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市场调查报告书
商品编码
1755470
网路安全中的人工智慧 (AI) 市场规模、份额、成长分析(按类型、产品、技术、产业垂直、应用、地区和预测)到 2025 年至 2032 年Artificial Intelligence (AI) in Cybersecurity Market Size, Share, and Growth Analysis, By Type (Network Security, Endpoint Security), By Offering (Hardware, Software), By Technology, By Vertical, By Application, By Region - Industry Forecast 2025-2032 |
预计到 2023 年,网路安全市场中的人工智慧 (AI) 将以 235 亿美元的复合年增长率增长,从 2024 年的 290.5 亿美元增长到 2032 年的 1582.1 亿美元,预测期内(2025-2032 年)的复合年增长率为 23.6%。
由于网路攻击的频率和复杂性不断增加,人工智慧 (AI) 技术市场,尤其是在网路安全领域,正在经历显着成长。安全和政府机构正在利用自然语言处理 (NLP) 和机器学习 (ML) 等先进的人工智慧应用来增强威胁侦测、回应和保护措施。关键洞察表明,透过行为生物识别技术进行强用户身份验证的需求日益增长,促使行业相关人员优先开发能够充分利用人工智慧潜力来提升安全智慧的机器学习演算法。此外,银行等领域日益增长的隐私问题进一步凸显了对人工智慧主导的网路安全解决方案的需求。因此,预计该市场将大幅扩张,以满足对全面安全解决方案日益增长的需求。
Global Artificial Intelligence (AI) in Cybersecurity Market size was valued at USD 23.5 billion in 2023 and is poised to grow from USD 29.05 billion in 2024 to USD 158.21 billion by 2032, growing at a CAGR of 23.6% during the forecast period (2025-2032).
The market for Artificial Intelligence (AI) technologies, particularly in cybersecurity, is experiencing substantial growth due to the increasing frequency and complexity of cyberattacks. Advanced AI applications, such as natural language processing (NLP) and machine learning (ML), are being leveraged by security and government agencies to enhance threat detection, response, and protection measures. Key insights reveal a rising demand for robust user authentication through behavioral biometrics, pushing industry stakeholders to prioritize the development of ML algorithms that harness AI's full potential for improving security intelligence. Additionally, heightened privacy concerns in sectors like banking further underscore the necessity for AI-driven cybersecurity solutions. As a result, the market is poised for significant expansion to meet the escalating demand for comprehensive security solutions.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Artificial Intelligence (AI) in Cybersecurity market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Global Artificial Intelligence (AI) in Cybersecurity Market Segments Analysis
Global Artificial Intelligence (AI) in Cybersecurity Market is segmented by Type, Offering, Technology, Vertical, Application and region. Based on Type, the market is segmented into Network Security, Endpoint Security, Application Security and Cloud Security. Based on Offering, the market is segmented into Hardware, Software and Services. Based on Technology, the market is segmented intomachine learning, Natural Language Processing (NLP) and Context-aware Computing. Based on Vertical, the market is segmented into BFSI, Retail, Government & Defense, Manufacturing, Enterprise, Healthcare, Automotive & Transportation and Others. Based on Application, the market is segmented into Identity And Access Management, Risk And Compliance Management, Data Loss Prevention, Unified Threat Management, Fraud Detection/Anti-Fraud, Threat Intelligence and Others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Global Artificial Intelligence (AI) in Cybersecurity Market
The surge in cyberattacks is a significant catalyst for the growing integration of AI in cybersecurity. Conventional security protocols frequently fall short in addressing the fast-evolving nature of threats, prompting a need for advanced solutions. AI technologies, with their ability to process vast datasets and detect patterns of wrongdoing, offer robust defense mechanisms against complex attacks, including common vulnerabilities and advanced persistent threats (APTs). As organizations seek to bolster their security frameworks, the adoption of AI-driven solutions becomes imperative, ensuring they can effectively navigate and counteract the ever-changing landscape of cyber threats.
Restraints in the Global Artificial Intelligence (AI) in Cybersecurity Market
The implementation of AI-driven cybersecurity solutions entails substantial investment in software, hardware, and specialized personnel, which can pose a challenge, especially for small and medium enterprises (SMEs) that often find these expenses prohibitive. This financial burden can deter SMEs from adopting such technologies, curbing their ability to enhance cybersecurity measures. Additionally, larger organizations, despite having more resources, may also face difficulties justifying the high costs associated with widespread AI deployment across various sectors of their operations. Consequently, these financial constraints represent a significant barrier to the broader integration of AI in cybersecurity practices.
Market Trends of the Global Artificial Intelligence (AI) in Cybersecurity Market
The integration of Artificial Intelligence (AI) into threat intelligence systems is a pivotal trend shaping the global AI in cybersecurity market. As cyber threats evolve in complexity, AI enhances the capacity to predict, detect, and mitigate risks in real-time by analyzing vast amounts of threat data from diverse sources, such as the dark web, social media, and network traffic. These sophisticated AI algorithms identify patterns and anomalies that signal potential attacks, enabling a proactive defense approach. Automating the correlation and analysis of threat intelligence not only provides timely and accurate insights but also fosters the development of scalable cybersecurity solutions, fortifying organizations against ever-evolving threats.