Top Generative AI Cybersecurity Companies

The generative AI cybersecurity market is anticipated to register 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. One of the most prominent drivers of the generative AI cybersecurity market is the rapid expansion of investments in AI-powered anomaly detection, threat hunting, and incident response systems, enabling real-time detection and neutralization of advanced threats. These capabilities are becoming critical as cyberattacks increasingly leverage AI to evade traditional defenses, with reports from the FBI’s Internet Crime Complaint Center showing a rise in AI-assisted phishing and business email compromise schemes. Another key driver is the surge in high-value cyberattacks targeting AI training datasets and intellectual property, which can lead to model theft, data poisoning, and compromised inference outputs. Incidents such as model inversion attacks in research settings have demonstrated the feasibility of extracting sensitive training data from deployed AI systems. To counter these risks, organizations are investing in secure model deployment frameworks and federated learning security to protect distributed training environments without compromising data privacy. Vendors, including Palo Alto Networks, Fortinet, and Protect AI, are developing solutions that integrate model integrity verification, encrypted training pipelines, and AI-powered SOC automation, addressing these evolving threats and reinforcing enterprise trust in generative AI deployments.

To know about the assumptions considered for the study download the pdf brochure

Vendors in the generative AI cybersecurity market are increasingly pursuing two high-impact strategies to expand market share. The first is strategic acquisitions of specialized AI security firms to rapidly integrate capabilities such as prompt injection prevention, model risk assessment, and AI-specific threat detection into their platforms, enabling faster innovation and competitive differentiation. The second is partnerships with cloud and AI infrastructure leaders to embed generative AI cybersecurity directly into widely used development, deployment, and compute environments, ensuring scalability and broad market reach. These approaches allow vendors to strengthen their technology portfolios while leveraging established partner ecosystems to accelerate adoption.

Palo Alto Networks acquired Protect AI (July 2025) to enhance AI model security and SOC integration.

Accenture partnered with Microsoft (July 2025) to co-develop generative AI-powered cybersecurity solutions and modernize SOC operations.

Google

Google plays a significant role in the generative AI cybersecurity market through its deep integration of AI model security and threat detection into its cloud and AI services. Leveraging its Vertex AI platform and Google Cloud Security Suite, the company focuses on embedding safeguards across the AI lifecycle, including data encryption, secure model deployment, adversarial testing, and continuous monitoring. Google has been advancing AI-powered anomaly detection and content moderation tools to mitigate risks like prompt injection, model inversion, and data leakage in generative AI applications. Its partnerships with enterprise customers emphasize secure adoption of large language models and retrieval-augmented generation (RAG) workflows, particularly in regulated industries such as finance and healthcare. Google is also aligning with global AI governance standards, contributing to frameworks like the NIST AI RMF, and embedding compliance tools into its offerings. A key strategy has been expanding confidential computing and AI-specific policy enforcement at the application layer, ensuring that generative AI capabilities deployed on Google Cloud are protected against both external and internal threats. By combining its expertise in AI infrastructure, cybersecurity, and compliance automation, Google is positioning itself as a trusted platform provider for enterprises scaling secure generative AI solutions.

AWS

Amazon Web Services (AWS) is a leading enabler of secure generative AI deployments, providing both infrastructure and application-level safeguards through services such as Amazon Bedrock, SageMaker, and AWS Security Hub. AWS’s role in the generative AI cybersecurity market centers on integrating robust security frameworks into AI model development and deployment, with features like encrypted data pipelines, access control via IAM, and AI model governance. The company is actively investing in threat detection technologies that leverage generative AI for anomaly detection, incident triage, and real-time alerting. AWS’s strategy includes enabling customers to protect training datasets and proprietary models from risks like data poisoning, unauthorized access, and model exfiltration by offering federated learning security and confidential computing. AWS collaborates with partners and independent software vendors to deliver AI-specific security controls, particularly for enterprises in high-compliance sectors such as healthcare, government, and BFSI. The company’s shared responsibility model extends to AI workloads, ensuring customers have tools to maintain compliance with regulations like HIPAA, GDPR, and the EU AI Act. By integrating generative AI security capabilities into its scalable cloud ecosystem, AWS empowers organizations to innovate with AI while mitigating risks at scale.

Market Ranking

Palo Alto Networks, Google, CrowdStrike, AWS, and Fortinet have emerged as key players in the generative AI cybersecurity market by combining advanced technology integration with targeted go-to-market strategies. These companies are leveraging a mix of in-house innovation, strategic acquisitions, and ecosystem partnerships to deliver comprehensive security across the AI lifecycle, from data protection and model integrity to real-time threat detection and incident response. Palo Alto Networks and CrowdStrike have focused on embedding generative AI-driven anomaly detection, SOC automation, and adversarial attack prevention into their platforms, enabling faster and more accurate threat mitigation. Google and AWS have integrated AI-specific security capabilities into their cloud ecosystems, offering secure model deployment, confidential computing, and compliance automation for enterprise AI workloads. Fortinet has expanded its FortiAI portfolio to include generative AI-powered threat detection and application-layer safeguards, addressing risks such as prompt injection and data leakage. Collectively, these vendors have capitalized on rising enterprise adoption of generative AI, regulatory pressures for model security, and the need for scalable, application-focused defenses, positioning themselves as trusted providers of end-to-end generative AI cybersecurity solutions.

Related Reports:

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

Contact:
Mr. Rohan Salgarkar
MarketsandMarkets Inc.
1615 South Congress Ave.
Suite 103,
Delray Beach, FL 33445
USA : 1-888-600-6441
sales@marketsandmarkets.com