AI Agent Security Market Size, Share, Trends and Forecast, 2026–2034
REPORT DETAILS
AI Agent Security Market Summary
The global AI agent security market was valued at USD 18.57 billion in 2025 and is projected to register a CAGR of 39.49% from 2026 to 2034. The market is growing as organizations implement autonomous AI agents in their business processes, data centers, and digital processes. The increasing usage of agents is creating greater demand for AI agent identity security management, access control systems, runtime protection, threat detection, and governance products to address the risks associated with autonomous agent usage.
Market Statistics
Key Takeaways
- North America led the AI agent security market share with 39.18% in 2025. The leading position is attributed to strong activity across agent identity, access management, governance, and security.
- The Asia Pacific market is expected to register a CAGR of 44.28% during the forecast period. Increasing introduction of AI agents and rising need for better identity, authorization, and runtime controls boost the regional AI agent security market growth.
- The agent identity & access security segment dominated with 24.36% revenue share in 2025. AI agents need controlled identities, authentication, authorization, permissions, and lifecycle management before safe operations. This factor drives the demand for AI agent identity and access management.
- In 2025, cloud deployment held the largest market share of 61.36% due to rising adoption of cloud-based applications, identity platforms, APIs, and AI services.
- IT and telecommunications held the largest share of 25.84% in 2025, owing to its extensive exposure to cloud applications, software development, identity systems, APIs, and AI infrastructure.
- Single agent-based systems led with 36.48% share in 2025, driven by their simplistic structure and greater early adoption for task completion within an organization.
Note: Figures and projections outlined in this report are the result of Polaris Market Research’s proprietary analytical processes, grounded in the latest available datasets and market observations.
AI Agent Security Market Definition
AI agent security market develops and commercializes technologies and services that facilitate the security of AI agents, particularly concerning their identity, permissions, tools, data interaction, behavior, and governance. It differentiates itself from AI cybersecurity, which includes the application of artificial intelligence in securing the network, endpoints, applications, and other digital resources. AI agent security focuses on controlling what an autonomous agent is, what it can access, what actions it can perform, and how those actions can be monitored.
The market includes agent identity and access security, agent runtime security, agent governance and compliance, agent data security, and agent threat detection and response. The need for these capabilities is increasing as AI agents move from conversational use toward workflows in which they can access enterprise applications and perform actions on behalf of users.
Enterprise security vendors are responding through product development, providing capabilities for agent discovery, lifecycle governance, access reviews, and control. In March 2026, Ping Identity announced the general availability of Identity for AI. It will help enterprises with continuous, contextual enforcement and real-time control over AI agents (Source: press.pingidentity.com).
The investment environment is contributing to the growth in the number of business transactions within this field. This was evidenced in August 2026 when Obsidian Security raised USD 85 million in Series D capitalization with a valuation of USD 1.1 billion for strengthening AI agent security (Source: obsidiansecurity.com). Also, GitGuardian raised USD 50 million in Series C capitalization in February 2026 to strengthen AI agent and non-human identity security (Source: blog.gitguardian.com).
The market is consequently moving toward a broader identity-security architecture. In this, AI agents are treated as managed digital identities rather than simply extensions of existing applications. This shift creates demand for lifecycle management, least-privilege access, runtime controls, auditability, and policy enforcement. The factors boost the global AI agent security market value.
AI Agent Security Market Dynamics
Driver: Expansion of Non-Human Identities
AI agents require identities and permissions when they access enterprise applications or perform actions on behalf of users. This changes the security problem from protecting only human accounts to managing a larger population of software-driven identities. Astrix Security found that nearly 1 in 5 organizations experienced an NHI-related security incident, while 69% view NHIs as an attack vector. Only 19% automate API key offboarding, 38% lack visibility into OAuth-connected vendors, and 25% are investing in non-human identity governance (Source: astrix.security).
The commercial implication is a growing requirement for identity controls that can apply continuously to agents. Ping Identity has similarly extended its identity architecture into agentic systems, including least-privilege access, centralized policy enforcement, auditability, and accountability.
Driver: NIST Standards Activity
The NIST AI Agent Standards Initiative of February 2026 offers an institutional motivation. The initiative is designed to advance secure and interoperable AI agents, while its associated NCCoE work examines practical identity and authorization standards for enterprise deployments. This activity gives enterprises and vendors a clearer direction for security architecture. The NCCoE concept paper specifically considers identification, authorization, auditing, and non-repudiation, making identity governance a central part of the emerging security framework.
Driver: Regulatory Requirements
The EU AI Act is creating a further reason for organizations to document and control AI systems. Regulation 2026/1744 revised certain implementation timelines under the AI Act while maintaining separate obligations for transparency. The differentiated timeline requires organizations to monitor regulatory requirements rather than treating AI compliance as a single deadline.
Restraint: Incomplete Standard Development
NIST's AI agent identity work remains part of a standards and demonstration process rather than a universally adopted technical standard. The February 2026 NCCoE document was published as a draft concept paper intended to gather input on applying identity standards to AI agents. This creates an issue of time for corporations because they need to develop the controls today when the standards, protocols, and designs of products are still evolving.
Restraint: Fragmented Identity Architecture
AI agents can interact with identity providers, applications, tools, APIs, and other agents. Okta's architectural design for its product portfolio includes agent lifecycle management and an Agent Gateway, whereas Ping Identity is working on runtime identity management capabilities and MCP-related controls.
Different approaches can increase integration requirements for organizations that operate multiple agent platforms. The market therefore requires security products capable of connecting existing identity infrastructure with emerging agent architectures.
Challenge: Limited Visibility into Agent Activity
AI agents create a governance problem when organizations do not have sufficient visibility into what agents exist, which permissions they hold, and which resources they access. Okta's product positioning focuses on answering where agents are, what they can connect to, and what they can do. The implication is that inventory, identity discovery, access reviews, and audit trails are becoming foundational requirements rather than optional security functions.
Opportunity: M&A and Platform Consolidation
Investment activity is creating opportunities for specialist vendors while larger security and identity companies expand their agent capabilities. In July 2026, Okta reached an agreement to purchase Permiso Security in order to enhance the security of AI agents by means of behavioral analytics, threat detection, and monitoring of anomalous agent behavior and tool usage (Source: finance.yahoo.com). Moreover, in July 2026, Cyera made the announcement of the purchase of Oasis Security in order to integrate data and identity security and offer enterprises unified control over AI agents (Source: oasis.security).
The pattern suggests that identity, data security, and agent governance are increasingly converging. Specialist vendors can therefore become acquisition targets when they provide capabilities that established platforms do not yet offer natively.
Opportunity: MCP Security
The Model Context Protocol is becoming relevant to AI-agent connectivity. Okta's AI-agent architecture includes an Agent Gateway and MCP-related capabilities, while Ping Identity has introduced an MCP server and describes security functions including OAuth validation, auditing, rate limiting, and policy enforcement for MCP environments. This creates opportunities for security controls that operate at the connection between agents and tools. Authentication, authorization, monitoring, and policy enforcement can become distinct product functions within MCP-enabled environments.
Opportunity: Managed Agent Security
Smaller enterprises may not have the identity engineering resources required to establish agent governance internally. This creates space for managed services that combine agent discovery, identity governance, access reviews, runtime controls, and security monitoring.
AI Agent Security Market Segmentation Analysis
The report provides a comprehensive analysis of the AI agent security market by security capability, deployment, organization size, end use, offering, agent type, and region to identify the leading revenue-generating segments and emerging growth opportunities.
Security Capability Insights
Agent identity & access security represented the largest AI agent security market share of 24.36% in 2025. This is because AI agents require controlled identities, authentication, authorization, permissions, and lifecycle management before they can safely operate across enterprise environments. Okta and Ping Identity have both launched dedicated capabilities around AI-agent identity and access governance, providing direct evidence of commercial activity in the AI agent identity and access security segment.
Agent runtime security is expected to record the highest CAGR of 40.18% during the forecast period. The AI agent runtime protection market has strong expansion potential because agent behavior occurs after identity has been established. In August 2026, Zenity Labs introduced AI Total, a free threat intelligence service. It uses dynamic testing of AI agent skill sets to detect any malicious behavior, including malware detection, data stealing, and unauthorized operations (Source: zenity.io).
The commercial opportunity extends beyond authentication. Security providers will need to monitor tool calls, enforce policies, restrict permissions, and identify abnormal actions during execution.
Comparison Matrix by Security Capability
| Security Capability | Market Position | Commercial Importance |
| Agent Identity & Access Security | Leading area of vendor activity | Identity, authorization, and lifecycle governance |
| Agent Runtime Security | Expanding | Protection during agent execution |
| Agent Governance & Compliance | Expanding | Policy, audit, and oversight |
| Agent Data Security | Expanding | Protection of data and secrets |
| Agent Threat Detection & Response | Emerging | Detection of malicious or abnormal agent behavior |
Source: Polaris Market Research Analysis
Deployment Insights
In AI agent security market by deployment, the cloud deployment segment held the largest market share of 61.36% in 2025. Cloud AI agent security remains a major deployment model because many AI agents operate through cloud-based applications, identity platforms, APIs, and AI services. Vendor products introduced in 2026 are increasingly designed to connect identity controls with agent platforms and cloud environments.
The hybrid deployment segment is expected to record the highest CAGR of 43.48% during the forecast period. The segment has a strong opportunity where enterprises cannot move every application or sensitive workload to cloud environments. The main requirement is consistent identity and authorization across different infrastructure environments.
Cloud vs. On-Premises vs. Hybrid Deployment
| Deployment | Position | Key Requirement |
| Cloud | Leading | Centralized agent identity and runtime controls |
| Hybrid | Expanding | Cross-environment identity and policy enforcement |
| On-premises | Specialized | Local control and enterprise integration |
Source: Polaris Market Research Analysis
Organization Size Insights
In AI agent security by organization size, in 2025, large enterprises represented the leading share of 68.42%. Large enterprise AI agent security dominated because they typically operate complex application environments in which AI agents can interact with multiple systems. Okta positions its platform around centralized discovery, governance, and access control for enterprise AI agents. Large enterprises also have increased needs for auditing and policy enforcement. Therefore, identity governance is an extension of enterprise security solutions.
The SMEs segment is expected to record the highest CAGR of 43.42% during the projected period. SMEs have an opportunity to expand through managed AI agent security services. Many smaller organizations may prefer externally managed identity, monitoring, and governance capabilities rather than building dedicated agent-security teams.
Large Enterprises Vs SMEs
| Organization Size | Position | Key Requirement |
| Large Enterprises | Leading | Centralized governance and identity controls |
| SMEs | Emerging | Managed security and simplified deployment |
Source: Polaris Market Research Analysis
End Use Insights
In the AI agent security market by end use, IT and telecommunications dominated with 25.84% share in 2025. The IT and telecom AI agent security segment represented a strong end-use area because the sector has extensive exposure to cloud applications, software development, APIs, identity systems, and AI infrastructure. The number of technology vendors developing agent identity and runtime capabilities also creates a direct ecosystem for this sector.
The BFSI segment is projected to exhibit the highest CAGR of 41.68% during the forecast period. The BFSI AI agent security segment has strong potential because agent deployments must operate within established security and governance frameworks. The commercial opportunity is strongest for platforms that combine identity, authorization, monitoring, and audit capabilities.
Comparison Matrix by End Use
| End Use | Market Position | Commercial Importance |
| IT & Telecommunications | Leading area of vendor activity | Agent identity and runtime protection |
| BFSI | High-potential | Authorization, governance, and auditability |
| Healthcare | Emerging | Data and access protection |
| Government | Emerging | Identity, authorization, and oversight |
| Other Industries | Developing | Application-specific controls |
Source: Polaris Market Research Analysis
Offering Insights
The software/platform segment dominated the market for AI agents security with 68.72% share in 2025. This is due to the growing need for tools that allow monitoring, controlling, and securing AI agents in the enterprise environment. The features provided by security platforms include agent monitoring, access control, threat detection, and policy enforcement.
The services segment is anticipated to witness the highest CAGR of 42.68% during the forecast period. The growing AI agent security market CAGR for this segment is driven by the rising demand for services related to consulting, implementation, integration, and managed security. Several companies require assistance from third-party firms for the integration of AI agent security in the company’s current security environment, as well as for managing emerging threats. The complexity associated with deploying agents is expected to drive the demand for managed security services.
Agent Type Insights
The single agent-based systems segment dominated with 36.48% share in 2025. The segment is leading due to its simplistic structure and greater early adoption for the completion of tasks within an organization. Individual agents can be assigned tasks without overly complicated security measures, access control, and monitoring processes being required. The real-world applications of such systems have ensured sustained demand for security measures for single agents.
The multi-agent systems segment is projected to witness the highest CAGR of 43.87% during the forecast period. This is due to the movement toward more complex AI workflows that include many specialized agents. This means that the need for communication, coordination, and information exchange between the agents in this environment. This will introduce new requirements concerning security issues such as identity, permissions, communications, and oversight. The growing use of agent orchestration layers is likely to drive the need for solutions for this environment.
AI Agent Security Market Regional Analysis
North America AI Agent Security Market Trends
North America held a leading position in the AI agent security market share, by holding 39.18%, in 2025. The dominance is driven by strong activity across agent identity, access management, governance, and security. In August 2026, Cyera introduced Agent Guardian to safeguard autonomous AI agents through constant observation of their activities and prevention of any risk behavior to prevent data access and leakage. This is helping improve the agent and non-human identity ecosystem in the region (Source: cyera.com).
In February 2026, NIST launched its AI Agent Standards Initiative through the Center for AI Standards and Innovation. Introduction of the CAISI Agent Standards Initiative has injected further momentum into the U.S. market. The program will target AI agent standards, MCP security, and identity research, thereby bringing more attention to the secure deployment of agents, propelling the US AI agent security market size (Source: nist.gov).
Europe AI Agent Security Market Trends
Europe has emerged as a significant market by accounting for 25.72% revenue share in 2025. The region market is growing owing to the AI Act of the EU and its requirement for transparency and governance of AI. In July 2026, the Digital Omnibus Regulation on artificial intelligence (Regulation (EU) 2026/1744) came into effect. It amends the EU Artificial Intelligence (AI) Act (Regulation (EU) 2024/1689). The Digital Omnibus has deferred certain high-risk obligations until 2027 and 2028 (Source: cobalt.legal).
Regulatory pressures will drive demand for controls related to agent identity, authorization, monitoring, and accountability. This opens up opportunities for providers with governance and compliance offerings for enterprise AI deployments.
Asia Pacific AI Agent Security Market Trends
The Asia Pacific market is expected to register the highest CAGR of 44.28% during the forecast period. The region is developing into a high-growth market for enterprises as they roll out more AI agents and need better identity, authorization, and runtime controls. Cloud security platforms can assist enterprises in integrating these features into their AI systems. In August 2026, Aliyun (Alibaba Cloud) introduced AgentLoop Audit, its AI agent security audit tool. The tool emphasizes distinguishing between actual risks and simple warnings during AI agent execution that handle shell commands, APIs, file systems, and external networks (Source: weex.com).
The commercial opportunity is linked to enterprise adoption of AI agents and the need to extend identity, authorization, and runtime security into these deployments. Global vendors are already developing platforms that can operate across cloud and enterprise environments, allowing organizations in Asia Pacific to adopt security controls without creating an entirely separate architecture. These factors are expected to boost the Asia Pacific AI agent security market share.
Latin America AI Agent Security Market Trends
Latin America represented a significant share of 5.36% in 2025, as organizations increase the use of AI-enabled enterprise applications. Demand is expected across identity management, access controls, and governance solutions for AI agents. The opportunity will most likely present itself in cases involving enterprise usage where there is a need for cloud-based AI apps requiring identity and access management. Centralized platform providers will make it easier for enterprises to deploy AI agent security solutions.
Middle East & Africa AI Agent Security Market Trends
The Middle East & Africa is emerging as a key market with 41.35% CAGR. In the Middle East AI agent security market, enterprises and public-sector organizations are increasing their focus on AI adoption and digital transformation. The expansion of autonomous AI applications is creating demand for secure identity, authorization, and governance capabilities.
The near-term opportunity is therefore more closely associated with enterprise adoption and the deployment of global identity and security platforms. KPMG’s UAE Tech Report 2026 found that 97% of UAE organizations use AI agents in core operations versus 87% globally, while 90% rank among the top two resilience tiers, based on a survey of 2,500 technology leaders, including 70 from the UAE (Source: kpmg.com). Regional buyers can use established technologies for agent lifecycle management, authentication, authorization, and governance without waiting for a region-specific agent-security product category to mature.
Regional AI Agent Security Market Size & CAGR Snapshot
| Region | Base Year Market share | CAGR | Key Growth Driver |
| North America | 39.18% | 37.82% | NIST agent standards activity and vendor development |
| Europe | 25.72% | 39.14% | EU AI Act compliance |
| Asia Pacific | 23.66% | 44.28% | Enterprise AI-agent deployment |
| Latin America | 5.36% | 40.16% | Insufficient verified region-specific evidence |
| Middle East & Africa | 6.08% | 41.35% | Insufficient verified region-specific evidence |
Source: Polaris Market Research Analysis.
AI Agent Security Market Regulation
Regulation has become one of the most powerful differentiation points when it comes to the AI-agent security market. On the one hand, the European Union has developed a mandatory regulatory framework, namely the AI Act. On the other hand, the U.S. approach in the field is best illustrated by the NIST initiatives.
The regulatory environment is also taking shape. Regulation (EU) 2026/1744 has been introduced on July 8, 2026, to amend the implementation dates of the EU AI Act. Some high-risk obligations were changed, while others were kept, and different compliance deadlines were introduced for organizations that use AI systems.
NIST’s approach is completely different. The AI Agent Standards Initiative concentrates on creating secure and interoperable standards. NCCoE initiative is researching approaches to software and AI agent identification and authorization. NIST has made agent identity standards and authorization a specific area of standards work. The NIST NCCoE separately published a February 2026 concept paper examining standards-based approaches to AI agent identity and authorization.
Regulatory Landscape By Region
| Region | Regulatory Stringency | Key Compliance / Standards Direction | Market Implication |
| North America | Medium | NIST AI Agent Standards Initiative and NCCoE identity work | Encourages standards-based agent identity and authorization |
| Europe | High | EU AI Act and amendments under Regulation 2026/1744 | Greater compliance and governance requirements |
| Asia Pacific | Not publicly verified | No comparable region-specific requirement identified in the reviewed sources | Regional assessment requires further verification |
| Latin America | Not publicly verified | No comparable region-specific requirement identified in the reviewed sources | Regional assessment requires further verification |
| Middle East & Africa | Not publicly verified | No comparable region-specific requirement identified in the reviewed sources | Regional assessment requires further verification |
Source: NIST and European Union regulatory publications
The regulatory significance extends beyond documentation. NIST's agent identity work covers identification, authorization, auditing, and non-repudiation, which are directly relevant to the security architecture enterprises need when agents can perform actions independently.
AI Agent Security Market Technology & Innovation Trends
MCP security is becoming an important technology area because AI agents increasingly need controlled access to external tools and enterprise resources. The Okta solution of AI agent technology features the Agent Gateway that provides MCP-specific functionality, whereas Ping Identity created the MCP server and security controls for MCP environment.
Requirements for agent authentication are also emerging. The NCCoE initiative by NIST is conducting an assessment of standards-based methods for agent authentication and authorization. This initiative aims to give practical recommendations to organizations implementing software and AI agents.
Runtime security has become a separate product category. In its July 2026 product update, Okta released Agent Gateway and Agent-to-Agent Connections for runtime protection of the interaction of agents with enterprise applications and other agents.
| Technology | Adoption Stage | Key Development | Market Impact |
| MCP security | Early commercial development | MCP gateway and identity controls | Secures agent-to-tool connections |
| Agent identity management | Commercial deployment | Okta and Ping Identity offerings | Establishes identity and access controls |
| Agent governance | Commercial deployment | Zenity and Okta platforms | Enables policy and lifecycle management |
| Runtime protection | Expanding | Agent Gateway and agent-to-agent controls | Controls actions during execution |
Source: Polaris Market Research Analysis
AI Agent Security Market Competitive Insights
The competitive structure contains two broad groups. The incumbent group includes Okta, Microsoft, Google, Palo Alto Networks, CrowdStrike, and SentinelOne. These companies extend established identity, endpoint, cloud, or security platforms into AI-agent environments. Okta launched a new solution to provide AI-agent identities, whereas SentinelOne acquired Prompt Security in 2025 to advance its generative AI and agent security strategy.
Specialist firms include Zenity, Obsidian Security, GitGuardian, Hush Security, Oasis Security, and many more. These AI agent security key players offer services such as AI governance, non-human identities, secrets, and agent security. The funding rounds of Zenity, Obsidian, GitGuardian, and Hush show how much investors are interested in specialized security offerings. Also, there have been efforts at consolidation happening within the market.
Competitive Positioning Table of Top AI Agent Security Vendors 2026
The competitive landscape is increasingly divided between established security and identity platforms and specialist vendors focused on agent governance or non-human identity. Product launches and financing activity indicate that both groups are investing in the category.
| Vendor | Market Position | AI Agent Security Positioning | Key Competitive Strength |
| CrowdStrike Holdings, Inc. | Leader | Broad AI-agent lifecycle security, agent discovery, continuous identity, supply-chain protection, and runtime detection/response. | Enterprise cybersecurity platform reach; strong endpoint, cloud, identity, and runtime telemetry. |
| Cyera | Emerging / Specialist | AI and data security with visibility and governance across sensitive data used by AI agents. | Data-security specialization and strong data discovery/classification capabilities. |
| Fortinet | Established / Broad Security | AI security capabilities integrated with network, endpoint, cloud, and security operations controls. | Large installed base and integrated security fabric; AI-agent-specific depth is developing. |
| GitGuardian | Specialist | Secrets and non-human identity protection for AI coding assistants, agents, MCP environments, and software supply chains. | Strong developer-security positioning and secrets detection across the SDLC. |
| Google LLC | Leader / Hyperscaler | Security for AI workloads and agents across Google Cloud, identity, data, and AI infrastructure. | Hyperscale cloud ecosystem and native AI infrastructure/security integration. |
| Hush Security | Emerging / Specialist | Identity-based security for AI agents and MCPs, with scoped permissions, ownership, and runtime governance. | Purpose-built non-human identity approach and least-privilege controls. |
| Microsoft Corporation | Leader / Hyperscaler | Agent identity, governance, security, and runtime controls integrated with Microsoft security and cloud ecosystem. | Broad enterprise footprint, Entra identity, Azure AI, and security-stack integration. |
| Obsidian Security | Emerging / Specialist | Discovery, risk assessment, behavioral monitoring, and runtime policy enforcement for enterprise AI agents. | SaaS/application-layer visibility and strong agent governance orientation. |
| Okta, Inc. | Leader / Identity Specialist | AI-agent identity lifecycle, authentication, authorization, and governance across enterprise resources and identity providers. | Strong identity leadership and non-human/agent identity capabilities. |
| Oligo Security | Emerging / Specialist | Application/runtime security and observability that can help identify anomalous agent behavior and application risk. | Runtime application-security expertise and strong visibility into live workloads. |
| Palo Alto Networks, Inc. | Leader | Agent security through Prisma AIRS, including agent discovery, identity, supply-chain security, behavior testing, and runtime enforcement. | Comprehensive AI security portfolio and established enterprise cybersecurity platform. |
| Ping Identity | Established / Identity Specialist | Identity, authentication, authorization, and access governance relevant to securing AI agents and machine identities. | Mature identity and access-management capabilities for enterprise environments. |
| SentinelOne, Inc. | Leader / Broad Security | AI-agent security integrated with autonomous endpoint, cloud, identity, and security operations capabilities. | AI-native cybersecurity positioning and autonomous detection/response strengths. |
| Token Security | Emerging / Specialist | Non-human identity discovery, governance, and lifecycle security for service accounts and AI agents. | Focused NHI security proposition and agent identity visibility. |
| Zenity | Leader / Specialist | Purpose-built agentic AI security spanning discovery, posture, configuration, policy enforcement, and runtime investigation. | Specialist focus on autonomous AI security across low-code/no-code and enterprise agent ecosystems. |
Source: Company announcements and verified public sources
Barriers to Entering the AI Agent Security Market?
The AI agent security market has relatively high technical and commercial entry requirements. Vendors must understand identity management, AI-agent behavior, application security, authorization, and emerging agent protocols. Capital requirements are becoming visible through funding activity. These transactions demonstrate the capital being directed toward specialized AI-agent security and governance platforms.
Incumbent identity vendors have another advantage. Okta has built dedicated AI-agent identity capabilities into its platform, while Ping Identity has extended its identity control plane into autonomous AI. Such established platforms already have enterprise relationships and identity infrastructure that new entrants must replicate or integrate with.
Technical standards represent another barrier. NIST continues to evaluate the standards-based approach to identity and authorization of AI agents, including identification, authorization, auditing, and non-repudiation. New vendors must therefore build products that can comply with an evolving standards environment.
MCP security also requires protocol-level expertise. Vendors must understand conventional identity controls and how agents interact with tools and other agents. This creates a higher technical threshold than traditional application security products.
List of AI Agent Security Market Leaders
- CrowdStrike Holdings, Inc.
- Cyera
- Fortinet
- GitGuardian
- Google LLC
- Hush Security
- Microsoft Corporation
- Obsidian Security
- Okta, Inc.
- Oligo Security
- Palo Alto Networks, Inc.
- Ping Identity
- SentinelOne, Inc.
- Token Security
- Zenity
AI Agent Security Market Industry Developments
- August 2026: Fortinet acquired Virtue AI for enhancing AI agent security by continuous validation, monitoring, governance, and protection from any malicious behavior. (source: fortinet.com)
- August 2026: Zenity received a USD 125 million Series C investment led by Norwest. The funding will boost Zenity's ability to meet rapidly increasing demand for AI agent security. (Source: zenity.io)
- July 2026: Hush Security received a USD 30 million Series A investment, with Akamai Joining as Strategic Investor. It will help the company close the AI agent governance gap. (source: hush.security)
- July 2026: Okta announced new innovations within Okta for AI Agents. It will help organizations secure AI agents at runtime and automate ongoing agent governance. (source: okta.com)
- March 2026: Palo Alto Networks released Prisma AIRS 3.0 for securing AI agents through their lifecycle by discovering, assessing risks, controlling identities, and providing runtime protection of agents. (source: investors.paloaltonetworks.com)
Premium Insights and Forward Outlook
As per our AI agent security market forecast 2034, the market is moving toward a security architecture in which agent identity becomes a core control layer. The segmentation analysis shows that identity and access security is closely connected to the regional picture because North America has the strongest concentration of vendors developing dedicated agent-identity capabilities.
Over the next three to five years, competitive differentiation is likely to move from simple agent discovery toward continuous identity governance, runtime enforcement, tool-level authorization, auditability, and policy management. The market opportunity will favor platforms that can integrate these controls without creating separate security silos.
AI Agent Security Market Segmentation
By Security Capability Outlook (Revenue, USD Billion, 2021–2034)
- Agent Identity & Access Security
- Agent Runtime Security
- Agent Governance & Compliance
- Agent Data Security
- Agent Threat Detection & Response
By Agent Type Outlook (Revenue, USD Billion, 2021–2034)
- Single Agents
- Multi-Agent Systems
- Human-in-the-Loop
- Agentic AI Pipelines
By Offering Outlook (Revenue, USD Billion, 2021–2034)
- Software / Platform
- Services
- Professional Services (consulting, implementation, integration)
- Managed Security Services
By Deployment Outlook (Revenue, USD Billion, 2021–2034)
- Cloud
- Hybrid
- On-premises
By Organization Size Outlook (Revenue, USD Billion, 2021–2034)
- Large Enterprises
- SMEs
By End Use Outlook (Revenue, USD Billion, 2021–2034)
- IT & Telecommunications
- BFSI (Banking, Financial Services & Insurance)
- Healthcare & Life Sciences
- Government & Defense
- Other Industries
By Regional Outlook (Revenue, USD Billion, 2021-2034)
- North America
- U.S.
- Canada
- Europe
- Germany
- France
- UK
- Italy
- Spain
- Netherlands
- Russia
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- Malaysia
- South Korea
- Indonesia
- Australia
- Vietnam
- Rest of Asia Pacific
- Middle East & Africa
- Saudi Arabia
- UAE
- Israel
- South Africa
- Rest of Middle East & Africa
- Latin America
- Mexico
- Brazil
- Argentina
- Rest of Latin America
AI Agent Security Market Report Scope
| Report Attributes | Details |
| Market Size in 2025 | USD 18.57 Billion |
| Market Size in 2026 | USD 25.88 Billion |
| Revenue Forecast by 2034 | USD 370.93 Billion |
| CAGR | 39.49% from 2026 to 2034 |
| Base Year | 2025 |
| Historical Data | 2021–2024 |
| Forecast Period | 2026–2034 |
| Quantitative Units | Revenue in USD Billion and CAGR from 2026 to 2034 |
| Report Coverage | Revenue Forecast, Competitive Landscape, Growth Factors, and Industry Trends |
| Segments Covered |
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| Regional Scope |
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| Competitive Landscape |
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| Report Format |
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| Customization | Report customization as per your requirements with respect to countries, regions, and segmentation. |
Source: Polaris Market Research Analysis
Research Methodology
The AI agent security market research methodology combines secondary research, primary validation, market sizing, forecasting, and data validation. Secondary research for this report places greater weight on government and regulatory publications because the market is relatively new and public market-sizing information remains limited.
The research reviewed NIST's AI Agent Standards Initiative, NIST NCCoE's work on software and AI agent identity and authorization, and European Union regulatory material. Product launches, financing operations, acquisitions, and positioning within the market have been cross-referenced through company communications.
Primary research following the Polaris methodology will consist of structured interviews, validation calls, and survey or panel participation. Industry participants, tech suppliers, security experts, and enterprise buyers can be considered in the validation of qualitative research and purchase motivations.
Market sizing utilizes top-down and bottom-up methodologies together with data triangulation. Top-down methodology takes into consideration the overall security and identity environment, while the bottom-up methodology considers the vendor activity, enterprise deployment, product commercialization, and application-driven demand. Final estimates are reconciled before publishing.
Forecasting will factor in the evolution of the needs for agent identities, standard maturity, regulation enforcement, enterprise implementation, product commercialization, and investment. The forecast will also analyze the competitive landscape between identity-security platforms and AI-agent security companies.
Data validation takes into consideration the cross-validation of quantitative and qualitative results through multiple data sources. Claims that could not be independently verified through reliable public sources were excluded rather than estimated.
AI Agent Security Market – Research Methodology Overview
| Research Phase | Key Activities | Data Sources | Purpose |
| Secondary Research | Review of AI-agent standards, regulation, company activity and technology developments | NIST, EU publications, company announcements, industry sources | Establish market fundamentals |
| Primary Research | Interviews and validation discussions | Industry experts and market participants | Validate market assumptions |
| Market Sizing | Top-down and bottom-up estimation | Company activity, industry data and internal research | Estimate market opportunity |
| Forecasting | Assessment of technology, regulation and procurement trends | Standards, regulatory and commercial developments | Develop market forecast |
| Data Validation | Cross-verification of findings | Primary and secondary sources | Improve accuracy and consistency |
Source: Polaris Market Research Analysis
Who Buys This Research Report and Why?
Enterprise CISOs and security architects use the report to understand how AI agents change identity, authorization, governance, and runtime-security requirements. The growing availability of dedicated products makes build-versus-buy decisions more relevant.
Technology and platform leaders can use the analysis to compare identity-based controls with runtime and governance platforms. Okta and Ping Identity’s releases of their products serve as an example of how traditional architectures of identity are being extended to AI.
The report can be used by investors and corporate strategy departments to gauge the development of specialty vendors. For instance, Zenity’s Series C funding amounting to USD 125 million.
Compliance departments can use the report to track regulations and standards developments. The two differing approaches to regulation and standards include NIST’s agent standards and the EU’s amended AI Act implementation framework.
Why Choose Polaris Market Research?
The AI agent security market requires more than a conventional cybersecurity market assessment because the category sits at the intersection of identity, AI governance, application security, runtime protection, and regulatory compliance.
This report places particular emphasis on primary institutional sources. NIST's AI Agent Standards Initiative and NCCoE identity and authorization work provide direct insight into how government standards activity is developing around AI agents. The EU regulatory analysis uses the official European Union regulatory framework rather than relying solely on secondary commentary.
The competitive analysis also considers current company activity rather than relying only on established cybersecurity rankings. Product launches from Okta and Ping Identity, funding from Zenity, Obsidian Security, GitGuardian, and Hush Security, and acquisition activity provide a current view of how vendors are positioning themselves in the category.
Polaris Market Research can further customize the study by country, region, security capability, deployment model, organization size, offering, agent type, end use, and company coverage. Analyst support can be provided for interpretation of market trends, competitive positioning, and segmentation requirements.
AI Agent Security Market FAQ's
The AI agent security market is valued at USD 18.57 billion in 2025 and it expected to cross USD 370.93 billion by 2034.
The AI agent security industry is expected to record a CAGR of 39.49% during the forecast period.
North America led in 2025, driven by strong vendor activity from Okta, Ping Identity, Zenity, and Obsidian Security.
Rise in the need for identity, authorization, governance, and secured access to enterprise systems drives the market growth.
It ensures the protection of the identity, permissions, actions, and operational capabilities of autonomous AI agents as well as conventional methods and datasets.
It increases the need for governance, visibility, risk management, and compliance of AI.
A few of the major players are Okta, Ping Identity, Palo Alto Networks, Cyera, Zenity, Obsidian Security, GitGuardian, Hush Security, Microsoft, Google, CrowdStrike, and SentinelOne.
The market is expected to expand as enterprise AI-agent adoption increases and identity, authorization, runtime security, and governance standards mature.
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