Artificial Intelligence (AI) in Cybersecurity

Global Artificial Intelligence (AI) in Cybersecurity Market to Reach US$77.5 Billion by 2030

The global market for Artificial Intelligence (AI) in Cybersecurity estimated at US$23.6 Billion in the year 2024, is expected to reach US$77.5 Billion by 2030, growing at a CAGR of 21.9% over the analysis period 2024-2030. Software Component, one of the segments analyzed in the report, is expected to record a 21.6% CAGR and reach US$32.5 Billion by the end of the analysis period. Growth in the Services Component segment is estimated at 25.7% CAGR over the analysis period.

The U.S. Market is Estimated at US$7.5 Billion While China is Forecast to Grow at 25.7% CAGR

The Artificial Intelligence (AI) in Cybersecurity market in the U.S. is estimated at US$7.5 Billion in the year 2024. China, the world`s second largest economy, is forecast to reach a projected market size of US$13.1 Billion by the year 2030 trailing a CAGR of 25.7% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 19.0% and 17.8% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 20.6% CAGR.

Global Artificial Intelligence (AI) in Cybersecurity Market – Key Trends & Drivers Summarized

How AI Is Reinventing Cybersecurity for the Digital Age

Artificial Intelligence (AI) is rapidly transforming cybersecurity from a reactive, perimeter-focused discipline into a proactive, intelligent defense mechanism that adapts in real time. Traditional cybersecurity tools often struggle to keep pace with the scale, complexity, and velocity of today’s threats—ranging from ransomware and zero-day exploits to insider attacks and nation-state cyberwarfare. AI brings a new dimension to this battle by enabling systems to detect, analyze, and respond to anomalies at machine speed, often before damage is done. Using techniques such as machine learning, deep learning, and natural language processing, AI can comb through massive volumes of network traffic, user behavior, and endpoint data to identify subtle patterns that signal potential threats.

One of the most prominent trends driving the AI-in-cybersecurity landscape is the rise of autonomous threat detection and response systems. These AI-driven tools are capable of learning from historical attack data and evolving attack vectors to recognize emerging threats—even when they’ve never been seen before. In addition, AI is increasingly being used to augment Security Operations Centers (SOCs) through automated alert triage, threat intelligence enrichment, and root cause analysis, significantly reducing response times and human workload. The adoption of AI-driven cybersecurity is also being fueled by the rapid expansion of cloud environments, remote workforces, and IoT devices, all of which increase the attack surface and demand real-time protection beyond the capabilities of static defense tools.

How Is AI Changing Threat Detection, Response, and Resilience?

AI’s greatest value in cybersecurity lies in its ability to enable continuous, adaptive protection that evolves alongside the threat landscape. Unlike rule-based systems that rely on predefined signatures or policies, AI models can detect novel threats through behavioral analysis and anomaly detection. For example, if an employee suddenly downloads large amounts of sensitive data at an unusual hour, or if a device begins communicating with a known malicious server, AI systems can flag or block the activity instantly. These models continuously train on new data, improving their accuracy and reducing the number of false positives over time.

In incident response, AI accelerates containment and recovery by automating initial triage steps such as isolating compromised endpoints, revoking access tokens, or correlating events across disparate systems to determine attack paths. AI-driven Security Information and Event Management (SIEM) and Extended Detection and Response (XDR) platforms are helping enterprises identify coordinated attacks that span multiple vectors—like phishing, lateral movement, and privilege escalation—all in real time. Furthermore, AI is enhancing threat intelligence by digesting information from threat feeds, dark web monitoring, and geopolitical developments to predict likely targets or adversary tactics. This predictive capability is critical for shifting cybersecurity from a reactive posture to a preventative one, enabling businesses to anticipate and mitigate threats before they escalate.

Which Sectors Are Adopting AI Cybersecurity Solutions Most Aggressively?

The adoption of AI in cybersecurity is particularly pronounced in industries where data sensitivity, regulatory pressure, and threat exposure are highest. Financial services firms are at the forefront, using AI to protect against fraud, identity theft, and large-scale breaches. AI systems here monitor transactional patterns in real-time, detect unusual financial behavior, and stop fraudulent transfers or logins before they occur. In healthcare, where protecting patient data and ensuring system availability is mission-critical, AI is being used to safeguard electronic health records, detect ransomware infections, and ensure compliance with regulations like HIPAA and GDPR.

Government and defense sectors are leveraging AI to defend against cyber-espionage, infrastructure sabotage, and critical national security threats. These institutions use AI to monitor large-scale networks, secure classified communication, and manage identity access across distributed environments. E-commerce and retail businesses are deploying AI-based tools to secure customer data, prevent bot attacks, and ensure trust across payment and transaction systems. Meanwhile, energy and utility companies are investing in AI to secure operational technology (OT) and industrial control systems (ICS) that run critical infrastructure. In all these industries, the growing complexity of threats and the importance of rapid response are pushing AI from a nice-to-have to an essential pillar of cybersecurity architecture.

What’s Fueling the Growth in the AI Cybersecurity Market?

The growth in the AI in cybersecurity market is driven by several factors rooted in rising threat sophistication, expanding digital ecosystems, and evolving operational needs. A primary catalyst is the exponential increase in cyberattacks targeting cloud infrastructure, remote work endpoints, and distributed applications—surfaces that demand continuous and automated defense. Organizations are increasingly unable to manage cybersecurity risks manually, especially given the shortage of skilled security professionals. AI offers a force multiplier by enabling security teams to scale detection and response capabilities without proportional increases in staffing.

From a technology standpoint, advancements in deep learning and behavioral analytics are improving the precision and contextual intelligence of AI models, making them more capable of identifying advanced persistent threats (APTs), fileless malware, and polymorphic code. The integration of AI with next-gen security tools such as XDR, Secure Access Service Edge (SASE), and Zero Trust Architectures is further accelerating adoption. Regulatory compliance is another major driver, as organizations must demonstrate real-time monitoring, incident reporting, and data breach prevention—capabilities that AI enhances significantly. Lastly, as digital transformation initiatives continue to drive cloud migrations, API adoption, and edge computing, the need for AI-powered, scalable, and intelligent cybersecurity solutions becomes indispensable across enterprises of all sizes and industries.

SCOPE OF STUDY:

The report analyzes the Artificial Intelligence (AI) in Cybersecurity market in terms of units by the following Segments, and Geographic Regions/Countries:

Segments:
Component (Software Component, Services Component, Hardware Component); Technology (Machine Learning Technology, Natural Language Processing (NLP) Technology, Context-Aware Computing Technology); Type (Network Security Type, Endpoint Security Type, Application Security Type, Cloud Security Type); Vertical (Enterprise Verticle, BFSI Verticle, Government & Defense Verticle, Retail Verticle, Manufacturing Verticle, Automotive & Transportation Verticle, Other Verticals)

Geographic Regions/Countries:
World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World.

Select Competitors (Total 25 Featured) -

• Check Point Software Technologies Ltd.
• Crowdstrike, Inc.
• Darktrace Holdings Limited
• IBM Corporation
• Kaspersky Lab
• Microsoft Corporation
• NetDepot.com LLC
• NVIDIA Corporation
• Sangfor Technologies, Inc.
• Sentinelone

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