North America Agentic AI In Cybersecurity Market Size, Share & Industry Analysis Report By Component (Solution, and Services), By Application (Threat Detection & Response, Vulnerability Management, and Other Application), By Deployment (Cloud, and On-prem
Description
The North America Agentic AI In Cybersecurity Market would witness market growth of 33.1% CAGR during the forecast period (2025-2032).
The US market dominated the North America Agentic AI In Cybersecurity Market by Country in 2024, and would continue to be a dominant market till 2032; thereby, achieving a market value of USD 59,652 million by 2032. The Canada market is experiencing a CAGR of 35.6% during (2025 - 2032). Additionally, The Mexico market would exhibit a CAGR of 35.5% during (2025 - 2032). The US and Canada led the North America Agentic AI In Cybersecurity Market by Country with a market share of 78.9% and 12.7% in 2024.
In North American cybersecurity, agentic AI refers to systems that can see, think, and act on their own with little help from humans. These systems can do things like threat triage, mitigation, and vulnerability remediation. The number of people using it has grown because cyber threats are getting more complicated, there aren't enough skilled workers, and people want quick responses. Early cybersecurity systems used signatures, but now agentic AI uses big models, cloud infrastructure, and orchestration frameworks to follow rules. Businesses use agentic AI carefully, usually starting with tasks that aren't too risky, and making sure that they follow the rules, can be audited, and can be explained. These systems are helping SOC analysts more and more by taking care of repetitive tasks so that people can focus on more complicated threats.
Multi-agent orchestration, integration with SIEM/XDR platforms, and strict governance, risk management, and compliance practices are some of the trends that are shaping the market. To handle liability and unintended consequences, vendors stress safe automation with guardrails, human-in-the-loop checkpoints, and clear auditing. Hyperscale cloud providers, traditional cybersecurity companies, and agile startups that focus on subdomains like explainability, agent identity, and adversarial robustness are all competing fiercely. Trust, safety, integration, and compliance with regulations are becoming more important than raw ability when it comes to differentiation. More and more, success depends on providing autonomous functionality while making sure that enterprise customers in regulated industries have oversight, risk mitigation, and transparency.
End Use Outlook
Based on End Use, the market is segmented into IT & Telecom, BFSI, Government & Defense, Healthcare, Retail & E-commerce, and Other End Use. Among various US Agentic AI In Cybersecurity Market by End Use; The IT & Telecom market achieved a market size of USD $1712.9 Million in 2024 and is expected to grow at a CAGR of 31 % during the forecast period. The Healthcare market is predicted to experience a CAGR of 33.5% throughout the forecast period from (2025 - 2032).
Component Outlook
Based on Component, the market is segmented into Solution, and Services. The Solution market segment dominated the Mexico Agentic AI In Cybersecurity Market by Component is expected to grow at a CAGR of 35.1 % during the forecast period thereby continuing its dominance until 2032. Also, The Services market is anticipated to grow as a CAGR of 36.3 % during the forecast period during (2025 - 2032).
Country Outlook
The US is quickly making progress in agentic AI for cybersecurity as businesses look for ways to automatically find, respond to, and contain threats in complicated cloud, IoT, and remote environments. Adoption is driven by a mature market, a lot of capital, and a lot of skilled AI workers. A fragmented regulatory environment encourages innovation but also requires careful governance, explainability, and auditability. Organizations use AI agents for SOC alert triage, threat hunting, and closed-loop remediation, usually with human oversight to protect privacy and legal issues. Big cloud companies and cybersecurity companies add self-driving agents to XDR, SOAR, and security copilot platforms. Startups, on the other hand, focus on specific areas like OT security and API protection. To keep up with changing federal and state rules, companies focus on adversarial testing, detailed logging, and rollback features. There is a lot of competition, and companies set themselves apart by their speed, accuracy, compliance, and industry-specific skills. This makes the U.S. market the best place to adopt safe and scalable agentic AI.
List of Key Companies Profiled
By Component
The US market dominated the North America Agentic AI In Cybersecurity Market by Country in 2024, and would continue to be a dominant market till 2032; thereby, achieving a market value of USD 59,652 million by 2032. The Canada market is experiencing a CAGR of 35.6% during (2025 - 2032). Additionally, The Mexico market would exhibit a CAGR of 35.5% during (2025 - 2032). The US and Canada led the North America Agentic AI In Cybersecurity Market by Country with a market share of 78.9% and 12.7% in 2024.
In North American cybersecurity, agentic AI refers to systems that can see, think, and act on their own with little help from humans. These systems can do things like threat triage, mitigation, and vulnerability remediation. The number of people using it has grown because cyber threats are getting more complicated, there aren't enough skilled workers, and people want quick responses. Early cybersecurity systems used signatures, but now agentic AI uses big models, cloud infrastructure, and orchestration frameworks to follow rules. Businesses use agentic AI carefully, usually starting with tasks that aren't too risky, and making sure that they follow the rules, can be audited, and can be explained. These systems are helping SOC analysts more and more by taking care of repetitive tasks so that people can focus on more complicated threats.
Multi-agent orchestration, integration with SIEM/XDR platforms, and strict governance, risk management, and compliance practices are some of the trends that are shaping the market. To handle liability and unintended consequences, vendors stress safe automation with guardrails, human-in-the-loop checkpoints, and clear auditing. Hyperscale cloud providers, traditional cybersecurity companies, and agile startups that focus on subdomains like explainability, agent identity, and adversarial robustness are all competing fiercely. Trust, safety, integration, and compliance with regulations are becoming more important than raw ability when it comes to differentiation. More and more, success depends on providing autonomous functionality while making sure that enterprise customers in regulated industries have oversight, risk mitigation, and transparency.
End Use Outlook
Based on End Use, the market is segmented into IT & Telecom, BFSI, Government & Defense, Healthcare, Retail & E-commerce, and Other End Use. Among various US Agentic AI In Cybersecurity Market by End Use; The IT & Telecom market achieved a market size of USD $1712.9 Million in 2024 and is expected to grow at a CAGR of 31 % during the forecast period. The Healthcare market is predicted to experience a CAGR of 33.5% throughout the forecast period from (2025 - 2032).
Component Outlook
Based on Component, the market is segmented into Solution, and Services. The Solution market segment dominated the Mexico Agentic AI In Cybersecurity Market by Component is expected to grow at a CAGR of 35.1 % during the forecast period thereby continuing its dominance until 2032. Also, The Services market is anticipated to grow as a CAGR of 36.3 % during the forecast period during (2025 - 2032).
Country Outlook
The US is quickly making progress in agentic AI for cybersecurity as businesses look for ways to automatically find, respond to, and contain threats in complicated cloud, IoT, and remote environments. Adoption is driven by a mature market, a lot of capital, and a lot of skilled AI workers. A fragmented regulatory environment encourages innovation but also requires careful governance, explainability, and auditability. Organizations use AI agents for SOC alert triage, threat hunting, and closed-loop remediation, usually with human oversight to protect privacy and legal issues. Big cloud companies and cybersecurity companies add self-driving agents to XDR, SOAR, and security copilot platforms. Startups, on the other hand, focus on specific areas like OT security and API protection. To keep up with changing federal and state rules, companies focus on adversarial testing, detailed logging, and rollback features. There is a lot of competition, and companies set themselves apart by their speed, accuracy, compliance, and industry-specific skills. This makes the U.S. market the best place to adopt safe and scalable agentic AI.
List of Key Companies Profiled
- CrowdStrike Holdings, Inc.
- Palo Alto Networks, Inc.
- Microsoft Corporation
- IBM Corporation
- Darktrace Holdings Limited
- Google LLC
- Anthropic PBC
- Salesforce, Inc.
- NVIDIA Corporation
- SentinelOne, Inc.
By Component
- Solution
- Services
- Threat Detection & Response
- Vulnerability Management
- Other Application
- Cloud
- On-premises
- IT & Telecom
- BFSI
- Government & Defense
- Healthcare
- Retail & E-commerce
- Other End Use
- US
- Canada
- Mexico
- Rest of North America
Table of Contents
178 Pages
- Chapter 1. Market Scope & Methodology
- 1.1 Market Definition
- 1.2 Objectives
- 1.3 Market Scope
- 1.4 Segmentation
- 1.4.1 North America Agentic AI In Cybersecurity Market, by Component
- 1.4.2 North America Agentic AI In Cybersecurity Market, by Application
- 1.4.3 North America Agentic AI In Cybersecurity Market, by Deployment
- 1.4.4 North America Agentic AI In Cybersecurity Market, by End Use
- 1.4.5 North America Agentic AI In Cybersecurity Market, by Country
- 1.5 Methodology for the research
- Chapter 2. Market at a Glance
- 2.1 Key Highlights
- Chapter 3. Market Overview
- 3.1 Introduction
- 3.1.1 Overview
- 3.1.1.1 Market Composition and Scenario
- 3.2 Key Factors Impacting the Market
- 3.2.1 Market Drivers
- 3.2.2 Market Restraints
- 3.2.3 Market Opportunities
- 3.2.4 Market Challenges
- Chapter 4. Market Trends – North America Agentic AI In Cybersecurity Market
- Chapter 5. State of Competition – North America Agentic AI In Cybersecurity Market
- Chapter 6. Value Chain Analysis of Agentic AI In Cybersecurity Market
- Chapter 7. Product Life Cycle – Agentic AI In Cybersecurity Market
- Chapter 8. Market Consolidation – Agentic AI in Cybersecurity Market
- Chapter 9. Key Customer Criteria – Agentic AI In Cybersecurity Market
- Chapter 10. Competition Analysis - Global
- 10.1 KBV Cardinal Matrix
- 10.2 Recent Industry Wide Strategic Developments
- 10.2.1 Partnerships, Collaborations and Agreements
- 10.2.2 Product Launches and Product Expansions
- 10.2.3 Acquisition and Mergers
- 10.3 Market Share Analysis, 2024
- 10.4 Top Winning Strategies
- 10.4.1 Key Leading Strategies: Percentage Distribution (2021-2025)
- 10.4.2 Key Strategic Move: (Product Launches and Product Expansions : 2024, Oct – 2025, Aug) Leading Players
- 10.5 Porter Five Forces Analysis
- Chapter 11. North America Agentic AI In Cybersecurity Market by Component
- 11.1 North America Solution Market by Country
- 11.2 North America Services Market by Country
- Chapter 12. North America Agentic AI In Cybersecurity Market by Application
- 12.1 North America Threat Detection & Response Market by Country
- 12.2 North America Vulnerability Management Market by Country
- 12.3 North America Other Application Market by Country
- Chapter 13. North America Agentic AI In Cybersecurity Market by Deployment
- 13.1 North America Cloud Market by Country
- 13.2 North America On-premises Market by Country
- Chapter 14. North America Agentic AI In Cybersecurity Market by End Use
- 14.1 North America IT & Telecom Market by Country
- 14.2 North America BFSI Market by Country
- 14.3 North America Government & Defense Market by Country
- 14.4 North America Healthcare Market by Country
- 14.5 North America Retail & E-commerce Market by Country
- 14.6 North America Other End Use Market by Country
- Chapter 15. North America Agentic AI In Cybersecurity Market by Country
- 15.1 US Agentic AI In Cybersecurity Market
- 15.1.1 US Agentic AI In Cybersecurity Market by Component
- 15.1.2 US Agentic AI In Cybersecurity Market by Application
- 15.1.3 US Agentic AI In Cybersecurity Market by Deployment
- 15.1.4 US Agentic AI In Cybersecurity Market by End Use
- 15.2 Canada Agentic AI In Cybersecurity Market
- 15.2.1 Canada Agentic AI In Cybersecurity Market by Component
- 15.2.2 Canada Agentic AI In Cybersecurity Market by Application
- 15.2.3 Canada Agentic AI In Cybersecurity Market by Deployment
- 15.2.4 Canada Agentic AI In Cybersecurity Market by End Use
- 15.3 Mexico Agentic AI In Cybersecurity Market
- 15.3.1 Mexico Agentic AI In Cybersecurity Market by Component
- 15.3.2 Mexico Agentic AI In Cybersecurity Market by Application
- 15.3.3 Mexico Agentic AI In Cybersecurity Market by Deployment
- 15.3.4 Mexico Agentic AI In Cybersecurity Market by End Use
- 15.4 Rest of North America Agentic AI In Cybersecurity Market
- 15.4.1 Rest of North America Agentic AI In Cybersecurity Market by Component
- 15.4.2 Rest of North America Agentic AI In Cybersecurity Market by Application
- 15.4.3 Rest of North America Agentic AI In Cybersecurity Market by Deployment
- 15.4.4 Rest of North America Agentic AI In Cybersecurity Market by End Use
- Chapter 16. Company Profiles
- 16.1 Crowdstrike Holdings, Inc.
- 16.1.1 Company Overview
- 16.1.2 Financial Analysis
- 16.1.3 Regional Analysis
- 16.1.4 Research & Development Expenses
- 16.1.5 Recent strategies and developments:
- 16.1.5.1 Partnerships, Collaborations, and Agreements:
- 16.1.5.2 Product Launches and Product Expansions:
- 16.1.6 SWOT Analysis
- 16.2 Palo Alto Networks, Inc.
- 16.2.1 Company Overview
- 16.2.2 Financial Analysis
- 16.2.3 Regional Analysis
- 16.2.4 Research & Development Expense
- 16.2.5 Recent strategies and developments:
- 16.2.5.1 Partnerships, Collaborations, and Agreements:
- 16.2.5.2 Acquisition and Mergers:
- 16.2.6 SWOT Analysis
- 16.3 Microsoft Corporation
- 16.3.1 Company Overview
- 16.3.2 Financial Analysis
- 16.3.3 Segmental and Regional Analysis
- 16.3.4 Research & Development Expenses
- 16.3.5 Recent strategies and developments:
- 16.3.5.1 Partnerships, Collaborations, and Agreements:
- 16.3.6 SWOT Analysis
- 16.4 IBM Corporation
- 16.4.1 Company Overview
- 16.4.2 Financial Analysis
- 16.4.3 Regional & Segmental Analysis
- 16.4.4 Research & Development Expenses
- 16.4.5 Recent strategies and developments:
- 16.4.5.1 Product Launches and Product Expansions:
- 16.4.6 SWOT Analysis
- 16.5 Darktrace Holdings Limited
- 16.5.1 Company Overview
- 16.5.2 Recent strategies and developments:
- 16.5.2.1 Product Launches and Product Expansions:
- 16.5.2.2 Acquisition and Mergers:
- 16.6 Google LLC
- 16.6.1 Company Overview
- 16.6.2 Financial Analysis
- 16.6.3 Segmental and Regional Analysis
- 16.6.4 Research & Development Expenses
- 16.6.5 Recent strategies and developments:
- 16.6.5.1 Product Launches and Product Expansions:
- 16.6.6 SWOT Analysis
- 16.7 Anthropic PBC
- 16.7.1 Company Overview
- 16.8 Salesforce, Inc.
- 16.8.1 Company Overview
- 16.8.2 Financial Analysis
- 16.8.3 Regional Analysis
- 16.8.4 Research & Development Expenses
- 16.8.5 SWOT Analysis
- 16.9 NVIDIA Corporation
- 16.9.1 Company Overview
- 16.9.2 Financial Analysis
- 16.9.3 Segmental and Regional Analysis
- 16.9.4 Research & Development Expenses
- 16.9.5 Recent strategies and developments:
- 16.9.5.1 Product Launches and Product Expansions:
- 16.9.6 SWOT Analysis
- 16.10. SentinelOne, Inc.
- 16.10.1 Company Overview
- 16.10.2 Recent strategies and developments:
- 16.10.2.1 Partnerships, Collaborations, and Agreements:
- 16.10.2.2 Product Launches and Product Expansions:
- 16.10.2.3 Acquisition and Mergers:
- 16.10.3 SWOT Analysis
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