사이버 보안 에이전트형 AI 시장 : 제공별, 에이전트 자율성별, 보안 기능별, 전개 형태별, 조직 규모별, 업계별 - 시장 규모, 업계 역학, 기회 분석 및 예측(2026년-2035년)

The cybersecurity agentic AI market is experiencing explosive growth as enterprises transition away from human-assisted artificial intelligence systems toward fully autonomous security architectures. In 2025, the market is valued at approximately USD 1.66 billion, marking the early but rapidly accelerating phase of adoption for agentic AI in cybersecurity. This valuation reflects growing enterprise investment in autonomous security platforms, as well as increasing confidence in AI systems that can operate with minimal human intervention while maintaining high accuracy in threat identification and response.

Looking ahead, the market is projected to reach around USD 24.93 billion by 2035, expanding at a strong compound annual growth rate (CAGR) of 31.12% during the forecast period from 2026 to 2035. This rapid growth trajectory is being fueled by widespread deployment of autonomous threat detection systems, continuous advancements in machine learning models, and the increasing integration of AI governance frameworks that ensure safety, compliance, and accountability in automated decision-making processes.

Noteworthy Market Developments

Five major players currently dominate the global Cybersecurity Agentic AI market landscape, each contributing distinct technological strengths that shape competitive dynamics in the sector. Palo Alto Networks holds a commanding position in the market due to its deeply integrated autonomous security platforms, which are built on robust proprietary systems designed for large-scale enterprise deployment.

CrowdStrike has established itself as a key leader by leveraging vast amounts of endpoint telemetry data collected across its global customer base. Microsoft plays a strategically important role in the market by capitalizing on its expansive enterprise cloud ecosystem, particularly through Azure and its broader security suite. SentinelOne distinguishes itself through its strong focus on autonomous endpoint protection, particularly its ability to isolate and remediate malware without human intervention. Darktrace remains a highly competitive force in the market by relying on advanced self-learning mathematical and behavioral AI algorithms.

Core Growth Drivers

The global cybersecurity talent shortage has become a major structural driver accelerating the growth of the cybersecurity agentic AI market. Across industries and regions, organizations are struggling to recruit and retain sufficient skilled professionals to defend increasingly complex digital infrastructures. This widening skills gap is placing immense pressure on security operations teams, pushing enterprises to explore automation and AI-driven solutions that can compensate for the lack of human expertise and workforce capacity. At a global level, the cybersecurity industry faces a critical deficit of talent, with estimates indicating that an additional 4.8 million professionals are required just to meet baseline security needs.

Emerging Opportunity Trends

AI-to-AI threat vectors are emerging as a significant opportunity and evolving trend that is expected to shape the future growth of the cybersecurity agentic AI market. As organizations increasingly deploy autonomous AI systems across critical digital infrastructure, a new category of cyber risk is beginning to surface, where malicious or compromised AI agents interact directly with other AI systems. Unlike traditional cyber threats that rely heavily on human-controlled operations, these advanced threat vectors involve automated, machine-speed interactions that can exploit vulnerabilities, manipulate model behavior, and execute attacks through system integrations such as APIs without requiring direct human involvement.

Barriers to Optimization

Excessive agency and privilege escalation represent significant constraints on the growth of the cybersecurity agentic AI market, primarily due to the risks associated with granting autonomous systems too much operational authority. While agentic AI is designed to enhance cybersecurity by enabling systems to independently detect, analyze, and respond to threats, extending this autonomy into real-world execution without sufficient human oversight introduces a range of potential vulnerabilities. Organizations remain cautious about allowing AI-driven agents unrestricted access to critical systems, especially in environments where even minor errors can result in severe operational, financial, or reputational consequences.

Detailed Market Segmentation

By security function, the threat detection and response segment, including Endpoint Detection and Response (EDR) and Extended Detection and Response (XDR) solutions, dominated the cybersecurity agentic AI market with a market share of approximately 47.30% in 2025. This segment represents the largest share of the market due to the growing need for organizations to identify, investigate, and mitigate cyber threats in real time. As cyberattacks become increasingly sophisticated, enterprises are prioritizing security technologies that can not only detect malicious activities but also respond autonomously before threats escalate into major security incidents.

By deployment model, cloud-based solutions dominated the cybersecurity agentic AI market in 2025, accounting for approximately 54.60% of the total market share. This leadership position is largely attributed to the growing demand for scalable, flexible, and cost-effective cybersecurity platforms capable of supporting increasingly complex digital environments. As organizations continue to accelerate cloud adoption and digital transformation initiatives, cloud-based cybersecurity agentic AI solutions have emerged as the preferred deployment model for enterprises seeking advanced threat protection, operational efficiency, and simplified infrastructure management.

By organization size, large enterprises emerged as the dominant segment of the cybersecurity agentic AI market, accounting for approximately 69.20% of the total market share in 2025. This substantial share reflects the increasing reliance of multinational corporations and large-scale organizations on advanced cybersecurity technologies to safeguard their extensive digital ecosystems. Large enterprises typically operate across multiple regions, manage thousands of employees, and maintain vast networks of interconnected systems, making cybersecurity a strategic business priority.

By Vertical, the Banking, Financial Services, and Insurance (BFSI) sector accounted for approximately 24% of the global cybersecurity agentic AI market, making it one of the largest end-user segments for advanced autonomous security solutions. The sector's substantial market share is driven by its critical dependence on digital platforms, online transactions, and interconnected financial ecosystems that process enormous volumes of sensitive customer and institutional data every day. As financial institutions continue to accelerate digital transformation initiatives, the need for sophisticated cybersecurity technologies capable of protecting complex infrastructures has become increasingly important.

Segment Breakdown

By Offering

• Platforms / Software
• Services (Managed Detection & Response, Professional)

By Agent Autonomy

• Assisted (Copilot)
• Semi-Autonomous
• Fully Autonomous

By Security Function

• Threat Detection & Response (EDR/XDR)
• Security Operations (SOC Automation / SOAR)
• Vulnerability Management
• Identity & Access Management
• Cloud Security
• Email & Phishing Security
• Threat Intelligence

By Deployment

• Cloud
• On-Premises
• Hybrid

By Organization Size

• Large Enterprises
• Small & Medium Enterprises

By Vertical

• BFSI
• Government & Defense
• Healthcare
• IT & Telecom
• Retail
• Energy & Utilities
• Manufacturing
• Others

By Region

• North America
• The U.S.
• Canada
• Mexico
• Europe
• Western Europe
• The UK
• Germany
• France
• Italy
• Spain
• Rest of Western Europe
• Eastern Europe
• Poland
• Russia
• Rest of Eastern Europe
• Asia Pacific
• China
• India
• Japan
• Australia & New Zealand
• South Korea
• ASEAN
• Rest of Asia Pacific
• Middle East & Africa (MEA)
• Saudi Arabia
• South Africa
• UAE
• Rest of MEA
• South America
• Argentina
• Brazil
• Rest of South America

Geography Breakdown

• As of 2026, North America has established itself as the largest and most influential market for cybersecurity agentic AI, accounting for approximately 48.10% of the global market share. This dominant position reflects the region's highly advanced digital ecosystem, substantial investments in cybersecurity technologies, and strong commitment to innovation in artificial intelligence.
• Furthermore, North America hosts many of the world's leading cybersecurity and AI companies, creating an environment that accelerates research, development, and commercialization of next-generation security technologies. With the global cybersecurity agentic AI market expected to reach approximately USD 2.43 billion in 2026, the United States contributes a significant portion of overall revenue, reinforcing the region's leadership in this rapidly expanding sector.
• A major factor behind North America's market dominance is the early adoption of autonomous cybersecurity systems by prominent technology and security firms. Industry leaders such as CrowdStrike, SentinelOne, and Microsoft have been at the forefront of integrating agentic AI into cybersecurity operations. These organizations have invested heavily in developing intelligent systems capable of independently identifying, assessing, and responding to cyber threats in real time.

Leading Market Participants

• Microsoft
• CrowdStrike
• Palo Alto Networks
• SentinelOne
• Darktrace
• Cisco
• Fortinet
• Check Point
• Google (Mandiant)
• Trend Micro
• Torq
• Dropzone AI
• Simbian
• Prophet Security
• Radiant Security
• Other Prominent Players

Table of Content

Chapter 1. Executive Summary: Global Cybersecurity Agentic AI Market

Chapter 2. Research Methodology & Research Framework

• 2.1. Research Objective
• 2.2. Product Overview
• 2.3. Market Segmentation
• 2.4. Qualitative Research
  • 2.4.1. Primary & Secondary Sources
• 2.5. Quantitative Research
  • 2.5.1. Primary & Secondary Sources
• 2.6. Breakdown of Primary Research Respondents, By Region
• 2.7. Assumption for Study
• 2.8. Market Size Estimation
• 2.9. Data Triangulation

Chapter 3. Global Cybersecurity Agentic AI Market Overview

• 3.1. Industry Value Chain Analysis
  • 3.1.1. AI Infrastructure & Compute Providers
  • 3.1.2. Foundation Model & LLM Developers
  • 3.1.3. Agentic Security Platform & SOC Automation Vendors
  • 3.1.4. MDR & Professional Service Providers
  • 3.1.5. Enterprise Security Teams / SOCs (BFSI, Government, Healthcare)
• 3.2. Industry Outlook
  • 3.2.1. Overview of the Global AI-Driven Cybersecurity & Autonomous SOC Industry
  • 3.2.2. Talent Shortage, Alert Fatigue & Tool Sprawl Driving Automation
  • 3.2.3. Governance, Trust & Human-in-the-Loop Guardrails
• 3.3. PESTLE Analysis
• 3.4. Porter's Five Forces Analysis
  • 3.4.1. Bargaining Power of Suppliers
  • 3.4.2. Bargaining Power of Buyers
  • 3.4.3. Threat of Substitutes
  • 3.4.4. Threat of New Entrants
  • 3.4.5. Degree of Competition
• 3.5. Market Growth and Outlook
  • 3.5.1. Market Revenue Estimates and Forecast (US$ Mn), 2020-2035
  • 3.5.2. Price Trend Analysis, By Offering

Chapter 4. Global Cybersecurity Agentic AI Market Analysis

• 4.1. Competition Dashboard
  • 4.1.1. Market Concentration Rate
  • 4.1.2. Company Market Share Analysis (Value %), 2025
  • 4.1.3. Competitor Mapping & Benchmarking

Chapter 5. Global Cybersecurity Agentic AI Market Analysis

• 5.1. Market Dynamics and Trends
  • 5.1.1. Growth Drivers
  • 5.1.2. Restraints
  • 5.1.3. Opportunity
  • 5.1.4. Key Trends
• 5.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 5.2.1. By Offering
    • 5.2.1.1. Key Insights
      • 5.2.1.1.1. Platforms / Software
      • 5.2.1.1.2. Services
        • 5.2.1.1.2.1. Managed Detection & Response
        • 5.2.1.1.2.2. Professional
  • 5.2.2. By Agent Autonomy
    • 5.2.2.1. Key Insights
      • 5.2.2.1.1. Assisted (Copilot)
      • 5.2.2.1.2. Semi-Autonomous
      • 5.2.2.1.3. Fully Autonomous
  • 5.2.3. By Security Function
    • 5.2.3.1. Key Insights
      • 5.2.3.1.1. Threat Detection & Response (EDR/XDR)
      • 5.2.3.1.2. Security Operations (SOC Automation / SOAR)
      • 5.2.3.1.3. Vulnerability Management
      • 5.2.3.1.4. Identity & Access Management
      • 5.2.3.1.5. Cloud Security
      • 5.2.3.1.6. Email & Phishing Security
      • 5.2.3.1.7. Threat Intelligence
  • 5.2.4. By Deployment
    • 5.2.4.1. Key Insights
      • 5.2.4.1.1. Cloud
      • 5.2.4.1.2. On-Premises
      • 5.2.4.1.3. Hybrid
  • 5.2.5. By Organization Size
    • 5.2.5.1. Key Insights
      • 5.2.5.1.1. Large Enterprises
      • 5.2.5.1.2. Small & Medium Enterprises
  • 5.2.6. By Vertical
    • 5.2.6.1. Key Insights
      • 5.2.6.1.1. BFSI
      • 5.2.6.1.2. Government & Defense
      • 5.2.6.1.3. Healthcare
      • 5.2.6.1.4. IT & Telecom
      • 5.2.6.1.5. Retail
      • 5.2.6.1.6. Energy & Utilities
      • 5.2.6.1.7. Manufacturing
      • 5.2.6.1.8. Others
  • 5.2.7. By Region
    • 5.2.7.1. Key Insights
      • 5.2.7.1.1. North America
        • 5.2.7.1.1.1. The U.S.
        • 5.2.7.1.1.2. Canada
        • 5.2.7.1.1.3. Mexico
      • 5.2.7.1.2. Europe
        • 5.2.7.1.2.1. Western Europe
          • 5.2.7.1.2.1.1. The UK
          • 5.2.7.1.2.1.2. Germany
          • 5.2.7.1.2.1.3. France
          • 5.2.7.1.2.1.4. Italy
          • 5.2.7.1.2.1.5. Spain
          • 5.2.7.1.2.1.6. Rest of Western Europe
        • 5.2.7.1.2.2. Eastern Europe
          • 5.2.7.1.2.2.1. Poland
          • 5.2.7.1.2.2.2. Russia
          • 5.2.7.1.2.2.3. Rest of Eastern Europe
      • 5.2.7.1.3. Asia Pacific
        • 5.2.7.1.3.1. China
        • 5.2.7.1.3.2. India
        • 5.2.7.1.3.3. Japan
        • 5.2.7.1.3.4. Australia & New Zealand
        • 5.2.7.1.3.5. South Korea
        • 5.2.7.1.3.6. ASEAN
        • 5.2.7.1.3.7. Rest of Asia Pacific
      • 5.2.7.1.4. Middle East & Africa (MEA)
        • 5.2.7.1.4.1. Saudi Arabia
        • 5.2.7.1.4.2. South Africa
        • 5.2.7.1.4.3. UAE
        • 5.2.7.1.4.4. Rest of MEA
      • 5.2.7.1.5. South America
        • 5.2.7.1.5.1. Argentina
        • 5.2.7.1.5.2. Brazil
        • 5.2.7.1.5.3. Rest of South America

Chapter 6. North America Market Analysis

• 6.1. Market Dynamics and Trends
  • 6.1.1. Growth Drivers
  • 6.1.2. Restraints
  • 6.1.3. Opportunity
  • 6.1.4. Key Trends
• 6.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 6.2.1. Key Insights
    • 6.2.1.1. By Offering
    • 6.2.1.2. By Agent Autonomy
    • 6.2.1.3. By Security Function
    • 6.2.1.4. By Deployment
    • 6.2.1.5. By Organization Size
    • 6.2.1.6. By Vertical
    • 6.2.1.7. By Country

Chapter 7. Europe Market Analysis

• 7.1. Market Dynamics and Trends
  • 7.1.1. Growth Drivers
  • 7.1.2. Restraints
  • 7.1.3. Opportunity
  • 7.1.4. Key Trends
• 7.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 7.2.1. Key Insights
    • 7.2.1.1. By Offering
    • 7.2.1.2. By Agent Autonomy
    • 7.2.1.3. By Security Function
    • 7.2.1.4. By Deployment
    • 7.2.1.5. By Organization Size
    • 7.2.1.6. By Vertical
    • 7.2.1.7. By Country

Chapter 8. Asia Pacific Market Analysis

• 8.1. Market Dynamics and Trends
  • 8.1.1. Growth Drivers
  • 8.1.2. Restraints
  • 8.1.3. Opportunity
  • 8.1.4. Key Trends
• 8.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 8.2.1. Key Insights
    • 8.2.1.1. By Offering
    • 8.2.1.2. By Agent Autonomy
    • 8.2.1.3. By Security Function
    • 8.2.1.4. By Deployment
    • 8.2.1.5. By Organization Size
    • 8.2.1.6. By Vertical
    • 8.2.1.7. By Country

Chapter 9. Middle East & Africa Market Analysis

• 9.1. Market Dynamics and Trends
  • 9.1.1. Growth Drivers
  • 9.1.2. Restraints
  • 9.1.3. Opportunity
  • 9.1.4. Key Trends
• 9.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 9.2.1. Key Insights
    • 9.2.1.1. By Offering
    • 9.2.1.2. By Agent Autonomy
    • 9.2.1.3. By Security Function
    • 9.2.1.4. By Deployment
    • 9.2.1.5. By Organization Size
    • 9.2.1.6. By Vertical
    • 9.2.1.7. By Country

Chapter 10. South America Market Analysis

• 10.1. Market Dynamics and Trends
  • 10.1.1. Growth Drivers
  • 10.1.2. Restraints
  • 10.1.3. Opportunity
  • 10.1.4. Key Trends
• 10.2. Market Size and Forecast, 2020-2035 (US$ Mn)
  • 10.2.1. Key Insights
    • 10.2.1.1. By Offering
    • 10.2.1.2. By Agent Autonomy
    • 10.2.1.3. By Security Function
    • 10.2.1.4. By Deployment
    • 10.2.1.5. By Organization Size
    • 10.2.1.6. By Vertical
    • 10.2.1.7. By Country

Chapter 11. Company Profile (Company Overview, Financial Matrix, Key Product landscape, Key Personnel, Key Competitors, Contact Address, and Business Strategy Outlook)

• 11.1. Microsoft
• 11.2. CrowdStrike
• 11.3. Palo Alto Networks
• 11.4. SentinelOne
• 11.5. Darktrace
• 11.6. Cisco
• 11.7. Fortinet
• 11.8. Check Point
• 11.9. Google (Mandiant)
• 11.10. Trend Micro
• 11.11. Torq
• 11.12. Dropzone AI
• 11.13. Simbian
• 11.14. Prophet Security
• 11.15. Radiant Security
• 11.16. Other Prominent Players

Chapter 12. Annexure

• 12.1. List of Secondary Sources
• 12.2. Key Country Markets- Macro Economic Outlook/Indicators