AI Usage in Security Operations, Global, 2025–2030
Description
Security operations are evolving rapidly as organizations face increasingly complex and dynamic threats across physical, identity, and cyber domains. Traditional approaches often struggle to keep pace with the scale and sophistication of modern attacks, leading to alert fatigue, delayed responses, and operational inefficiencies that compromise resilience.
AI introduces a transformative capability by enabling proactive threat detection, contextual analysis, and automated response workflows. Through ML, natural language processing, and advanced analytics, AI enhances visibility, accelerates incident resolution, and supports human decision-making with actionable insights for both routine and high-risk scenarios.
This report examines how AI is being applied in security operations centers (SOCs), integrated command-and-control environments, and enterprise security frameworks. It explores key use cases, including anomaly detection, identity verification, predictive threat modeling, and orchestration of automated playbooks. By leveraging AI-driven tools and adaptive architectures, organizations can achieve a more scalable, resilient, and future-ready security posture—reducing risk while improving efficiency and compliance.
AI introduces a transformative capability by enabling proactive threat detection, contextual analysis, and automated response workflows. Through ML, natural language processing, and advanced analytics, AI enhances visibility, accelerates incident resolution, and supports human decision-making with actionable insights for both routine and high-risk scenarios.
This report examines how AI is being applied in security operations centers (SOCs), integrated command-and-control environments, and enterprise security frameworks. It explores key use cases, including anomaly detection, identity verification, predictive threat modeling, and orchestration of automated playbooks. By leveraging AI-driven tools and adaptive architectures, organizations can achieve a more scalable, resilient, and future-ready security posture—reducing risk while improving efficiency and compliance.
Table of Contents
66 Pages
- Growth Environment: Transformation in the AI Usage in Security Operations Sector
- Why is it Increasingly Difficult to Grow?
- The Strategic Imperative 8™
- The Impact of the Top 3 Strategic Imperatives of the AI Usage in Security Operations Industry
- Growth Opportunity Analysis
- Scope of Analysis
- Technology Vertical Segmentation
- Introduction to AI Technologies in Security Operations
- Foundational Capabilities Enabled by AI in Security Operations
- Example Applications of AI Technologies in Security Operations
- Regulations Governing for AI in Security Operations
- AI Architecture Integration Within Security Operations
- AI Architecture Within Security Operations Discussion
- Growth Drivers
- Growth Restraints
- Growth Generator: Physical Security
- AI Usage Within Physical Security Operations
- AI Usage Within Physical Security—Application Areas
- AI Usage Within Physical Security—Executive Priorities
- AI Usage Within Physical Security—Key Challenges and Solutions
- Use Case 1—Axis Communications—Moving Beyond the AI Hype in Security
- Use Case 2—AI-Powered Physical Security Innovations Across Critical Infrastructure
- AI Usage in Physical Security—Current and Future Applications
- AI Usage in Physical Security—Key Solution Providers
- Growth Generator: Identity Security
- AI Usage Within Identity Security
- AI Usage Within Identity Security—Application Areas
- AI Usage within Identity Security—Executive Priorities
- AI Usage within Identity Security—Key Challenges and Solutions
- Use Case 1—Transforming Identity and Access Control with Generative AI
- Use Case 2—AI-Driven Contextual Authentication in Enterprise Security
- AI Usage in Identity Security—Current and Future Applications
- AI Usage in Identity Security—Key Solution Providers
- Growth Generator: Cybersecurity
- AI Usage Within Cybersecurity
- AI Usage Within Cybersecurity—Application Areas
- AI Usage Within Cybersecurity—Executive Priorities
- AI Usage Within Cybersecurity—Key Challenges and Solutions
- Use Case 1—Lenovo—Embedding AI-Powered Cybersecurity into Endpoint Devices
- Use Case 2—Securing AI Workloads with Zero Trust and Runtime Protection
- AI Usage in Cybersecurity—Current and Future Applications
- AI Usage in Cybersecurity—Key Solution Providers
- Growth Opportunity Universe
- Growth Opportunity 1: AI Agents
- Growth Opportunity 2: Insider Risk Management
- Growth Opportunity 3: Converged Physical-Cyber Security Platforms (Unified Security Intelligence)
- Benefits and Impacts of Growth Opportunities
- Next Steps
- Legal Disclaimer
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