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封面
市场调查报告书
商品编码
1953319

人工智慧在全球保全行动的应用，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个工作天内

价格
简介目录

特定任务人工智慧系统的整合将透过统一的工作流程和自适应即时决策来推动变革性成长。

随着企业面临来自实体、身分和网路领域的日益复杂和动态的威胁，保全行动也迅速演变。传统方法往往难以应对现代攻击的规模和复杂性，导致警报疲劳、反应时间延长、营运效率降低以及韧性下降。

人工智慧透过实现主动威胁侦测、情境分析和自动化回应工作流程，带来变革性的能力。借助机器学习、自然语言处理和高级分析技术，人工智慧能够提高可视性，加快事件解决速度，并在日常和高风险场景中提供可操作的洞察，从而支援人类决策。

本报告检验了人工智慧在安全营运中心 (SOC)、统一指挥控制环境和企业安全框架中的应用。报告重点分析了异常检测、身份验证、预测性威胁建模和自动化剧本编配等关键用例。透过利用人工智慧驱动的工具和自适应架构，企业可以建立更具扩充性、弹性和麵向未来的安全态势，从而在提高效率和合规性的同时降低风险。

目录

成长环境：人工智慧在保全行动营运的应用转型

  • 为什么经济成长变得越来越困难？
  • The Strategic Imperative 8(TM)
  • 人工智慧在保全行动产业中应用的三大策略要务的影响

成长机会分析

  • 分析范围
  • 依技术领域划分
  • 在保全行动中引入人工智慧技术
  • 人工智慧在保全行动中实现的基本功能
  • 人工智慧技术在保全行动中的应用范例
  • 规范人工智慧在保全行动中法规
  • 将人工智慧架构整合到保全行动中
  • 保全行动中人工智慧架构的考量
  • 成长要素
  • 成长限制阻碍因素

成长动力：实体安全

  • 在实体保全行动中运用人工智慧
  • 人工智慧在实体安全领域的应用—应用领域
  • 人工智慧在实体安全领域的应用：经营团队优先考虑的事项
  • 人工智慧在实体安全领域的应用：关键挑战与解决方案
  • 用例 1 - Axis Communications - 超越安全领域人工智慧的炒作
  • 用例 2 - 利用人工智慧改造关键基础设施的实体安全
  • 人工智慧在实体安全的应用—当前及未来应用领域
  • 人工智慧在实体安全的应用—领先的解决方案供应商

成长来源：身分安全

  • 身份安全领域的人工智慧
  • 人工智慧在身分安全领域的应用—应用领域
  • 在身分安全领域利用人工智慧：经营团队的优先事项
  • 身份安全领域的人工智慧：关键挑战与解决方案
  • 用例 1 - 利用生成式人工智慧变革身分和存取控制
  • 用例 2 - 企业安全性中基于 AI 的情境验证
  • 人工智慧在身分安全领域的应用—目前及未来应用领域
  • 利用人工智慧实现身分安全——领先的解决方案供应商

成长泉源：网路安全

  • 人工智慧在网路安全领域的应用
  • 人工智慧在网路安全的应用—应用领域
  • 网路安全领域的人工智慧：经营团队优先考虑的事项
  • 人工智慧在网路安全的应用：关键挑战与解决方案
  • 用例 1 - 联想 - 将 AI 驱动的网路安全嵌入终端设备
  • 用例 2 - 使用零信任和运行时保护来保护 AI 工作负载
  • 人工智慧在网路安全领域的应用—当前及未来应用领域
  • 网路安全领域的人工智慧——领先的解决方案供应商

成长机会领域

  • 成长机会 1：人工智慧代理
  • 成长机会二：内部风险管理
  • 成长机会 3：实体和网路安全整合平台（整合安全智慧）
  • 成长机会带来的益处和影响
  • 下一步
  • 免责声明
简介目录
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