The global market for Artificial Intelligence (AI) in Cybersecurity was valued at US$27.2 Billion in 2024 and is projected to reach US$89.0 Billion by 2030, growing at a CAGR of 21.8% from 2024 to 2030. This comprehensive report provides an in-depth analysis of market trends, drivers, and forecasts, helping you make informed business decisions. The report includes the most recent global tariff developments and how they impact the Artificial Intelligence (AI) in Cybersecurity market.
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.
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.
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.
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.
Segments: Component (Software, Services, Hardware); Technology (Machine Learning, Natural Language Processing (NLP), Context-Aware Computing); Type (Network Security, Endpoint Security, Application Security, Cloud Security); Vertical (Enterprise, BFSI, Government & Defense, Retail, Manufacturing, Automotive & Transportation, 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.
The analysts continuously track trade developments worldwide, drawing insights from leading global economists and over 200 industry and policy institutions, including think tanks, trade organizations, and national economic advisory bodies. This intelligence is integrated into forecasting models to provide timely, data-driven analysis of emerging risks and opportunities.
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.
Report Scope
The report analyzes the Artificial Intelligence (AI) in Cybersecurity market, presented in terms of units. The analysis covers the key segments and geographic regions outlined below.Segments: Component (Software, Services, Hardware); Technology (Machine Learning, Natural Language Processing (NLP), Context-Aware Computing); Type (Network Security, Endpoint Security, Application Security, Cloud Security); Vertical (Enterprise, BFSI, Government & Defense, Retail, Manufacturing, Automotive & Transportation, 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.
Key Insights:
- Market Growth: Understand the significant growth trajectory of the Software segment, which is expected to reach US$38.2 Billion by 2030 with a CAGR of a 21.6%. The Services segment is also set to grow at 25.4% CAGR over the analysis period.
- Regional Analysis: Gain insights into the U.S. market, valued at $7.5 Billion in 2024, and China, forecasted to grow at an impressive 20.7% CAGR to reach $13.4 Billion by 2030. Discover growth trends in other key regions, including Japan, Canada, Germany, and the Asia-Pacific.
Why You Should Buy This Report:
- Detailed Market Analysis: Access a thorough analysis of the Global Artificial Intelligence (AI) in Cybersecurity Market, covering all major geographic regions and market segments.
- Competitive Insights: Get an overview of the competitive landscape, including the market presence of major players across different geographies.
- Future Trends and Drivers: Understand the key trends and drivers shaping the future of the Global Artificial Intelligence (AI) in Cybersecurity Market.
- Actionable Insights: Benefit from actionable insights that can help you identify new revenue opportunities and make strategic business decisions.
Key Questions Answered:
- How is the Global Artificial Intelligence (AI) in Cybersecurity Market expected to evolve by 2030?
- What are the main drivers and restraints affecting the market?
- Which market segments will grow the most over the forecast period?
- How will market shares for different regions and segments change by 2030?
- Who are the leading players in the market, and what are their prospects?
Report Features:
- Comprehensive Market Data: Independent analysis of annual sales and market forecasts in US$ Million from 2024 to 2030.
- In-Depth Regional Analysis: Detailed insights into key markets, including the U.S., China, Japan, Canada, Europe, Asia-Pacific, Latin America, Middle East, and Africa.
- Company Profiles: Coverage of players such as Check Point Software Technologies Ltd., Crowdstrike, Inc., Darktrace Holdings Limited, IBM Corporation, Kaspersky Lab and more.
- Complimentary Updates: Receive free report updates for one year to keep you informed of the latest market developments.
Some of the 25 companies featured in this Artificial Intelligence (AI) in Cybersecurity market report include:
- 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
Tariff Impact Analysis: Key Insights for 2025
Global tariff negotiations across 180+ countries are reshaping supply chains, costs, and competitiveness. This report reflects the latest developments as of April 2025 and incorporates forward-looking insights into the market outlook.The analysts continuously track trade developments worldwide, drawing insights from leading global economists and over 200 industry and policy institutions, including think tanks, trade organizations, and national economic advisory bodies. This intelligence is integrated into forecasting models to provide timely, data-driven analysis of emerging risks and opportunities.
What’s Included in This Edition:
- Tariff-adjusted market forecasts by region and segment
- Analysis of cost and supply chain implications by sourcing and trade exposure
- Strategic insights into geographic shifts
Buyers receive a free July 2025 update with:
- Finalized tariff impacts and new trade agreement effects
- Updated projections reflecting global sourcing and cost shifts
- Expanded country-specific coverage across the industry
Table of Contents
I. METHODOLOGYII. EXECUTIVE SUMMARY2. FOCUS ON SELECT PLAYERSIII. MARKET ANALYSISCANADAITALYREST OF EUROPEREST OF WORLDIV. COMPETITION
1. MARKET OVERVIEW
3. MARKET TRENDS & DRIVERS
4. GLOBAL MARKET PERSPECTIVE
UNITED STATES
JAPAN
CHINA
EUROPE
FRANCE
GERMANY
UNITED KINGDOM
ASIA-PACIFIC
Companies Mentioned (Partial List)
A selection of companies mentioned in this report includes, but is not limited to:
- 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
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 210 |
| Published | April 2025 |
| Forecast Period | 2024 - 2030 |
| Estimated Market Value ( USD | $ 27.2 Billion |
| Forecasted Market Value ( USD | $ 89 Billion |
| Compound Annual Growth Rate | 21.8% |
| Regions Covered | Global |
