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市場調查報告書
商品編碼
1953319

人工智慧在全球保全行動的應用，2025-2030 年

AI Usage in Security Operations, Global, 2025-2030
出版日期: | 出版商: Frost & Sullivan | 英文 66 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

特定任務人工智慧系統的整合將透過統一的工作流程和自適應即時決策來推動變革性成長。

隨著企業面臨來自實體、身分和網路領域的日益複雜和動態的威脅，保全行動也迅速演變。傳統方法往往難以應對現代攻擊的規模和複雜性，導致警報疲勞、反應時間延長、營運效率降低以及韌性下降。

人工智慧透過實現主動威脅偵測、情境分析和自動化回應工作流程，帶來變革性的能力。借助機器學習、自然語言處理和高級分析技術，人工智慧能夠提高可視性，加快事件解決速度，並在日常和高風險場景中提供可操作的洞察，從而支援人類決策。

本報告檢驗了人工智慧在安全營運中心 (SOC)、統一指揮控制環境和企業安全框架中的應用。報告重點分析了異常檢測、身份驗證、預測性威脅建模和自動化劇本編配等關鍵用例。透過利用人工智慧驅動的工具和自適應架構，企業可以建立更具擴充性、彈性和麵向未來的安全態勢，從而在提高效率和合規性的同時降低風險。

目錄

成長環境：人工智慧在保全行動營運的應用轉型

  • 為什麼經濟成長變得越來越困難？
  • The Strategic Imperative 8(TM)
  • 人工智慧在保全行動產業中應用的三大策略要務的影響

成長機會分析

  • 分析範圍
  • 依技術領域分類
  • 在保全行動中引入人工智慧技術
  • 人工智慧在保全行動中實現的基本功能
  • 人工智慧技術在保全行動中的應用範例
  • 規範人工智慧在保全行動中法規
  • 將人工智慧架構整合到保全行動中
  • 保全行動中人工智慧架構的考量
  • 成長要素
  • 成長限制阻礙因素

成長動力：實體安全

  • 在實體保全行動中運用人工智慧
  • 人工智慧在實體安全領域的應用—應用領域
  • 人工智慧在實體安全領域的應用：經營團隊優先考慮的事項
  • 人工智慧在實體安全領域的應用：關鍵挑戰與解決方案
  • 用例 1 - Axis Communications - 超越安全領域人工智慧的炒作
  • 用例 2 - 利用人工智慧改造關鍵基礎設施的實體安全
  • 人工智慧在實體安全的應用—當前及未來應用領域
  • 人工智慧在實體安全的應用—領先的解決方案供應商

成長來源：身分安全

  • 身份安全領域的人工智慧
  • 人工智慧在身分安全領域的應用—應用領域
  • 在身分安全領域利用人工智慧：經營團隊的優先事項
  • 身份安全領域的人工智慧：關鍵挑戰與解決方案
  • 用例 1 - 利用生成式人工智慧變革身分和存取控制
  • 用例 2 - 企業安全性中基於 AI 的情境驗證
  • 人工智慧在身分安全領域的應用—目前及未來應用領域
  • 利用人工智慧實現身分安全——領先的解決方案供應商

成長泉源：網路安全

  • 人工智慧在網路安全領域的應用
  • 人工智慧在網路安全的應用—應用領域
  • 網路安全領域的人工智慧：經營團隊優先考慮的事項
  • 人工智慧在網路安全的應用：關鍵挑戰與解決方案
  • 用例 1 - 聯想 - 將 AI 驅動的網路安全嵌入終端設備
  • 用例 2 - 使用零信任和運行時保護來保護 AI 工作負載
  • 人工智慧在網路安全領域的應用—當前及未來應用領域
  • 網路安全領域的人工智慧——領先的解決方案供應商

成長機會領域

  • 成長機會 1：人工智慧代理
  • 成長機會二：內部風險管理
  • 成長機會 3：實體和網路安全整合平台（整合安全智慧）
  • 成長機會帶來的益處和影響
  • 下一步
  • 免責聲明
簡介目錄
Product Code: PG3Y-23

Integration of Task-Specific AI Systems is Driving Transformational Growth Due to Unified Workflows and Adaptive, Real-Time Decision-Making

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.

Table of Contents

Growth Environment: Transformation in the AI Usage in Security Operations Sector

  • Why is it Increasingly Difficult to Grow?
  • The Strategic Imperative 8(TM)
  • 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