Generative AI Cybersecurity Market Overview
According to MarketsandMarkets™, the global Generative AI Cybersecurity Market Size is projected to grow from USD 8.65 billion in 2025 to USD 35.50 billion by 2031, registering a strong CAGR of 26.5% during the forecast period.
The accelerating adoption of AI models, large language models (LLMs), and AI-driven automation across enterprises is transforming cybersecurity priorities. As organizations embed AI into core operations such as customer engagement, decision support, and workflow automation, their digital environments become more interconnected and complex. This expansion increases the attack surface, exposing AI systems, training data, and inference pipelines to threats including adversarial attacks, data poisoning, model theft, and prompt injection.
Industries managing sensitive information—such as BFSI, healthcare, and government—face heightened risk, as compromised AI systems can trigger major operational, regulatory, and reputational damage. In response, cybersecurity vendors are increasingly converging AI innovation with security platforms. Generative AI enhances threat detection and response through real-time anomaly identification, automated investigation, and intelligent remediation. Leading vendors such as Palo Alto Networks, CrowdStrike, Microsoft, and SentinelOne are advancing AI-powered SOC modernization, model integrity protection, and adaptive defense strategies. By blending AI security controls with generative AI-driven defense, enterprises can better anticipate evolving cyber threats and maintain trust in AI-enabled operations.
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Generative AI Application Security Leads the Market
Among cybersecurity software tools, the generative AI application security segment is expected to capture the largest share in 2025, driven by rapid deployment of GenAI-powered applications including chatbots, copilots, document automation platforms, and recommendation engines. These applications represent the most exposed layer of AI workflows, where risks such as prompt injection, data leakage, unsafe outputs, and unauthorized tool execution directly affect users and business processes.
Regulatory initiatives such as the EU AI Act and the NIST AI Risk Management Framework emphasize transparency, monitoring, and runtime safeguards, which are largely implemented at the application level. The growing adoption of retrieval-augmented generation (RAG) further increases exposure at the interface between models and enterprise data, making guardrails, redaction, jailbreak detection, and content filtering essential. Vendors including Palo Alto Networks, SentinelOne, Fortinet, and CrowdStrike are embedding generative AI protection into their platforms to deliver policy enforcement, SOC integration, and real-time monitoring at the application edge. For regulated industries, application security is the most direct way to ensure compliance, protect data, and preserve user trust.
Network Security to Hold the Largest Share by Security Type
By security type, network security is expected to dominate the generative AI cybersecurity market in 2025, supported by the surge in cloud connectivity, data traffic, and distributed enterprise architectures. Hybrid and multi-cloud adoption continues to expand network-layer exposure, making AI-powered defenses a top priority.
Generative AI enhances intrusion detection and prevention by enabling real-time anomaly detection across encrypted traffic with minimal performance impact. These models can emulate advanced attack behaviors, uncover zero-day vulnerabilities, and dynamically update firewall and segmentation policies. The growth of remote work, edge computing, and IoT further accelerates demand for AI-enabled secure access solutions such as Zero Trust Network Access (ZTNA). Regulatory mandates including the US Federal Zero Trust Strategy and the EU NIS2 Directive are also driving proactive network defense adoption. Vendors integrating generative AI into monitoring, segmentation, and automated response are achieving faster breach containment and lower false-positive rates, reinforcing network security as the foundation of AI cybersecurity strategies.
North America to Lead by Market Value
North America is projected to account for the largest share of the generative AI cybersecurity market in 2025, fueled by early and widespread adoption of generative AI across BFSI, healthcare, defense, and technology sectors. The region hosts many leading vendors—such as Microsoft, IBM, CrowdStrike, Palo Alto Networks, and SentinelOne—that are embedding generative AI capabilities into enterprise security platforms.
Policy momentum, including the White House Executive Order on Safe, Secure, and Trustworthy AI and NIST’s AI Risk Management Framework, is encouraging investment in adversarial defense, secure model deployment, and AI-driven response automation. Compliance requirements in US healthcare (HIPAA) and Canadian data protection laws further stimulate adoption of application-layer safeguards, runtime monitoring, and model governance. Combined with strong venture funding and enterprise AI budgets, North America provides a mature ecosystem for scaling generative AI cybersecurity solutions, positioning the region as the market leader.
Competitive Landscape
The generative AI cybersecurity market features major players with global reach, including Microsoft, IBM, Google, SentinelOne, AWS, NVIDIA, Cisco, CrowdStrike, Fortinet, Zscaler, Trend Micro, Palo Alto Networks, BlackBerry, Darktrace, F5, Okta, Sangfor, SecurityScorecard, Sophos, Broadcom, Trellix, Veracode, LexisNexis, Abnormal Security, Adversa AI, AquaSec, BigID, Checkmarx, Cohesity, Credo AI, NeuralTrust, Cybereason, DeepKeep, Elastic, Flashpoint, Lakera, Recorded Future, Secureframe, Skyflow, SlashNext, Snyk, Tenable, TrojAI, VirusTotal, XenonStack, and ZeroFox, among others.
These vendors are focusing on AI model protection, application-layer security, automated threat intelligence, and SOC modernization to help enterprises defend against the rapidly evolving AI threat landscape.