campaigns, create deepfakes, and develop advanced malware. This dual-use challenge forces vendors to continually evolve defensive strategies to stay ahead of adversarial AI threats while balancing innovation and security. Risk assessment software leads growth, driving proactive threat mitigation Risk assessment software within the generative AI cybersecurity ecosystem is projected to record the highest CAGR over the forecast period, fueled by its critical role in proactive threat prevention and compliance-driven decision-making. Generative AI enhances traditional risk assessment by simulating complex attack scenarios, predicting cascading impacts across interconnected systems, and identifying latent vulnerabilities that conventional tools may overlook. The technology enables continuous, adaptive scoring of cyber risks based on real-time telemetry, threat intelligence feeds, and contextual business impact, allowing enterprises to prioritize remediation efforts with precision. Industries with stringent compliance frameworks, such as BFSI, healthcare, and critical infrastructure, are accelerating adoption to meet evolving regulatory expectations like the US SEC's cyber incident disclosure rules and the EU Digital Operational Resilience Act (DORA). Moreover, AI-driven risk assessment platforms are being integrated with Security Orchestration, Automation, and Response (SOAR) systems to automate policy enforcement and reduce decision latency during incidents. By leveraging generative models to evaluate risks in dynamic environments, vendors can offer predictive insights that materially improve security posture and operational resilience. The combination of regulatory pressure, operational efficiency gains, and the ability to quantify and communicate cyber risk in business terms positions this software segment for sustained high-growth momentum. Static application security testing to hold largest market as AI-centric code security becomes mission-critical Static Application Security Testing (SAST) is estimated to capture the largest market share within application security types in 2025, driven by its critical role in securing AI-integrated software development pipelines and ensuring code integrity before deployment. The increasing adoption of secure-by-design principles in enterprise AI initiatives has elevated SAST from a compliance-focused measure to a strategic necessity, especially as regulatory bodies tighten oversight on AI-enabled applications handling sensitive data. Unlike dynamic testing, SAST enables early detection of vulnerabilities at the source code level, significantly reducing remediation costs and minimizing the risk of exploited flaws reaching production environments. In sectors such as BFSI, healthcare, and government, where AI applications process high-value and regulated data, SAST adoption is accelerating in parallel with generative AI deployments, ensuring robust protection against injection attacks, insecure dependencies, and code-level data leaks. Moreover, the growing integration of AI coding assistants and automated DevSecOps pipelines is expanding the demand for SAST tools capable of handling AI-generated code, addressing unique vulnerabilities introduced by large language model-assisted programming. Leading security vendors are embedding AI-driven analytics into SAST platforms to improve vulnerability prioritization and reduce false positives, further enhancing operational efficiency and developer adoption. These combined factors position SAST as the dominant force in the 2025 application security landscape. Asia Pacific to witness rapid market growth fueled by innovation and emerging technologies, while North America leads in market size North America is estimated to account for the largest share of the generative AI cybersecurity market in 2025, underpinned by its mature technology ecosystem, strong enterprise adoption rates, and early regulatory engagement in AI governance. The region benefits from the presence of leading cybersecurity vendors, robust venture capital activity, and a concentration of high-value industries such as BFSI, healthcare, and defense, where AI-driven security solutions are rapidly embedded into operational frameworks. Government-backed initiatives, such as the US Executive Order on AI and sector-specific compliance mandates, are accelerating investment in advanced AI threat detection, incident response automation, and AI-assisted risk assessment platforms. In parallel, Asia Pacific is poised to record the fastest CAGR during the forecast period, driven by rapid digital transformation, large-scale cloud adoption, and a growing need to counter evolving cyber threats targeting expanding digital infrastructures. Countries such as China, India, Japan, and South Korea are investing heavily in AI R&D, supported by government programs and strategic public-private partnerships. The region's expanding base of SMEs and startups is leveraging generative AI for both offensive and defensive cybersecurity innovation, while hyperscale cloud providers are localizing AI security services to address diverse compliance environments. This combination of high-growth adoption patterns in the Asia Pacific and entrenched market dominance in North America is shaping a dual-center growth model for the global generative AI cybersecurity landscape. The report provides insights on the following pointers: Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the generative AI cybersecurity market. Market Development: Comprehensive information about lucrative markets - the report analyses the generative AI cybersecurity market across varied regions. Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the generative AI cybersecurity market. Competitive Assessment: In-depth assessment of market shares, growth strategies, and offerings of leading players. Key Attributes: Report Attribute Details No. of Pages 509 Forecast Period 2025 - 2031 Estimated Market Value in 2025 8.65 billion Forecasted Market Value by 2031 35.5 billion Compound Annual Growth Rate 26.5% Regions Covered Global Market Dynamics Drivers Rising Frequency and Sophistication of AI-Driven Cyberattacks Operational Efficiency Gains Through AI-Assisted Security Operations Centers (AI-Soc), Reducing Alert Fatigue and Response Times Escalating Zero-Day Vulnerabilities, Necessitating Rapid AI-Enabled Detection and Remediation Growing Demand for AI-Powered Behavioral Anomaly Detection to Combat Insider Threats Restraints Lack of Standardized Benchmarks for Evaluation of AI Cybersecurity Solutions Uncertainty Around Liability in AI-Led Automated Security Actions Opportunities Adoption of Zero Trust for AI Frameworks to Validate AI-Generated Outputs Leveraging AI for Real-Time Detection of Adversarial AI Attacks on Critical Infrastructure Development of AI-Driven Penetration Testing and Vulnerability Assessment Platforms Challenges Exploitation of Prompt Injection and Model Manipulation Techniques to Bypass Safeguards Proliferation of AI-Enabled Deepfake Fraud Targeting Enterprises and Critical Infrastructure Ecosystem Analysis Generative AI-Based Cybersecurity Providers Cybersecurity Providers for Generative AI Generative AI Cybersecurity Service Providers Security Types Case Study Analysis Zerofox Provides Actionable Intelligence to Shore Up Simply Business'S Information Security Pomelo Stays Secure Amidst Rapid Growth With Snyk Evocabank Helps Nokia Protect Millions of Followers Carnival Corporation Charts a Safer Course With Cyberark IBM Uses Palo Alto to Protects Its AI Systems Openai Uses Okta to Safeguard Itself Technology Analysis Key Technologies Adversarial Machine Learning Federated Learning Security Differential Privacy Homomorphic Encryption Secure Multi-Party Computation Complementary Technologies Blockchain Zero Trust Architecture Endpoint Detection & Response Vulnerability Management Adjacent Technologies Quantum Computing Devsecops Forensics & Incident Response Big Data Analytics Regulatory Landscape North America Executive Order on AI (US) Nist AI Risk Management Framework (Under the Ndaa) National AI Risk Management Framework Artificial Intelligence and Data Act (Aida) Kids Online Safety Act (Kosa) Canadian Centre for Cyber Security Privacy Guidelines Europe Regulation (Eu) 2024/1689 - Artificial Intelligence Act (AI Act) Directive (Eu) 2022/2555 - Nis 2 Directive Regulation (Eu) 2024/2847 - Cyber Resilience Act (CRA) Regulation (Eu) 2024/903 - Cyber Solidarity Act (CSA) Asia-Pacific Model AI Governance Framework (Singapore) AI Guidelines for Business Version 1.0 (Japan) Basic Law for Promoting Responsible AI (Japan, Proposed) Act on Promotion of the AI Industry and Framework for Establishing Trustworthy AI (South Korea) Middle East & Africa Uae Strategy for Artificial Intelligence 2031 National AI Programme African Union Convention on Cyber Security and Personal Data Protection (Malabo Convention) National Strategy for Data and AI (Nsdai) Saudi Data and Artificial Intelligence Authority (Sdaia) Latin America Bill No. 2,338/2023 - Proposed Law on Artificial Intelligence (Brazil) National Artificial Intelligence Strategy (Ebia) (Brazil) National Policy on Exploitation of Data (Big Data) (Colombia) AI Regulation Bill (Colombia) Companies Featured Microsoft IBM Google Sentinelone Nvidia Neuraltrust Trend Micro Blackberry Okta Sangfor Technologies Veracode Lexisnexis Securityscorecard Broadcom Cohesity Elastic Nv Cybereason Flashpoint Mostly AI Recorded Future Secureframe Slashnext Virustotal Xenonstack Zerofox Aws Cisco Crowdstrike Fortinet Zscaler Palo Alto Networks Darktrace F5 Sophos Trellix Tenable Snyk Abnormal Security Adversa AI Aqua Security Bigid Checkmarx Credo AI Deepkeep Lakera Skyflow Trojai For more information about this report visit https://www.researchandmarkets.com/r/4i8oga About ResearchAndMarkets.com ResearchAndMarkets.com is the world's leading source for international market research reports and market data. 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