Artificial Intelligence in Security Market Size, Share, Growth Analysis, By Type, By Offering, By Technology (Machine Learning, Natural Language Processing ), By Application, By Vertical, By Region - Industry Forecast 2024-2031

Global Artificial Intelligence in Security Market size was valued at USD 16.5 billion in 2022 and is poised to grow from USD 20.56 billion in 2023 to USD 119.44 billion by 2031, growing at a CAGR of 24.60% during the forecast period (2024-2031).

In recent years, the artificial intelligence (AI) landscape has experienced significant advancements, establishing AI as a crucial tool for reducing costs across various sectors, including research, manufacturing, and cybersecurity. Tools leveraging AI, such as Google's search engine and Facebook's facial recognition software, are instrumental in analyzing and preventing cybercrimes. This technology enhances cybersecurity measures by allowing systems to react to threats in mere milliseconds, positioning AI as a vital anti-fraud and vulnerability management strategy. The demand for Cyber AI is on the rise, particularly due to its ability to provide proactive defense mechanisms and precise threat detection. Notably, the need for continuous user authentication through behavioral biometrics is gaining traction. As industry stakeholders focus on integrating machine learning algorithms, the landscape for security intelligence is set to see substantial improvements. Moreover, the market for AI-based cybersecurity solutions is projected to expand significantly, driven by the increasing interest from small and medium enterprises (SMEs) in adopting these advanced technologies. Analysts predict that the U.S. artificial intelligence in security market will experience a sustainable compound annual growth rate (CAGR) in the coming years, underscoring the potential for investment and innovation in the field. This growth reflects a broader trend of businesses seeking to leverage AI capabilities to enhance their cybersecurity infrastructure and respond effectively to the evolving digital threat landscape.

Top-down and bottom-up approaches were used to estimate and validate the size of the global artificial intelligence in security 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 in security Market Segmental Analysis

Global Artificial Intelligence in Security Market is segmented by Type, Offering, Technology, Application, Vertical, and region. Based on Type, the market is segmented into Network Security, Endpoint Security, Application Security, Cloud Security. Based on Offering, the market is segmented into Hardware, Software, Services. Based on Technology, the market is segmented into Machine Learning (ML), Natural Language Processing (NLP), Context-aware Computing. 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 Vertical, the market is segmented into BFSI, Retail, Government & Defense, Manufacturing, Enterprise, Healthcare, Automotive & Transportation, and Others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & and Africa.

Driver of the global artificial intelligence in security Market

The proliferation of the Internet of Things (IoT) is acting as a significant market driver for the global artificial intelligence in security sector, as the rise in interconnected devices creates numerous vulnerabilities that amplify the risk of cyberattacks. This escalation in threats, coupled with a shortage of cybersecurity specialists, intensifies the demand for AI-driven security solutions that can efficiently analyze patterns, predict attacks, and respond in real-time. Furthermore, an increase in mobile malware incidents and stringent data protection regulations underscore the urgency for robust security mechanisms. As businesses become increasingly interconnected, the need for advanced AI technologies to safeguard diverse endpoints is more critical than ever.

Restraints in the global artificial intelligence in security Market

The global artificial intelligence in security market faces significant restraints stemming from escalating corporate executive cyber risks and limited security resources within organizations. These factors contribute to a pervasive sense of vulnerability, as many companies struggle to deploy effective AI solutions capable of addressing advanced and zero-day attacks, which are increasingly prevalent. Compounding these challenges is a notable shortage of skilled AI professionals, alongside a general lack of awareness regarding AI capabilities in cybersecurity. Together, these impediments are likely to stymie industry growth and adoption, hindering the full potential of AI technologies to enhance security measures over the forecast period.

Market Trends of the global artificial intelligence in security Market

The global artificial intelligence in security market is witnessing a notable trend with the emergence of AI TRiSM, a comprehensive framework focused on governing AI models. This framework emphasizes key elements such as fairness, robustness, and privacy, addressing the rising need for trust and transparency in AI applications. As enterprises increasingly adopt AI technologies, there is a pressing demand for robust governance practices to protect consumer interests and ensure model dependability. IT leaders are actively implementing AI TRiSM capabilities to enhance model interpretability and resilience against adversarial threats, ultimately driving growth and innovation in the AI security landscape.