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市場調查報告書
商品編碼
2059127

人工智慧驅動的威脅情報市場預測至2034年：按組件、安全類型、部署模式、組織規模、最終用戶和地區分類的全球分析

AI-Powered Threat Intelligence Market Forecasts to 2034 - Global Analysis By Component (Solutions and Services), Security Type, Deployment Mode, Organization Size, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球人工智慧驅動的威脅情報市場預計將在 2026 年達到 72 億美元，在預測期內以 19.5% 的複合年成長率成長，到 2034 年達到 301 億美元。

人工智慧驅動的威脅情報是指利用人工智慧 (AI) 和機器學習技術即時收集、分析和解讀網路安全威脅資料。這使組織能夠更準確、更快速地識別惡意活動、偵測新興攻擊模式並預測潛在的安全漏洞。透過自動化處理來自網路、終端、雲端系統和外部威脅情報來源的大規模數據，人工智慧驅動的威脅情報能夠增強主動防禦策略，最大限度地縮短響應時間，並提升企業IT基礎設施、關鍵產業和數位生態系統的風險緩解能力。

勒索軟體和國家支持的威脅日益加劇

勒索軟體攻擊日益頻繁、手段愈加複雜，經濟影響也急劇擴大，加之國家支持的網路間諜活動和針對關鍵基礎設施、供應鏈和政府網路的破壞性攻擊宣傳活動日益增多，迫使各行各業的組織機構投資於人工智慧驅動的威脅情報能力。這是因為，與使用傳統威脅情報工具的人工分析團隊相比，人工智慧能夠更快地偵測並應對複雜且持續存在的威脅，而人工分析團隊需要手動處理當今企業安全環境中產生的大量威脅訊號。

誤報造成的疲勞負擔

基於不完整或不具代表性的威脅資料訓練的人工智慧威脅偵測模型會產生較高的誤報率，導致安全營運中心 (SOC) 分析師出現警報疲勞。分析師必須同時調查和檢驗機器產生的威脅警報以及真實的安全事件，而諷刺的是，當誤報數量超過分析師的處理能力時，人工智慧威脅情報部署的實際安全價值反而會降低，使他們無法及時處理真正重要的警報。隨著企業網路環境的演變、新型雲端服務的引入以及合法用戶行為模式的改變，準確維護威脅偵測模型的效能變得越來越困難，需要不斷地重新訓練和調整閾值。這導致持續的營運投入超過了初始平台部署成本。

利用人工智慧生成實現自動化保全行動

將大規模語言模型 (LLM) 的功能整合到人工智慧威脅情報平台中，可以實現基於自然語言的安全事件調查、自動生成威脅報告、人工智慧驅動的惡意軟體逆向工程以及智慧安全劇本的執行。這在無需相應增加人員的情況下，並顯著提升了保全行動團隊的分析能力。已部署生成式人工智慧威脅分析功能的安全營運中心報告稱，偵測和回應安全事件的平均時間顯著縮短。這是因為人工智慧系統能夠自主執行諸如初步分類、證據收集和上下文增強等任務，而這些任務以往需要分析師花費大量時間才能啟動實質調查。

敵對人工智慧規避技術的擴散

包括國家支持的駭客組織和高度發達的犯罪組織在內的老練威脅行為者，正在積極開發和部署對抗性機器學習技術，例如用於惡意軟體變異、多態程式碼生成和人工智慧驅動的行為模仿的生成對抗網路（GAN），這些技術旨在規避人工智慧偵測系統。這導致了一場日益激烈的技術軍備競賽，防禦者必須不斷提升自身的人工智慧能力，以應對攻擊者在人工智慧規避技術方面的創新。

新冠疫情的感染疾病：

疫情期間遠距辦公的普及，透過大規模部署VPN、個人裝置存取企業網路以及快速雲端遷移，顯著擴大了企業的攻擊面。因此，網路安全事件數量激增，令傳統的保全行動能力不堪負荷。這也加速了人工智慧威脅偵測的應用，以增強那些面臨人員短缺的安全團隊的能力。針對醫療保健產業和關鍵基礎設施的網路攻擊，利用了疫情造成的混亂局面，凸顯了威脅情報能力不足對國家安全的影響，促使各國政府加快網路安全投資計畫。

在預測期內，服務業預計將佔據最大的市場佔有率。

預計在預測期內，服務領域將佔據最大的市場佔有率。這主要得益於市場對託管檢測與響應 (MDR) 服務的強勁且不斷成長的需求。這類服務將人工智慧驅動的威脅情報平台與專家安全分析師提供的全天候監控相結合，為中小企業提供安全營運中心 (SOC) 的功能，而這些功能在企業內部建構和營運成本較高。提供人工智慧威脅情報、端點偵測與回應 (EDR) 以及安全資訊和事件管理 (SIEM) 等託管服務的保全服務供應商 (MSSP) 的訂閱服務，能夠為企業客戶帶來可預測且穩定的經常性收入。這些企業客戶希望獲得全面的安全保障，但又不想投資建置內部保全行動。

網路安全產業預計在預測期內將呈現最高的複合年成長率。

在預測期內，網路安全領域預計將呈現最高的成長率。這主要是由於混合企業網路（涵蓋本地、多重雲端和營運技術 (OT) 環境）的網路流量日益複雜且規模龐大，需要藉助人工智慧 (AI) 分析來偵測高階橫向機芯、命令與控制通訊、資料竊取嘗試以及繞過基於特徵碼偵測的零日攻擊流量。能夠對加密網路流量進行行為分析的 AI 網路偵測與回應平台，彌補了 TLS 加密廣泛應用所造成的偵測缺口。由於缺乏解密開銷，傳統的深層封包檢測在威脅偵測的有效性有所降低。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率。這主要是由於針對美國組織的網路攻擊頻發，以及帕洛阿爾托網路公司 (Palo Alto Networks Inc.)、CrowdStrike Holdings Inc. 和 Darktrace plc 等領先的人工智慧威脅情報平台供應商集中於此。預計這些供應商將帶來全球最高的企業網路安全支出和最大的商業市場總收入。美國聯邦政府基於《加強國家網路安全行政命令》的網路安全現代化計劃，要求在私營部門網路中部署先進的威脅偵測能力，這使得人工智慧威脅情報成為公共部門採購的關鍵議題。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率。這主要是由於針對亞太地區組織的網路威脅活動迅速加劇，以及新加坡、澳洲、日本、韓國和印度等國的國家網路安全戰略計畫推動了企業網路安全投資的增加。這些計劃制定了強制性安全標準，促進了受監管行業採用人工智慧威脅情報。澳洲的《關鍵基礎設施安全法》和新加坡的《網路安全法》對關鍵基礎設施營運商提出了更高的安全要求，推動了通訊、能源、金融和醫療保健等產業強制採購威脅情報能力。

免費客製化服務：

所有購買此報告的客戶均可享受以下免費自訂選項之一：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要公司進行SWOT分析（最多3家公司）
  • 區域細分
    • 應客戶要求，我們提供主要國家的市場估算和預測，以及複合年成長率（註：需進行可行性檢查）。
  • 競爭性標竿分析
    • 根據產品系列、地理覆蓋範圍和策略聯盟對領先公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧驅動的威脅情報市場：按組件分類

  • 解決方案
  • 服務

第6章：全球人工智慧驅動的威脅情報市場：依安全類型分類

  • 網路安全
  • 雲端安全
  • 端點安全
  • 應用程式安全
  • 資料安全
  • 身分安全

第7章：全球人工智慧驅動的威脅情報市場：依部署模式分類

  • 現場
  • 基於雲端的
  • 混合

第8章：全球人工智慧驅動的威脅情報市場：按組織規模分類

  • 大公司
  • 中小企業

第9章：全球人工智慧驅動的威脅情報市場：按最終用戶分類

  • 銀行、金融服務和保險（BFSI）
  • 政府/國防
  • 醫療保健和生命科學
  • 資訊科技/通訊
  • 零售與電子商務
  • 能源公用事業
  • 製造業
  • 媒體與娛樂

第10章：全球人工智慧驅動的威脅情報市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第11章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第12章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第13章：公司簡介

  • Palo Alto Networks Inc.
  • CrowdStrike Holdings Inc.
  • Fortinet Inc.
  • Check Point Software Technologies Ltd.
  • Cisco Systems Inc.
  • IBM Corporation
  • Microsoft Corporation
  • Broadcom Inc.（Symantec）
  • Trend Micro Incorporated
  • McAfee Corp.
  • Darktrace plc
  • SentinelOne Inc.
  • FireEye Inc.（Mandiant）
  • Splunk Inc.
  • Rapid7 Inc.
  • Google LLC（Alphabet Inc.）
  • Amazon Web Services Inc.
  • Oracle Corporation
Product Code: SMRC36645

According to Stratistics MRC, the Global AI-Powered Threat Intelligence Market is accounted for $7.2 billion in 2026 and is expected to reach $30.1 billion by 2034 growing at a CAGR of 19.5% during the forecast period. AI-powered threat intelligence refers to the use of artificial intelligence and machine learning technologies to collect, analyze, and interpret cybersecurity threat data in real time. It enables organizations to identify malicious activities, detect emerging attack patterns, and predict potential security breaches with greater accuracy and speed. By automating large-scale data processing from networks, endpoints, cloud systems, and external threat feeds, AI-powered threat intelligence enhances proactive defense strategies, minimizes response times, and strengthens risk mitigation capabilities across enterprise IT infrastructures, critical industries, and digital ecosystems.

Market Dynamics:

Driver:

Ransomware and nation-state threat escalation

Dramatic escalation in ransomware attack frequency, sophistication, and financial impact combined with increasing nation-state sponsored cyber espionage and destructive attack campaigns targeting critical infrastructure, supply chains, and government networks is compelling organizations across all sectors to invest in AI-powered threat intelligence capabilities that can detect and respond to advanced persistent threats faster than human analyst teams working with traditional threat intelligence tools can manually process the volume of threat signals generated by modern enterprise security environments.

Restraint:

False positive alert fatigue burden

High false positive rates generated by AI threat detection models trained on incomplete or unrepresentative threat data create alert fatigue among security operations center analysts who must investigate and validate machine-generated threat alerts alongside genuine security incidents, paradoxically reducing the effective security value of AI threat intelligence deployments when false positive volumes overwhelm analyst capacity to process legitimate high-priority alerts. The difficulty of maintaining accurate threat detection model performance as enterprise network environments evolve, new cloud services are adopted, and legitimate user behavior patterns shift requires continuous model retraining and threshold calibration that imposes ongoing operational investment beyond initial platform deployment costs.

Opportunity:

Generative AI security operations automation

Integration of large language model capabilities into AI threat intelligence platforms is enabling natural language security incident investigation, automated threat report generation, AI-assisted malware reverse engineering, and intelligent security playbook execution that dramatically expands the analytical capacity of security operations teams without proportional headcount increases. Security operations centers deploying generative AI threat analysis capabilities report significant reductions in mean time to detect and respond to security incidents as AI systems autonomously perform initial triage, evidence collection, and contextual enrichment tasks that previously consumed analyst time before substantive investigation could begin.

Threat:

Adversarial AI evasion technique proliferation

Sophisticated threat actors, including nation-state hacking groups and advanced criminal organizations, are actively developing and deploying adversarial machine learning techniques, including generative adversarial network-powered malware mutation, polymorphic code generation, and AI-driven behavioral mimicry specifically engineered to evade AI-powered detection systems, creating an accelerating technological arms race where defensive AI capabilities must continuously evolve to counter offensive AI evasion innovation.

Covid-19 Impact:

Pandemic-driven remote work expansion dramatically increased enterprise attack surfaces through mass VPN deployment, personal device corporate access, and rapid cloud migration, creating surging cybersecurity incident volumes that overwhelmed traditional security operations capabilities and accelerated AI-powered threat detection adoption as a force multiplier for understaffed security teams. Healthcare and critical infrastructure cyber attacks exploiting pandemic disruptions demonstrated the national security consequences of inadequate threat intelligence capabilities, driving emergency government cybersecurity investment programs.

The services segment is expected to be the largest during the forecast period

The services segment is expected to account for the largest market share during the forecast period, due to the strong and growing demand for managed detection and response services, combining AI-powered threat intelligence platforms with 24/7 expert security analyst coverage that provides small and medium enterprises with the security operations center capabilities they cannot build and staff internally at a viable cost. Managed security service provider subscriptions delivering AI threat intelligence, endpoint detection and response, and security information and event management as bundled managed services generate predictable high-retention recurring revenue from enterprise customers seeking comprehensive security coverage without internal security operations investment.

The network security segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the network security segment is predicted to witness the highest growth rate, driven by the expanding complexity and volume of network traffic requiring AI-powered analysis to detect sophisticated lateral movement, command-and-control communications, data exfiltration attempts, and zero-day exploit traffic that evade signature-based detection across hybrid enterprise networks spanning on-premises, multi-cloud, and operational technology environments simultaneously. AI network detection and response platforms providing behavioral analytics across encrypted network traffic are addressing the detection gap created by universal TLS encryption adoption that rendered traditional deep packet inspection less effective for threat detection without decryption overhead.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to the highest enterprise cybersecurity spending globally, driven by extensive regulatory compliance requirements, high cyber attack frequency targeting United States organizations, and concentration of leading AI-powered threat intelligence platform vendors, including Palo Alto Networks Inc., CrowdStrike Holdings Inc., and Darktrace plc, generating the largest aggregate commercial market revenue. United States federal government cybersecurity modernization programs under the Executive Order on Improving the Nation's Cybersecurity, mandating the deployment of advanced threat detection capabilities across civilian agency networks, represent significant public sector AI threat intelligence procurement.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, due to rapidly escalating cyber threat activity targeting Asia Pacific organizations, combined with growing enterprise cybersecurity investment driven by national cybersecurity strategy programs in Singapore, Australia, Japan, South Korea, and India, establishing mandatory security standards that are driving AI threat intelligence adoption across regulated industries. Australia's Security of Critical Infrastructure Act and Singapore's Cybersecurity Act, establishing enhanced security requirements for critical infrastructure operators, are driving mandatory threat intelligence capability procurement across telecommunications, energy, finance, and healthcare sectors.

Key players in the market

Some of the key players in AI-Powered Threat Intelligence Market include Palo Alto Networks Inc., CrowdStrike Holdings Inc., Fortinet Inc., Check Point Software Technologies Ltd., Cisco Systems Inc., IBM Corporation, Microsoft Corporation, Broadcom Inc. (Symantec), Trend Micro Incorporated, McAfee Corp., Darktrace plc, SentinelOne Inc., FireEye Inc. (Mandiant), Splunk Inc., Rapid7 Inc., Google LLC (Alphabet Inc.), Amazon Web Services Inc., and Oracle Corporation.

Key Developments:

In April 2026, Microsoft Corporation announced enhanced Microsoft Sentinel AI threat intelligence integration with Security Copilot, providing automated threat actor attribution and campaign tracking for enterprise security operations teams managing hybrid cloud environments.

In March 2026, Darktrace plc expanded its Cyber AI Loop platform with proactive threat exposure management capabilities, enabling organizations to simulate adversary attack paths against their specific network topology before active exploitation occurs.

In February 2026, Palo Alto Networks Inc. released Cortex XSIAM 3.0 with autonomous AI-powered security operations center capabilities, reducing mean time to respond for critical incidents through automated investigation, containment, and remediation playbook execution.

Components Covered:

  • Solutions
  • Services

Security Types Covered:

  • Network Security
  • Cloud Security
  • Endpoint Security
  • Application Security
  • Data Security
  • Identity Security

Deployment Modes Covered:

  • On-Premises
  • Cloud-Based
  • Hybrid

Organization Sizes Covered:

  • Large Enterprises
  • Small & Medium Enterprises (SMEs)

End Users Covered:

  • Banking, Financial Services & Insurance (BFSI)
  • Government & Defense
  • Healthcare & Life Sciences
  • IT & Telecommunications
  • Retail & E-Commerce
  • Energy & Utilities
  • Manufacturing
  • Media & Entertainment

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI-Powered Threat Intelligence Market, By Component

  • 5.1 Solutions
  • 5.2 Services

6 Global AI-Powered Threat Intelligence Market, By Security Type

  • 6.1 Network Security
  • 6.2 Cloud Security
  • 6.3 Endpoint Security
  • 6.4 Application Security
  • 6.5 Data Security
  • 6.6 Identity Security

7 Global AI-Powered Threat Intelligence Market, By Deployment Mode

  • 7.1 On-Premises
  • 7.2 Cloud-Based
  • 7.3 Hybrid

8 Global AI-Powered Threat Intelligence Market, By Organization Size

  • 8.1 Large Enterprises
  • 8.2 Small & Medium Enterprises (SMEs)

9 Global AI-Powered Threat Intelligence Market, By End User

  • 9.1 Banking, Financial Services & Insurance (BFSI)
  • 9.2 Government & Defense
  • 9.3 Healthcare & Life Sciences
  • 9.4 IT & Telecommunications
  • 9.5 Retail & E-Commerce
  • 9.6 Energy & Utilities
  • 9.7 Manufacturing
  • 9.8 Media & Entertainment

10 Global AI-Powered Threat Intelligence Market, By Geography

  • 10.1 North America
    • 10.1.1 United States
    • 10.1.2 Canada
    • 10.1.3 Mexico
  • 10.2 Europe
    • 10.2.1 United Kingdom
    • 10.2.2 Germany
    • 10.2.3 France
    • 10.2.4 Italy
    • 10.2.5 Spain
    • 10.2.6 Netherlands
    • 10.2.7 Belgium
    • 10.2.8 Sweden
    • 10.2.9 Switzerland
    • 10.2.10 Poland
    • 10.2.11 Rest of Europe
  • 10.3 Asia Pacific
    • 10.3.1 China
    • 10.3.2 Japan
    • 10.3.3 India
    • 10.3.4 South Korea
    • 10.3.5 Australia
    • 10.3.6 Indonesia
    • 10.3.7 Thailand
    • 10.3.8 Malaysia
    • 10.3.9 Singapore
    • 10.3.10 Vietnam
    • 10.3.11 Rest of Asia Pacific
  • 10.4 South America
    • 10.4.1 Brazil
    • 10.4.2 Argentina
    • 10.4.3 Colombia
    • 10.4.4 Chile
    • 10.4.5 Peru
    • 10.4.6 Rest of South America
  • 10.5 Rest of the World (RoW)
    • 10.5.1 Middle East
      • 10.5.1.1 Saudi Arabia
      • 10.5.1.2 United Arab Emirates
      • 10.5.1.3 Qatar
      • 10.5.1.4 Israel
      • 10.5.1.5 Rest of Middle East
    • 10.5.2 Africa
      • 10.5.2.1 South Africa
      • 10.5.2.2 Egypt
      • 10.5.2.3 Morocco
      • 10.5.2.4 Rest of Africa

11 Strategic Market Intelligence

  • 11.1 Industry Value Network and Supply Chain Assessment
  • 11.2 White-Space and Opportunity Mapping
  • 11.3 Product Evolution and Market Life Cycle Analysis
  • 11.4 Channel, Distributor, and Go-to-Market Assessment

12 Industry Developments and Strategic Initiatives

  • 12.1 Mergers and Acquisitions
  • 12.2 Partnerships, Alliances, and Joint Ventures
  • 12.3 New Product Launches and Certifications
  • 12.4 Capacity Expansion and Investments
  • 12.5 Other Strategic Initiatives

13 Company Profiles

  • 13.1 Palo Alto Networks Inc.
  • 13.2 CrowdStrike Holdings Inc.
  • 13.3 Fortinet Inc.
  • 13.4 Check Point Software Technologies Ltd.
  • 13.5 Cisco Systems Inc.
  • 13.6 IBM Corporation
  • 13.7 Microsoft Corporation
  • 13.8 Broadcom Inc. (Symantec)
  • 13.9 Trend Micro Incorporated
  • 13.10 McAfee Corp.
  • 13.11 Darktrace plc
  • 13.12 SentinelOne Inc.
  • 13.13 FireEye Inc. (Mandiant)
  • 13.14 Splunk Inc.
  • 13.15 Rapid7 Inc.
  • 13.16 Google LLC (Alphabet Inc.)
  • 13.17 Amazon Web Services Inc.
  • 13.18 Oracle Corporation

List of Tables

  • Table 1 Global AI-Powered Threat Intelligence Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI-Powered Threat Intelligence Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI-Powered Threat Intelligence Market Outlook, By Solutions (2023-2034) ($MN)
  • Table 4 Global AI-Powered Threat Intelligence Market Outlook, By Services (2023-2034) ($MN)
  • Table 5 Global AI-Powered Threat Intelligence Market Outlook, By Security Type (2023-2034) ($MN)
  • Table 6 Global AI-Powered Threat Intelligence Market Outlook, By Network Security (2023-2034) ($MN)
  • Table 7 Global AI-Powered Threat Intelligence Market Outlook, By Cloud Security (2023-2034) ($MN)
  • Table 8 Global AI-Powered Threat Intelligence Market Outlook, By Endpoint Security (2023-2034) ($MN)
  • Table 9 Global AI-Powered Threat Intelligence Market Outlook, By Application Security (2023-2034) ($MN)
  • Table 10 Global AI-Powered Threat Intelligence Market Outlook, By Data Security (2023-2034) ($MN)
  • Table 11 Global AI-Powered Threat Intelligence Market Outlook, By Identity Security (2023-2034) ($MN)
  • Table 12 Global AI-Powered Threat Intelligence Market Outlook, By Deployment Mode (2023-2034) ($MN)
  • Table 13 Global AI-Powered Threat Intelligence Market Outlook, By On-Premises (2023-2034) ($MN)
  • Table 14 Global AI-Powered Threat Intelligence Market Outlook, By Cloud-Based (2023-2034) ($MN)
  • Table 15 Global AI-Powered Threat Intelligence Market Outlook, By Hybrid (2023-2034) ($MN)
  • Table 16 Global AI-Powered Threat Intelligence Market Outlook, By Organization Size (2023-2034) ($MN)
  • Table 17 Global AI-Powered Threat Intelligence Market Outlook, By Large Enterprises (2023-2034) ($MN)
  • Table 18 Global AI-Powered Threat Intelligence Market Outlook, By Small & Medium Enterprises (SMEs) (2023-2034) ($MN)
  • Table 19 Global AI-Powered Threat Intelligence Market Outlook, By End User (2023-2034) ($MN)
  • Table 20 Global AI-Powered Threat Intelligence Market Outlook, By Banking, Financial Services & Insurance (BFSI) (2023-2034) ($MN)
  • Table 21 Global AI-Powered Threat Intelligence Market Outlook, By Government & Defense (2023-2034) ($MN)
  • Table 22 Global AI-Powered Threat Intelligence Market Outlook, By Healthcare & Life Sciences (2023-2034) ($MN)
  • Table 23 Global AI-Powered Threat Intelligence Market Outlook, By IT & Telecommunications (2023-2034) ($MN)
  • Table 24 Global AI-Powered Threat Intelligence Market Outlook, By Retail & E-Commerce (2023-2034) ($MN)
  • Table 25 Global AI-Powered Threat Intelligence Market Outlook, By Energy & Utilities (2023-2034) ($MN)
  • Table 26 Global AI-Powered Threat Intelligence Market Outlook, By Manufacturing (2023-2034) ($MN)
  • Table 27 Global AI-Powered Threat Intelligence Market Outlook, By Media & Entertainment (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.