The AI Cyber Security Market is expected to grow at a CAGR of 25.30%, reaching a market size of US$147.610 billion in 2030 from US$47.790 billion in 2025.
The term artificial intelligence (AI) cyber security entails enhancing the security of networks, digital systems, and data from cyber threats using AI technology and machine learning capability. Specifically, it uses AI algorithms to identify, prevent, and counter various forms, including cyberattacks, outbreaks, and compromises of security, among others.
AI cybersecurity integrates threat intelligence streams and databases to enhance the security layer and decision-making processes. AI systems are increasingly helpful for these organizations by providing information about the threats and attack patterns promptly after collecting and processing data on threats from many channels, such as OSINT, dark web scans, and security research. In-ceiling the ground with machines, CEB headers use AI and machine learning to evaluate user activities, hence being able to track down any threats posed by users, breaches of accounts, and strange entry attempts. However, user behavior analytics systems can integrate user behavior data and other relevant contextual/predicated factors, such as risk, to identify unusual behaviors, estimate possible threats to security, or other wrongful activities.
In the face of contemporary threats, which are quite complicated and dynamic, AI cybersecurity protects organizations from the negative impacts of cyberattacks, increases efficiency in threat detection and response, and improves overall security. With the help of AI technologies, organizations can re-gear their defenses and lessen the damage costs occurring due to the infiltration of their computer systems and data.
As the rate of cyberattacks intensifies, so does the rate of evolution of the incidence of cybercrimes. Hence, in the last few years, there has been an ever-growing demand for advanced cybersecurity, with the likes of systems that detect and prevent intrusions using AI. The statistics provided by the Indian Ministry of Home Affairs stated that there have been more than 16 lakh cybercrime complaints which were received from January 01, 2020, to December 07, 2022, in India, as well as more than 32 thousand FIRs that were lodged during the above-mentioned period.
The escalating cyber-attack risk highlights the need for new, effective cybersecurity systems capable of providing constant online threat detection, initiatives for online threat detection, and defense mechanisms that can evolve with the threats. Cybersecurity solutions that utilize AI technologies are helping organizations to swiftly detect and respond to emerging cyber threats. Thus, it minimizes risks and eliminates the chances of data loss and other security threats. With the changes in the threat landscape, the need for AI cybersecurity solutions is expected to increase as organizations consider cybersecurity as a business risk management must incorporate such solutions.
With the increasing dependency on cloud systems, cloud security becomes even more important by providing the means for actively protecting individuals, companies, or public entities from new forms of criminal activity appearing in cyberspace. This suggests how a cloud security solution, such as Cisco Umbrella – a Secure Access Service Edge (SASE) security product offered by Cisco, works. This solution provides networking and security services delivered over the cloud, enabling businesses to scale their operations up or down without geographical limitations.
The SASE security model, also an additional product of the service offered by the SASE provider, is placed at the edge of the cloud, providing complete security from data centers to remote access and mobile users. SASE allows the secure utilization of cloud-based teamwork software or application servers within the organization's headquarters. This results in increased adoption of AI-supported cybersecurity solutions as organizations seek to prevent losses and costs associated with improving cloud security.
Threat assessment and prevention systems utilize threat information feeds and databases to enhance security analysis and decision-making capabilities. Incident response systems assist in forming and analyzing forensic data regarding security incidents, which helps in the investigation and recovery process. Security orchestration, automation, and response solutions enhance incident response processes and enable coordination between security personnel and IT operations.
User and Entity Behaviour Analytics based on AI is incorporated into the Identity and Access Management systems for identifying unusual behavior patterns that pose any security risk. AI-powered adaptive authentication systems tailor authentication requirements to user behavior, context, and risk factors, enhancing access restrictions and minimizing unauthorized access threats.
Developing, installing, and maintaining AI cybersecurity systems may be time-consuming and expensive for businesses. AI algorithms' training and inference activities require enormous computing resources, necessitating high-performance hardware, cloud services, and storage infrastructure. In the AI cybersecurity market, vendors and organizations need to improve the cost, reach, and ease of use of AI-enhanced security systems. This will enable the organizations to harness these systems fully.
The North American region is expected to have a sizable proportion of the AI cyber security market due to the spike in network-connected devices and the rising use of the Internet of Things, 5G, and Wi-Fi.
Organizations in the automotive, healthcare, government, energy, and mining industries have accelerated 5G network deployment, creating a potential access point for hackers. This region is replete with numerous research institutions for startups focusing on AI. It is home to strong industry players like Anthropic, Adept AI, Berkeley AI Research Lab, University of Arizona Artificial Intelligence Lab, Wysa, and so many others, which are making great contributions to the development of AI-based cybersecurity systems.
In addition, various government programs, initiatives of public-private partnerships, and investment projects in cybersecurity boost cyber posture and protect infrastructure against such attacks. This region is subject to various cyber threats: nation-state attacks, cyber espionage, ransomware attacks, encroaching threats, and even more. Hence, there is a high demand for such AI-powered cybersecurity solutions targeted at threat detection, incident response, and risk mitigation measures.
| Report Metric | Details |
|---|---|
| Study Period | 2021 to 2031 |
| Historical Data | 2021 to 2024 |
| Base Year | 2025 |
| Forecast Period | 2026 – 2031 |
| Report Metric | Details |
|
AI Cyber Security Market Size in 2025 |
US$47.790 billion |
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AI Cyber Security Market Size in 2030 |
US$147.610 billion |
| Growth Rate | CAGR of 25.30% |
| Study Period | 2020 to 2030 |
| Historical Data | 2020 to 2023 |
| Base Year | 2025 |
| Forecast Period | 2025 – 2030 |
| Forecast Unit (Value) | USD Billion |
| Segmentation |
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| Geographical Segmentation | North America, South America, Europe, Middle East and Africa, Asia Pacific |
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List of Major Companies in the AI Cyber Security Market |
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| Customization Scope | Free report customization with purchase |
The AI cybersecurity market is analyzed into the following segments: