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市場調查報告書
商品編碼
1755470
網路安全中的人工智慧 (AI) 市場規模、佔有率、成長分析(按類型、產品、技術、產業垂直、應用、地區和預測)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 |
預計到 2023 年,網路安全市場中的人工智慧 (AI) 將以 235 億美元的複合年成長率成長,從 2024 年的 290.5 億美元成長到 2032 年的 1582.1 億美元,預測期內(2025-2032 年)的複合年成長率為 23.6%。
由於網路攻擊的頻率和複雜性不斷增加,人工智慧 (AI) 技術市場,尤其是在網路安全領域,正在經歷顯著成長。安全和政府機構正在利用自然語言處理 (NLP) 和機器學習 (ML) 等先進的人工智慧應用來增強威脅偵測、回應和保護措施。關鍵洞察表明,透過行為生物識別技術進行強用戶身份驗證的需求日益成長,促使行業相關人員優先開發能夠充分利用人工智慧潛力來提升安全智慧的機器學習演算法。此外,銀行等領域日益成長的隱私問題進一步凸顯了對人工智慧主導的網路安全解決方案的需求。因此,預計該市場將大幅擴張,以滿足對全面安全解決方案日益成長的需求。
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.