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市場調查報告書
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2170043

人工智慧安全態勢管理市場預測至2034年－全球分析（按組件、安全功能、部署模式、人工智慧環境、最終用戶和區域分類）

AI Security Posture Management Market Forecasts to 2034 - Global Analysis By Component (Software, Services), Security Capability, Deployment Mode, AI Environment, End User, and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球 AI 安全態勢管理市場預計將在 2026 年達到 10 億美元，並在預測期內以 5.2% 的複合年成長率成長，到 2034 年達到 15 億美元。

人工智慧安全態勢管理 (AI-SPM) 指的是幫助組織識別人工智慧資產、評估安全風險、精確定位配置錯誤、監控管治和合規性以及保護人工智慧模型、應用程式、資料和支援基礎設施的技術和服務。該市場涵蓋透過雲端、本地部署和混合部署模式交付的軟體和服務。 AI-SPM 解決方案可滿足生成式人工智慧應用程式、大規模語言模型、人工智慧代理和基於代理的工作流程、機器學習模型和管道以及第三方和嵌入式人工智慧服務的安全需求。企業對人工智慧的日益普及、人工智慧攻擊面的不斷擴大以及對持續風險可見性和管治需求的不斷成長，正在推動該市場的發展。

企業對人工智慧的日益普及以及人工智慧帶來的日益成長的安全風險。

隨著人工智慧快速融入企業應用、業務流程、軟體開發和雲端基礎設施，對專業人工智慧安全管理能力的需求日益成長。企業正在部署生成式人工智慧應用、大規模語言模型、機器學習管道和自主人工智慧代理，這些應用和代理會與企業資料、外部工具和業務系統互動。這些部署帶來了許多風險，例如未授權存取、敏感資料外洩、配置不當、快速注入、模型篡改和代理過度授權。人工智慧安全績效管理 (AI-SPM) 解決方案可以幫助安全團隊識別人工智慧資產、評估其安全狀況、確定漏洞優先級，並在開發和生產環境中建立一致的控制措施。此外，隨著企業對第三方人工智慧服務的依賴性日益增強，持續了解人工智慧的使用情況、依賴關係和相關風險的需求也日益迫切。

複雜的AI環境與整合挑戰

企業級人工智慧環境的複雜性對人工智慧安全態勢管理市場構成重大限制。企業通常跨多個雲端平台、開發環境、資料儲存庫、模型供應商和第三方應用程式運行人工智慧工作負載。將安全態勢管理與現有的雲端安全、身分管理、資料保護、應用程式安全和管治工具整合可能需要大量的技術資源。此外，快速發展的人工智慧框架和代理架構會使資產發現、風險分類和策略執行變得更加複雜。安全團隊可能難以區分合法的人工智慧實驗和惡意部署，同時也要保持對敏感資訊的充分可見性。對於網路安全資源有限的企業而言，這些挑戰會導致部署成本增加、部署週期延長以及營運複雜性增加。

對人工智慧管治、代理安全和持續風險評估的需求日益成長。

生成式人工智慧和自主代理的擴展為人工智慧安全績效管理 (AI-SPM) 提供者帶來了巨大的機會。各組織機構越來越希望集中查看其人工智慧模型、應用程式、資料集、身分、工具以及對外部服務的依賴關係。整合資產發現和配置評估、管治控制以及運行時監控的安全解決方案有助於組織機構在整個人工智慧生命週期中管理風險。此外，人工智慧代理的日益普及也推動了對控制措施的需求，以應對權限過高、未經授權的工具存取、代理之間不安全的通訊以及敏感資料外洩等問題。與雲端安全平台、軟體開發平臺和保全行動系統整合可以提升 AI-SPM 解決方案的價值。此外，新興的人工智慧管治要求和內部風險管理策略正促使企業建立可重複的流程，用於人工智慧資產管理、課責和安全評估。

快速演變的攻擊方法以及與更廣泛的安全平台的競爭

人工智慧安全平台管理 (AI-SPM) 市場面臨著日益複雜的攻擊威脅，這些威脅針對人工智慧模型、應用程式、資料和基於代理的工作流程。攻擊者可以利用快速注入、安全性低下的模型整合、洩漏的憑證、篡改的資料集、易受攻擊的依賴項以及分配給人工智慧代理的權限漏洞。隨著人工智慧技術的不斷發展，安全提供者必須持續更新其檢測方法、風險評估和防護措施。同時，現有的雲端安全、應用安全、資料安全和網路安全平台供應商正在將人工智慧專屬功能整合到其更廣泛的產品系列中。這給專業供應商帶來了競爭壓力，並可能促使客戶將安全工具與其現有提供者整合。人工智慧框架和部署環境的差異也增加了在企業人工智慧生態系統中建構一致安全措施的複雜性。

新型冠狀病毒（COVID-19）的影響：

新冠疫情加速了企業數位轉型，包括雲端部署、遠距辦公和自動化。這些變化進一步凸顯了雲端安全、身分管理、資料保護和集中式風險監控的重要性。儘管在疫情初期，人工智慧安全態勢管理尚未形成廣泛成熟的獨立市場，但向雲端營運和人工智慧驅動的業務流程的廣泛轉變，為後續發展奠定了技術基礎。疫情以來，生成式人工智慧、企業級人工智慧概念驗證和自主工作流程部署的普及，增加了對專業人工智慧安全措施的需求。各組織正日益將人工智慧風險評估、管治和安全監控融入其更廣泛的網路安全戰略中。

在預測期內，軟體領域預計將佔據最大佔有率。

預計軟體領域將佔據最大的市場佔有率，這主要得益於企業對可擴展平台的需求，這些平台能夠自動完成人工智慧資產發現、安全態勢評估、風險優先排序和管治監控。人工智慧安全績效管理 (AI-SPM) 軟體使組織能夠識別分散式環境中的人工智慧模型和應用程式，檢測配置錯誤，評估安全漏洞，並持續監控與人工智慧相關的風險。透過與雲端安全平台、身分管理系統、開發平臺和保全行動工具的整合，其在企業安全架構中的作用得到了進一步增強。隨著組織部署越來越多的人工智慧應用程式和代理，基於軟體的解決方案能夠支援跨多個環境的持續監控和一致的策略執行。專業服務服務和託管服務透過部署、整合、評估和持續的安全支持，為這些平台提供補充。

預計在預測期內，人工智慧風險評估和錯誤配置偵測領域將實現強勁成長。

隨著企業尋求識別日益複雜的人工智慧環境中的漏洞，「人工智慧風險評估和配置錯誤檢測」領域預計將迎來顯著成長。企業需要評估其人工智慧應用的模型配置、存取權限、暴露的服務、資料連接、軟體依賴關係以及安全控制措施。配置錯誤的人工智慧基礎設施可能導致敏感資訊洩露，並為未授權存取和利用創造機會。自動化風險評估使安全團隊能夠根據漏洞的潛在業務影響和修復需求來確定其優先順序。此外，第三方人工智慧的日益整合以及基於代理的工作流程的擴展，使得企業更加需要持續評估安全態勢，而非定期進行安全審查。這些需求推動了對自動化人工智慧風險檢測和修復能力的需求。

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，這得益於企業人工智慧的廣泛應用、成熟的網路安全投入、先進的雲端基礎設施以及領先的人工智慧技術和安全廠商的存在。美國市場尤其重要，因為其集中了眾多雲端服務供應商、人工智慧開發商、網路安全公司以及部署生成式人工智慧應用的大型企業。金融服務、醫療保健、科技、製造和政府等行業的機構正日益重視人工智慧管治、敏感資料保護和企業風險管理。此外，該地區成熟的網路安全生態系統和專用人工智慧安全平台的可用性也促進了市場滲透。企業在人工智慧開發和部署安全方面的投入不斷增加，進一步鞏固了北美的領先地位。

複合年成長率最高的地區：

預計亞太地區在預測期內將實現最高的複合年成長率，這主要得益於快速的數位轉型、企業人工智慧應用的不斷擴展、雲端基礎設施投資以及日益成長的網路安全需求。在中國、日本、印度、韓國、澳洲和東南亞國家，人工智慧在金融服務、製造業、電信、零售和公共部門等領域的應用正在不斷擴展。隨著企業部署更多生成式人工智慧應用和智慧自動化系統，對人工智慧資產發現、安全配置評估、管治和風險監控的需求也不斷成長。此外，數位經濟的擴張、資料保護意識的提高以及企業對雲端原生安全的投資，都為人工智慧安全績效管理（AI-SPM）供應商創造了商機。該地區網路安全能力和人工智慧管治框架的發展也進一步推動了市場成長。

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
    • 主要參與者（最多3家公司）的SWOT分析
  • 區域細分
    • 根據客戶的興趣，我們將提供主要國家的市場估算和預測，以及複合年成長率（需進行可行性評估）。
  • 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 全球人工智慧安全態勢管理市場：按組件分類

  • 軟體
  • 服務

第6章 全球人工智慧安全態勢管理市場：依安全功能分類

  • 人工智慧資產檢測和盤點
  • 人工智慧風險評估和錯誤配置偵測
  • 人工智慧模型和應用程式的安全評估
  • 人工智慧管治和合規性監控
  • AI運行時安全和威脅偵測

第7章 全球人工智慧安全態勢管理市場：依部署模式分類

  • 基於雲端的
  • 現場
  • 混合

第8章 全球人工智慧安全態勢管理市場：依人工智慧環境分類

  • 生成式人工智慧應用與大規模語言模型
  • 人工智慧代理和基於代理的工作流程
  • 機器學習模型和流程
  • 第三方和嵌入式人工智慧服務

第9章 全球人工智慧安全態勢管理市場：依最終用戶分類

  • 銀行業、金融服務業及保險業
  • 醫療保健和生命科學
  • 資訊科技/通訊
  • 零售與電子商務
  • 製造業
  • 政府/公共部門
  • 其他最終用戶

第10章 全球人工智慧安全態勢管理市場：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.
  • Microsoft Corporation
  • Google LLC
  • Amazon Web Services, Inc.
  • Cisco Systems, Inc.
  • CrowdStrike Holdings, Inc.
  • SentinelOne, Inc.
  • Wiz, Inc.
  • Protect AI, Inc.
  • HiddenLayer, Inc.
  • Securiti, Inc.
  • IBM Corporation
  • Trend Micro Incorporated
  • Check Point Software Technologies Ltd.
  • Robust Intelligence, Inc.
Product Code: SMRC40429

According to Stratistics MRC, the Global AI Security Posture Management Market is accounted for $1.0 billion in 2026 and is expected to reach $1.5 billion by 2034 growing at a CAGR of 5.2% during the forecast period. AI Security Posture Management (AI-SPM) refers to technologies and services that help organizations discover AI assets, assess security risks, identify misconfigurations, monitor governance and compliance, and protect AI models, applications, data, and supporting infrastructure. The market encompasses software and services delivered through cloud-based, on-premises, and hybrid deployment models. AI-SPM solutions address security requirements across generative AI applications and large language models, AI agents and agentic workflows, machine learning models and pipelines, and third-party and embedded AI services. Increasing enterprise AI adoption, expanding AI attack surfaces, and growing demand for continuous risk visibility and governance are driving the development of this market.

Market Dynamics:

Driver:

Increasing enterprise AI adoption and expanding AI-related security risks

The rapid integration of artificial intelligence into enterprise applications, business workflows, software development, and cloud infrastructure is increasing demand for specialized AI security management capabilities. Organizations are deploying generative AI applications, large language models, machine learning pipelines, and autonomous AI agents that interact with corporate data, external tools, and business systems. These deployments introduce risks involving unauthorized access, sensitive data exposure, insecure configurations, prompt injection, model manipulation, and excessive agent permissions. AI-SPM solutions help security teams discover AI assets, assess their security posture, prioritize vulnerabilities, and establish consistent controls across development and production environments. Moreover, growing enterprise reliance on third-party AI services is increasing the need for continuous visibility into AI usage, dependencies, and associated risks.

Restraint:

Complex AI environments and integration challenges

The complexity of enterprise AI environments represents a significant restraint for the AI Security Posture Management Market. Organizations frequently operate AI workloads across multiple cloud platforms, development environments, data repositories, model providers, and third-party applications. Integrating security posture management with existing cloud security, identity management, data protection, application security, and governance tools can require substantial technical resources. Additionally, rapidly evolving AI frameworks and agent architectures can complicate asset discovery, risk classification, and policy enforcement. Security teams may also face difficulties distinguishing legitimate AI experimentation from unauthorized deployments while maintaining appropriate visibility into sensitive information. These challenges can increase implementation costs, extend deployment timelines, and create operational complexity for organizations with limited cybersecurity resources.

Opportunity:

Growing demand for AI governance, agent security, and continuous risk assessment

The expansion of generative AI and autonomous agents presents significant opportunities for AI-SPM providers. Organizations increasingly require centralized visibility into AI models, applications, datasets, identities, tools, and external service dependencies. Security solutions that connect asset discovery with configuration assessment, governance controls, and runtime monitoring can help organizations manage risks throughout the AI lifecycle. Furthermore, the growing use of AI agents creates demand for controls addressing excessive permissions, unauthorized tool access, insecure inter-agent communication, and sensitive data exposure. Integration with cloud security platforms, software development pipelines, and security operations systems can strengthen the value of AI-SPM offerings. Additionally, emerging AI governance requirements and internal risk management policies are encouraging enterprises to establish repeatable processes for AI inventory, accountability, and security assessment.

Threat:

Rapidly evolving attack techniques and competition from broader security platforms

The AI-SPM market faces threats from increasingly sophisticated attacks against AI models, applications, data, and agentic workflows. Attackers may exploit prompt injection, insecure model integrations, exposed credentials, poisoned datasets, vulnerable dependencies, and weaknesses in the permissions assigned to AI agents. As AI technologies evolve, security providers must continuously update detection methods, risk assessments, and protective controls. At the same time, established cloud security, application security, data security, and cybersecurity platform providers are incorporating AI-specific capabilities into broader product portfolios. This creates competitive pressure for specialized vendors and may encourage customers to consolidate security tools with existing providers. Differences in AI frameworks and deployment environments also increase the complexity of developing consistent security coverage across enterprise AI ecosystems.

Covid-19 Impact:

The COVID-19 pandemic accelerated digital transformation, cloud adoption, remote working, and the use of automation across enterprises. These changes strengthened the importance of cloud security, identity management, data protection, and centralized risk monitoring. Although AI Security Posture Management had not yet emerged as a widely established standalone market during the early stages of the pandemic, the broader shift toward cloud-based operations and AI-enabled business processes helped establish the technological foundation for its subsequent development. Following the pandemic, generative AI adoption, enterprise AI experimentation, and the deployment of autonomous workflows have increased the need for specialized AI security controls. Organizations are increasingly incorporating AI risk assessment, governance, and security monitoring into their broader cybersecurity strategies.

The Software segment is expected to account for the largest share during the forecast period

The Software segment is expected to hold the largest market share, supported by enterprise demand for scalable platforms that automate AI asset discovery, security posture assessment, risk prioritization, and governance monitoring. AI-SPM software enables organizations to identify AI models and applications across distributed environments, detect misconfigurations, evaluate security weaknesses, and maintain visibility into AI-related risks. Integration with cloud security platforms, identity systems, development pipelines, and security operations tools further strengthens its role in enterprise security architectures. As organizations deploy increasing numbers of AI applications and agents, software-based solutions can support continuous monitoring and consistent policy enforcement across multiple environments. Professional and managed services complement these platforms through implementation, integration, assessment, and ongoing security support.

The AI Risk Assessment and Misconfiguration Detection segment is expected to witness strong growth during the forecast period

The AI Risk Assessment and Misconfiguration Detection segment is expected to experience significant growth as enterprises seek to identify weaknesses across increasingly complex AI environments. Organizations must assess model configurations, access permissions, exposed services, data connections, software dependencies, and the security controls governing AI applications. Misconfigured AI infrastructure can expose sensitive information or create opportunities for unauthorized access and exploitation. Automated risk assessment helps security teams prioritize weaknesses according to their potential business impact and remediation requirements. Moreover, the expansion of third-party AI integrations and agentic workflows increases the need for continuous posture evaluation rather than periodic security reviews. These requirements are strengthening demand for automated AI risk discovery and remediation capabilities.

Region with largest share:

During the forecast period, North America is expected to hold the largest market share, supported by extensive enterprise AI adoption, established cybersecurity spending, advanced cloud infrastructure, and the presence of major AI technology and security vendors. The United States represents a particularly important market because of its concentration of cloud service providers, AI developers, cybersecurity companies, and large enterprises deploying generative AI applications. Organizations across financial services, healthcare, technology, manufacturing, and government are increasing their focus on AI governance, sensitive data protection, and enterprise risk management. Additionally, the region's established cybersecurity ecosystem and availability of specialized AI security platforms support market adoption. Growing enterprise investment in securing AI development and deployment is reinforcing North America's leading position.

Region with highest CAGR:

Asia Pacific is expected to register the highest CAGR during the forecast period, driven by rapid digital transformation, expanding enterprise AI adoption, cloud infrastructure investment, and growing cybersecurity requirements. China, Japan, India, South Korea, Australia, and Southeast Asian economies are increasing their use of AI in financial services, manufacturing, telecommunications, retail, and public-sector applications. As organizations deploy more generative AI applications and intelligent automation systems, the need for AI asset discovery, security configuration assessment, governance, and risk monitoring is increasing. Additionally, expanding digital economies, growing awareness of data protection, and enterprise investment in cloud-native security are creating opportunities for AI-SPM providers. The development of regional cybersecurity capabilities and AI governance frameworks is further supporting market expansion.

Key players in the market

Some of the key players in the Global AI Security Posture Management Market include Palo Alto Networks, Inc., Microsoft Corporation, Google LLC, Amazon Web Services, Inc., Cisco Systems, Inc., CrowdStrike Holdings, Inc., SentinelOne, Inc., Wiz, Inc., Protect AI, Inc., HiddenLayer, Inc., Securiti, Inc., IBM Corporation, Trend Micro Incorporated, Check Point Software Technologies Ltd., and Robust Intelligence, Inc.

Key Developments:

In September 2026, Palo Alto Networks, Inc. expanded its AI security initiatives through product developments addressing AI coding assistants, agent security, and enterprise AI protection. The company's Prisma AIRS platform and related integrations support security assessment across AI applications, models, and agentic workflows, reflecting the growing need to manage risks across the enterprise AI lifecycle.

In August 2026, Amazon Web Services, Inc. announced expanded integration of AWS Continuum for code vulnerability analysis into developer workflows involving Anthropic Claude Code, OpenAI Codex, and Kiro. The preview initiative applies AI-assisted security analysis within software development workflows, supporting efforts to identify and address vulnerabilities as code is created.

In May 2026, Google Cloud introduced Google AI Threat Defense, an AI-powered cybersecurity platform designed to help organizations identify critical risks, assess potential attack paths, and accelerate remediation. The announcement reflects growing investment in AI-driven security capabilities and continuous risk management across enterprise environments.

In April 2026, Google Cloud and Wiz announced expanded AI security capabilities at Google Cloud Next, including AI bill of materials functionality in AI development tools and enhanced protection for AI applications and agents across cloud environments. These capabilities address risks associated with shadow AI, AI-generated code, and the development of secure agentic applications.

Components Covered:

  • Software
  • Services

Security Capabilities Covered:

  • AI Asset Discovery and Inventory
  • AI Risk Assessment and Misconfiguration Detection
  • AI Model and Application Security Assessment
  • AI Governance and Compliance Monitoring
  • AI Runtime Security and Threat Detection

Deployment Modes Covered:

  • Cloud-Based
  • On-Premises
  • Hybrid

AI Environments Covered:

  • Generative AI Applications and Large Language Models
  • AI Agents and Agentic Workflows
  • Machine Learning Models and Pipelines
  • Third-Party and Embedded AI Services

End Users Covered:

  • Banking, Financial Services, and Insurance
  • Healthcare and Life Sciences
  • IT and Telecommunications
  • Retail and E-Commerce
  • Manufacturing
  • Government and Public Sector
  • Other End Users

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 regional and country-level segments
  • Strategic recommendations for new entrants
  • Covers market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032, and 2034
  • Market trends, including drivers, constraints, opportunities, threats, challenges, investment opportunities, and recommendations
  • Strategic recommendations for key business segments based on market estimations
  • Competitive landscape mapping and assessment of key industry trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends and assessment of the latest technological advancements

Free Customization Offerings:

All 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 (subject to feasibility assessment)
  • 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 Security Posture Management Market, By Component

  • 5.1 Software
  • 5.2 Services

6 Global AI Security Posture Management Market, By Security Capability

  • 6.1 AI Asset Discovery and Inventory
  • 6.2 AI Risk Assessment and Misconfiguration Detection
  • 6.3 AI Model and Application Security Assessment
  • 6.4 AI Governance and Compliance Monitoring
  • 6.5 AI Runtime Security and Threat Detection

7 Global AI Security Posture Management Market, By Deployment Mode

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

8 Global AI Security Posture Management Market, By AI Environment

  • 8.1 Generative AI Applications and Large Language Models
  • 8.2 AI Agents and Agentic Workflows
  • 8.3 Machine Learning Models and Pipelines
  • 8.4 Third-Party and Embedded AI Services

9 Global AI Security Posture Management Market, By End User

  • 9.1 Banking, Financial Services, and Insurance
  • 9.2 Healthcare and Life Sciences
  • 9.3 IT and Telecommunications
  • 9.4 Retail and E-Commerce
  • 9.5 Manufacturing
  • 9.6 Government and Public Sector
  • 9.7 Other End Users

10 Global AI Security Posture Management 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 Microsoft Corporation
  • 13.3 Google LLC
  • 13.4 Amazon Web Services, Inc.
  • 13.5 Cisco Systems, Inc.
  • 13.6 CrowdStrike Holdings, Inc.
  • 13.7 SentinelOne, Inc.
  • 13.8 Wiz, Inc.
  • 13.9 Protect AI, Inc.
  • 13.10 HiddenLayer, Inc.
  • 13.11 Securiti, Inc.
  • 13.12 IBM Corporation
  • 13.13 Trend Micro Incorporated
  • 13.14 Check Point Software Technologies Ltd.
  • 13.15 Robust Intelligence, Inc.

List of Tables

  • Table 1 Global AI Security Posture Management Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI Security Posture Management Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI Security Posture Management Market Outlook, By Software (2023-2034) ($MN)
  • Table 4 Global AI Security Posture Management Market Outlook, By Services (2023-2034) ($MN)
  • Table 5 Global AI Security Posture Management Market Outlook, By Security Capability (2023-2034) ($MN)
  • Table 6 Global AI Security Posture Management Market Outlook, By AI Asset Discovery and Inventory (2023-2034) ($MN)
  • Table 7 Global AI Security Posture Management Market Outlook, By AI Risk Assessment and Misconfiguration Detection (2023-2034) ($MN)
  • Table 8 Global AI Security Posture Management Market Outlook, By AI Model and Application Security Assessment (2023-2034) ($MN)
  • Table 9 Global AI Security Posture Management Market Outlook, By AI Governance and Compliance Monitoring (2023-2034) ($MN)
  • Table 10 Global AI Security Posture Management Market Outlook, By AI Runtime Security and Threat Detection (2023-2034) ($MN)
  • Table 11 Global AI Security Posture Management Market Outlook, By Deployment Mode (2023-2034) ($MN)
  • Table 12 Global AI Security Posture Management Market Outlook, By Cloud-Based (2023-2034) ($MN)
  • Table 13 Global AI Security Posture Management Market Outlook, By On-Premises (2023-2034) ($MN)
  • Table 14 Global AI Security Posture Management Market Outlook, By Hybrid (2023-2034) ($MN)
  • Table 15 Global AI Security Posture Management Market Outlook, By AI Environment (2023-2034) ($MN)
  • Table 16 Global AI Security Posture Management Market Outlook, By Generative AI Applications and Large Language Models (2023-2034) ($MN)
  • Table 17 Global AI Security Posture Management Market Outlook, By AI Agents and Agentic Workflows (2023-2034) ($MN)
  • Table 18 Global AI Security Posture Management Market Outlook, By Machine Learning Models and Pipelines (2023-2034) ($MN)
  • Table 19 Global AI Security Posture Management Market Outlook, By Third-Party and Embedded AI Services (2023-2034) ($MN)
  • Table 20 Global AI Security Posture Management Market Outlook, By End User (2023-2034) ($MN)
  • Table 21 Global AI Security Posture Management Market Outlook, By Banking, Financial Services, and Insurance (2023-2034) ($MN)
  • Table 22 Global AI Security Posture Management Market Outlook, By Healthcare and Life Sciences (2023-2034) ($MN)
  • Table 23 Global AI Security Posture Management Market Outlook, By IT and Telecommunications (2023-2034) ($MN)
  • Table 24 Global AI Security Posture Management Market Outlook, By Retail and E-Commerce (2023-2034) ($MN)
  • Table 25 Global AI Security Posture Management Market Outlook, By Manufacturing (2023-2034) ($MN)
  • Table 26 Global AI Security Posture Management Market Outlook, By Government and Public Sector (2023-2034) ($MN)
  • Table 27 Global AI Security Posture Management Market Outlook, By Other End Users (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.