AI in Cybersecurity Market by Solution (AI-native Security, AI-enhanced Security Products), Security Type (Endpoint Security & Management, Network Security, Application Security, Cloud Security, Data Security, IAM, Encryption & Tokenization, Cybersecurity Operation Solutions) - Global Forecast to 2031

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USD 50.83 BN
MARKET SIZE, 2031
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CAGR 14.8%
(2026-2031)
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487
REPORT PAGES
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547
MARKET TABLES

OVERVIEW

artificial intelligence ai cyber security market Overview

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

The AI in cybersecurity market was a valuation of USD 25.53 billion in 2026. By 2031, it's expected to reach USD 50.83 billion, reflecting a compound annual growth rate (CAGR) of 14.8%. The increasing market growth has been driven by high enterprise adoption of AI in sectors such as financial, retail, healthcare, and technology, where AI-enabled cybersecurity has been used to monitor attacks and analyze large security data to help make faster decisions for various cybersecurity operations. Organizations are deploying artificial intelligence across security operations to automatically incorporate detections of anomalous activity, accelerate responses to incidents, and bolster security at cloud, network, and endpoint. The rising adoption of threat intelligence, security analytics platforms, and identity protection through AI adoption is a growing enterprise use case in the cybersecurity landscape.

Market Size and Forecast:

  • Market Size Value in 2025: USD 22.37 Billion
  • Market Size Value in 2026: USD 25.53 Billion
  • Revenue Forecast in 2031: USD 50.83 Billion
  • Growth Rate: CAGR of 14.8% from 2026 to 2031
  • Base year: 2025
  • Forecast period: 2026–2031
  • North America is estimated to account for the largest market share of 35.50% in 2026.
  • The endpoint security & management segment is positioned to hold the largest market share of 18.75% in 2026.

Key Market Trends and Insights

  • By Solution: The AI-enhanced Security Products segment accounts for a significant share of the AI in Cybersecurity market, driven by increasing demand for AI-powered threat detection, automated incident response, real-time monitoring, and enhanced protection against sophisticated cyber threats.
  • Industry Dynamics: Organizations are increasingly adopting AI-driven cybersecurity solutions to strengthen security operations, improve threat intelligence, accelerate incident response, and enhance visibility across cloud, network, endpoint, and enterprise IT environments.
  • Market Drivers: The increasing complexity and frequency of cyberattacks, expanding cloud adoption, growing digital transformation initiatives, rising attack surfaces across connected devices, and the need for real-time threat detection and automated security operations are driving market growth.
  • Future Opportunities: Significant opportunities are emerging in AI-native security platforms, autonomous threat detection and response, predictive threat intelligence, cloud security, identity and access management (IAM), and AI-powered cybersecurity operations designed to improve organizational resilience and reduce security response times.

KEY TAKEAWAYS

  • By Region
    North America is estimated to account for the largest market share of 35.50% in 2026.
  • By Offering
    The software segment is projected to hold the largest market share in 2026.
  • By Security Type
    The endpoint security & management segment is positioned to hold the largest market share of 18.75% in 2026.
  • By Application
    The security operations optimization segment is projected to showcase the highest CAGR of 18.6% during the forecast period.
  • By Vertical
    The retail & e-commerce segment is projected to grow at the highest CAGR during the forecast period.
  • Competitive Landscape - Key Players
    Microsoft, Palo Alto Networks, and AWS are among the leading players in the AI in cybersecurity market, given their strong market share and product portfolios.
  • Competitive Landscape - Startups/SMEs
    Deep Instinct, Nozomi Networks, and Acalvio Technologies have distinguished themselves among other players by securing strong footholds in specialized niche areas, underscoring their potential as emerging leaders.

Many global initiatives are accelerating the adoption of AI in cybersecurity as organizations focus on improving threat detection and response across ever more complex environments. Adoption is being further driven by the increasing need for automated SOC workflows and faster incident response via platforms including SOAR and XDR, as well as rising adoption of AI for securing cloud workloads and APIs. Technology vendors, meanwhile, are expanding infrastructure to enable these use cases, including AI-enabled security platforms and high-performance computing infrastructures.

TRENDS & DISRUPTIONS IMPACTING CUSTOMERS' CUSTOMERS

The cybersecurity landscape is evolving. There is a shift away from the old, reactive security measures and toward smart, data-powered platforms that can respond automatically and in real time. Companies are now weaving AI into various security tools, such as identity management, data protection, and network security, all in an effort to make better decisions. This change is causing a significant shake-up, allowing vendors to build unified, scalable security systems that adapt to the changing needs of both businesses and their partners.

artificial intelligence ai cyber security market Disruptions

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

MARKET DYNAMICS

Drivers
Impact
Level
  • Increasing complexity and frequency of cyberattacks driving AI adoption
  • AI-powered cloud workload & API security
RESTRAINTS
Impact
Level
  • Limited availability of quality data and privacy concerns restricting AI effectiveness
  • Growth of AI-driven cloud security posture management (CSPM) & workload protection platforms
OPPORTUNITIES
Impact
Level
  • Rising need for automated security operations creating growth opportunities
  • The growing use of artificial intelligence in identity threat detection and response (ITDR)
CHALLENGES
Impact
Level
  • Evolving adversarial threats posing challenges to AI-based cybersecurity systems
  • The use of shadow AI is creating unmonitored vulnerabilities in enterprise applications

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

Driver – Increasing complexity and frequency of cyberattacks driving AI adoption

The rising frequency and complexity of cyberattacks, including zero-day exploits and AI-powered threats, are driving the adoption of AI in cybersecurity. Organizations are leveraging AI for real-time threat detection, anomaly identification, and faster response. The growing attack surface across cloud, endpoints, and networks further accelerates demand for advanced AI-driven cybersecurity solutions and services.

Restraint – Limited availability of quality data and privacy concerns restricting AI effectiveness

The efficacy of AI models also relies on the availability of large amounts of quality security information, which may not be feasible owing to privacy concerns and organizational barriers. Furthermore, the fear of sharing information may also be a challenge in the development of AI-based cybersecurity tools.

Opportunity – Rising need for automated security operations creating growth opportunities

The increasing need to manage alert volumes and reduce response times is creating strong demand for AI-driven security operations platforms. Technologies such as XDR, SOAR, and AI copilots are enabling automation of threat detection and response. This shift toward autonomous and intelligent security operations presents significant growth opportunities for vendors offering AI-powered security platforms, automation solutions, and managed security services.

Challenge – Evolving adversarial threats posing challenges to AI-based cybersecurity systems

Cybercriminals are increasingly using AI to develop more sophisticated attacks, which are difficult to evade. They are also using adversarial attacks, which are difficult to detect by AI models. Therefore, it is a continuous process for both attackers and defenders. Robustness, explainability, and robustness are challenges in this context.

ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: COMMERCIAL USE CASES ACROSS INDUSTRIES

COMPANY USE CASE DESCRIPTION BENEFITS
A financial investment organization implemented zero-trust security, including SASE, endpoint security, and network security at Infosys. The deployment improved threat detection, enabled centralized management, sped up incident response, and strengthened security policy compliance.
Used AWS-based cybersecurity platform (SageMaker, Glue, Lambda, S3) to detect and analyze large-scale cyber threats in real-time. Exceeded cybersecurity benchmarks, processes 60,000 threats/sec, enables fast forensic analysis without performance impact, and operates efficiently with a small team.
Using model from Snorkel Flow, US national security teams can develop AI/ML applications that utilize text, voice, and satellite data to accelerate intelligence work. Platform minimizes manual labeling effort, increases scalability, gives more transparent models and higher performance with easier troubleshooting.

Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.

MARKET ECOSYSTEM

The AI in cybersecurity ecosystem comprises software and service providers that develop advanced threat detection systems, analytics tools, and comprehensive security platforms. Together, these components work seamlessly to safeguard digital environments. This integrated approach delivers a holistic suite of cybersecurity solutions, effectively protecting both enterprise and cloud infrastructures.

artificial intelligence ai cyber security market Ecosystem

Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.

MARKET SEGMENTS

artificial intelligence ai cyber security market Segments

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

AI in Cybersecurity Market, By Offering

Software will take the biggest share by 2026 because more businesses are using AI-based security tools. Companies want solutions that can quickly detect threats and handle them automatically. The growing use of cloud platforms is also pushing the demand for software even higher.

AI in Cybersecurity Market, By Security Type

Cloud security is expected to grow the fastest. This is because more companies are moving to the cloud and using multiple cloud services. AI helps them spot threats, fix issues, and manage security problems in real time. The shift toward cloud-native systems and zero-trust security is also increasing the need for these solutions.

AI in Cybersecurity Market, By Application

Threat detection and prevention is expected to grow the fastest as companies focus more on finding and stopping cyber threats early. Tools powered by AI, like anomaly detection and behavior analysis, are becoming important for real-time protection. As cyberattacks become more complex, the need for these tools is increasing.

AI in Cybersecurity Market, By Vertical

The BFSI sector has the largest market share, given that this sector is more prone to cyber attacks and has strict regulations. There is a rise in the adoption of AI in banks and financial institutions for fraud prevention. There is also a rise in digital transactions.

REGION

Asia Pacific is expected to be the fastest-growing region in the AI in cybersecurity market during the forecast period.

Asia Pacific is poised to outpace all others in the AI in cybersecurity market, according to projections. This surge is fueled by the region's swift digital transformation and the widespread embrace of AI by businesses. The growth is further bolstered by the escalating number and complexity of cyber threats. Asia Pacific is a major victim of cyber incidents worldwide, and the frequency of attacks shows no sign of abating. Organizations are investing in AI-driven security solutions to improve threat detection, protect critical infrastructure, and strengthen resilience across digital environments.

artificial intelligence ai cyber security market Region

ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: COMPANY EVALUATION MATRIX

The Company Evaluation Matrix places Palo Alto Networks in the stars quadrant, driven by its strong AI-driven cybersecurity portfolio, integrated platform approach, and broad enterprise adoption. IBM is positioned in the emerging leaders quadrant as it continues to expand its AI-enabled security offerings, particularly in security operations and threat intelligence, supported by its focus on hybrid cloud and enterprise security solutions.

artificial intelligence ai cyber security market Evaluation Metrics

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

KEY MARKET PLAYERS

MARKET SCOPE

REPORT METRIC DETAILS
Market Size in 2025 (Value) USD 22.37 Billion
Market Size in 2026 (Value) USD 25.53 Billion
Market Forecast in 2031 (Value) USD 50.83 Billion
CAGR GAGR of14.8% from 2026-2031
Years Considered 2021-2031
Base Year 2025
Forecast Period 2026-2031
Units Considered USD Billion/Million
Report Coverage Revenue forecast, company ranking, competitive landscape, growth factors, and trends
Segments Covered
  • By Offering:
    • Solutions
    • Services
  • By Security Type:
    • Endpoint Security & Management
    • Application Security
    • Network Security
    • Cloud Security
    • Data Security
    • Identity & Access Management
    • Encryption & Tokenization
    • Cybersecurity Operation Solutions
  • By Application:
    • Threat Detection & Prevention
    • Threat Investigation & Response
    • Identity & Access Analytics
    • Fraud Detection & Prevention
    • Data Protection & Privacy Intelligence
    • Risk & Compliance Intelligence
    • Vulnerability & Exposure Intelligence
    • Security Operations Optimization
    • Other Applications
  • By Deployment Mode:
    • Cloud
    • On-premises
  • By Vertical:
    • BFSI
    • Retail & E-commerce
    • Government & Defense
    • Manufacturing
    • Healthcare & Life Sciences
    • Media & Entertainment
    • Telecommunications
    • Automotive
    • Transportation & Logistics
    • Technology & Software
    • Others (Oil & Gas
    • Energy & Utilities
    • and Education)
Regions Covered North America, Asia Pacific, Europe, Middle East & Africa, Latin America

WHAT IS IN IT FOR YOU: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET REPORT CONTENT GUIDE

artificial-intelligence-ai-cyber-security-market Content Guide

DELIVERED CUSTOMIZATIONS

We have successfully delivered the following deep-dive customizations:

CLIENT REQUEST CUSTOMIZATION DELIVERED VALUE ADDS
Leading BFSI Firm
  • Assessment of AI-driven security solutions on the basis of detection accuracy, automation aptitude, and its convergence with existing security products
  • Coverage of cloud, endpoint and network security environment
  • Assistance with choosing appropriate AI-enabled security solutions
  • Improves system-wide visibility
  • Decrease detection and response time
  • Improves security posture
Leading Telecommunication Vendor
  • Analysis of vendor solutions in identity protection, threat intelligence, and security analytics
  • Evaluation of performance indicators, scalability features, and operational effectiveness
  • Allowed comparisons between platforms to enable better purchase decisions
  • Facilitate a deployment of a standards-based, scalable security program
  • Bring increased efficiency and cost-effectiveness

RECENT DEVELOPMENTS

  • March 2026 : Palo Alto Networks launched a secure browser designed for modern digital environments, increasing protection against emerging risks from advanced workflows. The move strengthens its platform strategy and focus on securing the evolving enterprise workspace.
  • March 2026 : Microsoft introduced enhanced security features in 2026 through its Security Copilot, significantly increasing the ability of teams to detect threats in real-time and respond faster. The system increases efficiency by analyzing large volumes of security data and delivering actionable insights.
  • February 2026 : Google Cloud introduced advanced security features for threat management, increasing the speed of threat detection, strengthening identity protection, and enhancing automated response capabilities.

 

Table of Contents

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TITLE
PAGE NO
1
INTRODUCTION
 
 
 
15
2
EXECUTIVE SUMMARY
 
 
 
 
3
PREMIUM INSIGHTS
 
 
 
 
4
MARKET OVERVIEW
Presents a concise view of industry direction, strategic priorities, and key indicators influencing market momentum.
 
 
 
 
 
4.1
INTRODUCTION
 
 
 
 
4.2
MARKET DYNAMICS
 
 
 
 
 
4.2.1
DRIVERS
 
 
 
 
4.2.2
RESTRAINTS
 
 
 
 
4.2.3
OPPORTUNITIES
 
 
 
 
4.2.4
CHALLENGES
 
 
 
4.3
UNMET NEEDS AND WHITE SPACES
 
 
 
 
4.4
INTERCONNECTED MARKETS AND CROSS-SECTOR OPPORTUNITIES
 
 
 
 
4.5
STRATEGIC MOVES BY PLAYERS
 
 
 
5
INDUSTRY TRENDS
Maps the market evolution with focus on trend catalysts, risk factors, and growth opportunities across segments.
 
 
 
 
 
5.1
PORTER’S FIVE FORCES ANALYSIS
 
 
 
 
5.2
MACROECONOMIC OUTLOOK
 
 
 
 
 
5.2.1
INTRODUCTION
 
 
 
 
5.2.2
GDP TRENDS AND FORECAST
 
 
 
 
5.2.3
TRENDS IN AI-DRIVEN SECURITY OPERATIONS (SOC) & THREAT DETECTION
 
 
 
 
5.2.4
TRENDS IN GLOBAL NETWORK & EDGE SECURITY INDUSTRY
 
 
 
5.3
SUPPLY CHAIN ANALYSIS
 
 
 
 
 
5.4
ECOSYSTEM ANALYSIS
 
 
 
 
 
5.5
PRICING ANALYSIS
 
 
 
 
 
 
5.5.1
AVERAGE SELLING PRICE OF OFFERING, BY KEY PLAYER,
 
 
 
 
5.5.2
AVERAGE SELLING PRICE, BY APPLICATION,
 
 
 
5.6
KEY CONFERENCES AND EVENTS, 2026-2027
 
 
 
 
5.7
TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
 
 
 
 
5.8
INVESTMENT AND FUNDING SCENARIO
 
 
 
 
5.9
CASE STUDY ANALYSIS
 
 
 
6
TECHNOLOGICAL ADVANCEMENTS, AI-DRIVEN IMPACT, AND PATENTS
 
 
 
 
 
6.1
KEY TECHNOLOGIES
 
 
 
 
 
6.1.1
GENERATIVE AI
 
 
 
 
6.1.2
BLOCKCHAIN
 
 
 
 
6.1.3
PREDICTIVE ANALYTICS
 
 
 
6.2
COMPLEMENTARY TECHNOLOGIES
 
 
 
 
 
6.2.1
TOKENIZATION
 
 
 
 
6.2.2
AR/VR
 
 
 
 
6.2.3
CLOUD COMPUTING
 
 
 
6.3
ADJACENT TECHNOLOGIES
 
 
 
 
 
6.3.1
QUANTUM COMPUTING
 
 
 
 
6.3.2
IOT
 
 
 
 
6.3.3
BIG DATA
 
 
 
 
6.3.4
5G
 
 
 
6.4
TECHNOLOGY ROADMAP
 
 
 
 
6.5
PATENT ANALYSIS
 
 
 
 
 
 
6.5.1
METHODOLOGY
 
 
 
 
6.5.2
PATENTS FILED, BY DOCUMENT TYPE, 2016–2025
 
 
 
 
6.5.3
INNOVATION AND PATENT APPLICATIONS
 
 
 
 
6.5.4
TOP APPLICANTS
 
 
7
REGULATORY LANDSCAPE
 
 
 
 
 
7.1
REGIONAL REGULATIONS AND COMPLIANCE
 
 
 
 
 
7.1.1
REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
 
 
 
 
7.1.2
INDUSTRY STANDARDS
 
 
8
CUSTOMER LANDSCAPE & BUYER BEHAVIOR
 
 
 
 
 
8.1
INTRODUCTION
 
 
 
 
8.2
DECISION-MAKING PROCESS
 
 
 
 
8.3
KEY STAKEHOLDERS INVOLVED IN BUYING PROCESS AND THEIR EVALUATION CRITERIA
 
 
 
 
 
8.3.1
KEY STAKEHOLDERS IN BUYING PROCESS
 
 
 
 
8.3.2
BUYING CRITERIA
 
 
 
8.4
ADOPTION BARRIERS & INTERNAL CHALLENGES
 
 
 
 
8.5
UNMET NEEDS OF VARIOUS END USERS
 
 
 
9
AI IN CYBERSECURITY MARKET, BY OFFERING
Market Size, Volume & Forecast – USD Million
 
 
 
 
 
9.1
INTRODUCTION
 
 
 
 
 
9.1.1
OFFERING: AI IN CYBERSECURITY MARKET DRIVERS
 
 
 
9.2
SOLUTION
 
 
 
 
 
9.2.1
BY TYPE
 
 
 
 
 
9.2.1.1
AI-NATIVE SECURITY PLATFORMS
 
 
 
 
9.2.1.2
AI-EMBEDDED SECURITY PRODUCTS
 
 
 
9.2.2
BY DEPLOYMENT
 
 
 
 
 
9.2.2.1
CLOUD
 
 
 
 
9.2.2.2
ON-PREMISES
 
 
9.3
SERVICES
 
 
 
 
 
9.3.1
PROFESSIONAL SERVICES
 
 
 
 
 
9.3.1.1
CONSULTING SERVICES
 
 
 
 
9.3.1.2
DEPLOYMENT & INTEGRATION
 
 
 
 
9.3.1.3
CUSTOM DEVELOPMENT
 
 
 
 
9.3.1.4
TRAINING & ENABLEMENT
 
 
 
9.3.2
MANAGED SERVICES
 
 
 
 
 
9.3.2.1
MANAGED DETECTION & RESPONSE (MDR)
 
 
 
 
9.3.2.2
MANAGED SIEM & SOC SERVICES
 
 
 
 
9.3.2.3
THREAT HUNTING AS A SERVICE
 
 
 
 
9.3.2.4
CLOUD SECURITY MANAGEMENT
 
10
AI IN CYBERSECURITY MARKET, BY SECURITY TYPE
Market Size, Volume & Forecast – USD Million
 
 
 
 
 
10.1
INTRODUCTION
 
 
 
 
 
10.1.1
SECURITY TYPE: AI IN CYBERSECURITY MARKET DRIVERS
 
 
 
10.2
ENDPOINT SECURITY & MANAGEMENT
 
 
 
 
 
10.2.1
ANTIVIRUS AND ANTI-MALWARE
 
 
 
 
10.2.2
ENDPOINT DETECTION AND RESPONSE (EDR)
 
 
 
 
10.2.3
PATCH MANAGEMENT
 
 
 
 
10.2.4
OTHERS
 
 
 
10.3
APPLICATION SECURITY
 
 
 
 
 
10.3.1
SECURE DEVELOPMENT TOOLS
 
 
 
 
10.3.2
WEB APPLICATION FIREWALL
 
 
 
 
10.3.3
OTHERS (SECURE SOFTWARE DEVELOPMENT LIFE CYCLE, API SECURITY)
 
 
 
10.4
NETWORK SECURITY
 
 
 
 
 
10.4.1
INTRUSION DETECTION AND PREVENTION SYSTEM (IPS)
 
 
 
 
10.4.2
NETWORK ACCESS CONTROL (NAC)
 
 
 
 
10.4.3
VIRTUAL PRIVATE NETWORK (VPN)
 
 
 
 
10.4.4
NETWORK FIREWALLS
 
 
 
 
10.4.5
OTHERS (NETWORK TRAFFIC ANALYSIS AND ANOMALY DETECTION)
 
 
 
10.5
CLOUD SECURITY
 
 
 
 
 
10.5.1
CLOUD ACCESS SECURITY BROKER (CASB)
 
 
 
 
10.5.2
SECURITY POSTURE MANAGEMENT
 
 
 
10.6
DATA SECURITY
 
 
 
 
10.7
IDENTITY AND ACCESS MANAGEMENT
 
 
 
 
10.8
ENCRYPTION & TOKENIZATION
 
 
 
 
10.9
CYBERSECURITY OPERATION SOLUTIONS
 
 
 
11
AI IN CYBERSECURITY MARKET, BY APPLICATION
Market Size, Volume & Forecast – USD Million
 
 
 
 
 
11.1
INTRODUCTION
 
 
 
 
 
11.1.1
APPLICATION: AI IN CYBERSECURITY MARKET DRIVERS
 
 
 
11.2
IDENTITY & ACCESS MANAGEMENT (IAM)
 
 
 
 
 
11.2.1
ACCESS POLICY ENFORCEMENT
 
 
 
 
11.2.2
USER PROVISIONING & DEPROVISIONING
 
 
 
 
11.2.3
SINGLE SIGN-ON (SSO)
 
 
 
 
11.2.4
IDENTITY GOVERNANCE & ADMINISTRATION (IGA)
 
 
 
 
11.2.5
MULTI-FACTOR AUTHENTICATION (MFA)
 
 
 
11.3
THREAT DETECTION & RESPONSE
 
 
 
 
 
11.3.1
ENDPOINT DETECTION & RESPONSE (EDR)
 
 
 
 
11.3.2
NETWORK DETECTION (NDR / IDS)
 
 
 
 
11.3.3
SIEM & THREAT ANALYTICS
 
 
 
 
11.3.4
THREAT INTELLIGENCE
 
 
 
11.4
SECURITY OPERATIONS AUTOMATION
 
 
 
 
 
11.4.1
SECURITY ORCHESTRATION, AUTOMATION, AND RESPONSE (SOAR)
 
 
 
 
11.4.2
INCIDENT RESPONSE AUTOMATION
 
 
 
 
11.4.3
AI SECURITY ASSISTANTS/COPILOTS (SOC AUGMENTATION)
 
 
 
 
11.4.4
ALERT TRIAGE & PRIORITIZATION
 
 
 
11.5
DATA SECURITY
 
 
 
 
 
11.5.1
DATA ENCRYPTION & TOKENIZATION
 
 
 
 
11.5.2
DATA DISCOVERY & CLASSIFICATION
 
 
 
 
11.5.3
DATA ACCESS MONITORING
 
 
 
 
11.5.4
INSIDER THREAT DETECTION
 
 
 
 
11.5.5
DATA LOSS/LEAKAGE DETECTION (DLP)
 
 
 
11.6
RISK & COMPLIANCE MANAGEMENT
 
 
 
 
 
11.6.1
AUTOMATED COMPLIANCE AUDITING
 
 
 
 
11.6.2
AUDIT TRAIL GENERATION
 
 
 
 
11.6.3
REGULATORY COMPLIANCE REPORTING
 
 
 
 
11.6.4
RISK SCORING & PRIORITIZATION
 
 
 
 
11.6.5
THREAT MODELING
 
 
 
 
11.6.6
INCIDENT RESPONSE PLANNING
 
 
 
11.7
FRAUD DETECTION & PREVENTION
 
 
 
 
 
11.7.1
TRANSACTION MONITORING
 
 
 
 
11.7.2
BEHAVIORAL FRAUD ANALYTICS
 
 
 
 
11.7.3
PAYMENT FRAUD DETECTION
 
 
 
 
11.7.4
ACCOUNT TAKEOVER DETECTION
 
 
 
 
11.7.5
PHISHING & SOCIAL ENGINEERING DETECTION
 
 
 
11.8
VULNERABILITY & EXPOSURE MANAGEMENT
 
 
 
 
 
11.8.1
VULNERABILITY SCANNING & ASSESSMENT
 
 
 
 
11.8.2
PATCH MANAGEMENT
 
 
 
 
11.8.3
CONFIGURATION MANAGEMENT
 
 
 
 
11.8.4
EXPOSURE PRIORITIZATION (AI-BASED RISK RANKING)
 
 
 
 
11.8.5
BREACH & ATTACK SIMULATION
 
 
 
11.9
OTHER APPLICATIONS (
 
 
 
12
AI IN CYBERSECURITY MARKET, BY VERTICAL
Market Size, Volume & Forecast – USD Million
 
 
 
 
 
12.1
INTRODUCTION
 
 
 
 
 
12.1.1
VERTICAL: AI IN CYBERSECURITY MARKET DRIVERS
 
 
 
12.2
BFSI
 
 
 
 
12.3
RETAIL & E-COMMERCE
 
 
 
 
12.4
GOVERNMENT & DEFENSE
 
 
 
 
12.5
MANUFACTURING
 
 
 
 
12.6
HEALTHCARE & LIFE SCIENCES
 
 
 
 
12.7
MEDIA & ENTERTAINMENT
 
 
 
 
12.8
TELECOMMUNICATIONS
 
 
 
 
12.9
AUTOMOTIVE, TRANSPORTATION & LOGISTICS
 
 
 
 
12.10
TECHNOLOGY & SOFTWARE
 
 
 
 
12.11
OTHERS (OIL & GAS, ENERGY & UTILITIES, AND EDUCATION)
 
 
 
13
AI IN CYBERSECURITY MARKET, BY REGION
Market Size, Volume & Forecast – USD Million
 
 
 
 
 
13.1
INTRODUCTION
 
 
 
 
13.2
NORTH AMERICA
 
 
 
 
 
13.2.1
NORTH AMERICA: MARKET DRIVERS
 
 
 
 
13.2.2
US
 
 
 
 
13.2.3
CANADA
 
 
 
13.3
EUROPE
 
 
 
 
 
13.3.1
EUROPE: MARKET DRIVERS
 
 
 
 
13.3.2
UNITED KINGDOM
 
 
 
 
13.3.3
GERMANY
 
 
 
 
13.3.4
FRANCE
 
 
 
 
13.3.5
ITALY
 
 
 
 
13.3.6
SPAIN
 
 
 
 
13.3.7
REST OF EUROPE (NETHERLANDS, POLAND, AUSTRIA, AND OTHERS)
 
 
 
13.4
ASIA PACIFIC
 
 
 
 
 
13.4.1
ASIA PACIFIC: MARKET DRIVERS
 
 
 
 
13.4.2
CHINA
 
 
 
 
13.4.3
INDIA
 
 
 
 
13.4.4
JAPAN
 
 
 
 
13.4.5
ASEAN
 
 
 
 
13.4.6
SOUTH KOREA
 
 
 
 
13.4.7
AUSTRALIA & NEW ZEALAND
 
 
 
 
13.4.8
REST OF ASIA PACIFIC (BANGLADESH, PAKISTAN, SRI LANKA, AND OTHERS)
 
 
 
13.5
MIDDLE EAST & AFRICA
 
 
 
 
 
13.5.1
MIDDLE EAST & AFRICA: MARKET DRIVERS
 
 
 
 
13.5.2
KSA
 
 
 
 
13.5.3
UAE
 
 
 
 
13.5.4
TURKEY
 
 
 
 
13.5.5
EGYPT
 
 
 
 
13.5.6
SOUTH AFRICA
 
 
 
 
13.5.7
REST OF MIDDLE EAST & AFRICA (NIGERIA, IRAQ, KUWAIT, IRAN, ANGOLA, QATAR, AND OTHERS)
 
 
 
13.6
LATIN AMERICA
 
 
 
 
 
13.6.1
LATIN AMERICA: MARKET DRIVERS
 
 
 
 
13.6.2
BRAZIL
 
 
 
 
13.6.3
MEXICO
 
 
 
 
13.6.4
ARGENTINA
 
 
 
 
13.6.5
REST OF LATIN AMERICA (COLOMBIA, ECUADOR, AND OTHERS)
 
 
14
COMPETITIVE LANDSCAPE
 
 
 
 
 
14.1
OVERVIEW
 
 
 
 
14.2
KEY PLAYER COMPETITIVE STRATEGIES/RIGHT TO WIN, 2021 -
 
 
 
 
14.3
REVENUE ANALYSIS, 2021 -
 
 
 
 
 
14.4
MARKET SHARE ANALYSIS,
 
 
 
 
 
14.5
PRODUCT COMPARISON
 
 
 
 
 
14.6
COMPANY EVALUATION MATRIX: KEY PLAYERS,
 
 
 
 
 
 
14.6.1
STARS
 
 
 
 
14.6.2
EMERGING LEADERS
 
 
 
 
14.6.3
PERVASIVE PLAYERS
 
 
 
 
14.6.4
PARTICIPANTS
 
 
 
 
14.6.5
COMPANY FOOTPRINT: KEY PLAYERS,
 
 
 
 
 
14.6.5.1
COMPANY FOOTPRINT
 
 
 
 
14.6.5.2
OFFERING FOOTPRINT
 
 
 
 
14.6.5.3
SECURITY TYPE FOOTPRINT
 
 
 
 
14.6.5.4
APPLICATION FOOTPRINT
 
 
 
 
14.6.5.5
VERTICAL FOOTPRINT
 
 
 
 
14.6.5.6
REGION FOOTPRINT
 
 
14.7
COMPANY EVALUATION MATRIX: STARTUPS/SMES,
 
 
 
 
 
 
14.7.1
PROGRESSIVE COMPANIES
 
 
 
 
14.7.2
RESPONSIVE COMPANIES
 
 
 
 
14.7.3
DYNAMIC COMPANIES
 
 
 
 
14.7.4
STARTING BLOCKS
 
 
 
 
14.7.5
COMPETITIVE BENCHMARKING: STARTUPS/SMES,
 
 
 
 
 
14.7.5.1
DETAILED LIST OF KEY STARTUPS/SMES
 
 
 
 
14.7.5.2
COMPETITIVE BENCHMARKING OF KEY STARTUPS/SMES
 
 
14.8
COMPANY VALUATION AND FINANCIAL METRICS
 
 
 
 
14.9
COMPETITIVE SCENARIO
 
 
 
 
 
14.9.1
PRODUCT LAUNCHES
 
 
 
 
14.9.2
DEALS
 
 
15
COMPANY PROFILES
 
 
 
 
 
15.1
INTRODUCTION
 
 
 
 
15.2
KEY PLAYERS
 
 
 
 
 
15.2.1
NVIDIA
 
 
 
 
15.2.2
INTEL
 
 
 
 
15.2.3
AMD
 
 
 
 
15.2.4
SAMSUNG ELECTRONICS
 
 
 
 
15.2.5
MICRON TECHNOLOGY
 
 
 
 
15.2.6
IBM
 
 
 
 
15.2.7
AWS
 
 
 
 
15.2.8
MICROSOFT
 
 
 
 
15.2.9
PALO ALTO NETWORKS
 
 
 
 
15.2.10
TRELLIX
 
 
 
 
15.2.11
CROWDSTRIKE
 
 
 
 
15.2.12
NORTON LIFELOCK
 
 
 
15.3
OTHER KEY PLAYERS
 
 
 
 
 
15.3.1
BLACKBERRY
 
 
 
 
15.3.2
THREATMETRIX
 
 
 
 
15.3.3
SIFT SCIENCE
 
 
 
 
15.3.4
ACALVIO TECHNOLOGIES
 
 
 
 
15.3.5
DARKTRACE
 
 
 
 
15.3.6
SPARKCOGNITION
 
 
 
 
15.3.7
FORTINET
 
 
 
 
15.3.8
CHECK POINT SOFTWARE TECHNOLOGIES
 
 
 
 
15.3.9
HIGH TECH BRIDGE
 
 
 
 
15.3.10
DEEP INSTINCT
 
 
 
 
15.3.11
SENTINELONE
 
 
 
 
15.3.12
FEEDZAI
 
 
 
 
15.3.13
VECTRA
 
 
 
 
15.3.14
ZIMPERIUM
 
 
 
 
15.3.15
PLAXIDITYX
 
 
 
 
15.3.16
NOZOMI NETWORKS
 
 
 
 
15.3.17
BITSIGHT TECHNOLOGIES
 
 
 
15.4
ANTIVIRUS COMPANIES
 
 
 
 
 
15.4.1
KASPERSKY LAB
 
 
 
 
15.4.2
BITDEFENDER
 
 
 
 
15.4.3
ESET
 
 
16
RESEARCH METHODOLOGY
 
 
 
 
 
16.1
RESEARCH DATA
 
 
 
 
 
16.1.1
SECONDARY DATA
 
 
 
 
 
16.1.1.1
KEY DATA FROM SECONDARY SOURCES
 
 
 
 
16.1.1.2
LIST OF KEY SECONDARY SOURCES
 
 
 
16.1.2
PRIMARY DATA
 
 
 
 
 
16.1.2.1
KEY DATA FROM PRIMARY SOURCES
 
 
 
 
16.1.2.2
KEY PRIMARY PARTICIPANTS
 
 
 
 
16.1.2.3
BREAKDOWN OF PRIMARY INTERVIEWS
 
 
 
 
16.1.2.4
KEY INDUSTRY INSIGHTS
 
 
16.2
MARKET SIZE ESTIMATION
 
 
 
 
 
16.2.1
BOTTOM-UP APPROACH
 
 
 
 
16.2.2
TOP-DOWN APPROACH
 
 
 
 
16.2.3
MARKET SIZE CALCULATION FOR BASE YEAR
 
 
 
16.3
MARKET FORECAST APPROACH
 
 
 
 
 
16.3.1
SUPPLY SIDE
 
 
 
 
16.3.2
DEMAND SIDE
 
 
 
16.4
DATA TRIANGULATION
 
 
 
 
16.5
FACTOR ANALYSIS
 
 
 
 
16.6
RESEARCH ASSUMPTIONS AND LIMITATIONS
 
 
 
 
16.7
RISK ASSESSMENT
 
 
 
17
APPENDIX
 
 
 
 
 
17.1
DISCUSSION GUIDE
 
 
 
 
17.2
KNOWLEDGESTORE: MARKETANDMARKETS’ SUBSCRIPTION PORTAL
 
 
 
 
17.3
CUSTOMIZATION OPTIONS
 
 
 
 
17.4
RELATED REPORTS
 
 
 
 
17.5
AUTHOR DETAILS
 
 
 

Methodology

The research methodology for the AI in cybersecurity market report relied on extensive secondary sources and directories, as well as reputable open-source databases, to identify and collect relevant information for this technical and market-oriented study. In-depth interviews were conducted with primary respondents, including end users, senior executives from multiple companies offering AI in cybersecurity solutions and services, and industry consultants, to obtain and verify critical qualitative and quantitative information and to assess market prospects and industry trends.

Secondary Research

During the secondary research process, various secondary sources were consulted to identify and collect information for the study. The secondary sources included annual reports, press releases, and investor presentations of companies; white papers; and certified publications.
Secondary research was used to gather key information on the industry’s value chain, the market’s monetary chain, the overall pool of key players, market classification, and segmentation based on industry trends, regional markets, and key developments from both market and technology-oriented perspectives.

Primary Research

In the primary research process, a diverse range of stakeholders from both the supply and demand sides of the AI in cybersecurity ecosystem were interviewed to gather qualitative and quantitative insights specific to this market. From the supply side, key industry experts, such as chief executive officers (CEOs), vice presidents (VPs), marketing directors, technology & innovation directors, and technical leads from vendors offering AI in cybersecurity software & services, were consulted. Additionally, system integrators, service providers, and IT service firms that implement and support the AI in cybersecurity solutions were included in the study. On the demand side, input from IT decision-makers, infrastructure managers, and business heads from prominent industry verticals was collected to understand user perspectives and adoption challenges within the targeted industries.
The primary research ensured that all crucial parameters affecting the AI in cybersecurity market, including technological advancements and evolving use cases, as well as regulatory and compliance needs, were considered. Each factor was thoroughly analyzed, verified through primary research, and evaluated to obtain precise quantitative and qualitative data for this market.
Once the initial phase of market engineering was completed, which included detailed calculations for market statistics, segment-specific growth forecasts, and data triangulation, a second round of primary research was conducted. This step was crucial for refining and validating critical data points, such as AI in cybersecurity offerings (software, and services), industry adoption trends, the competitive landscape, and key market dynamics like demand drivers (Automated SOC workflows & incident response (SOAR/XDR, AI-powered cloud workload & API security), challenges (Model inversion and data extraction attacks can expose sensitive training data and important business information), and opportunities (Growth of AI-driven cloud security posture management (CSPM) & workload protection platforms, growing use of artificial intelligence in identity threat detection and response (ITDR), restraints (Data silos are restricting unified thread visibility across endpoints, cloud, and network layers).
In the comprehensive market engineering process, the top-down and bottom-up approaches, along with several data triangulation methods, were extensively employed to estimate and forecast the overall market segments and subsegments listed in this report. Extensive qualitative and quantitative analysis was conducted across the complete market engineering process to capture critical information/insights throughout the report.

Artificial Intelligence in Cybersecurity Market Size, and Share

Note: Tier 1 companies' revenue is more than USD 10 billion; tier 2 companies' revenue ranges between USD 1 billion and USD 10 billion; and tier 3 companies' revenue ranges between USD 500 million and USD 1 billion.

To know about the assumptions considered for the study, download the pdf brochure

Market Size Estimation

The top-down and bottom-up approaches were employed to estimate and forecast AI in cybersecurity market, as well as its dependent submarkets. This multi-layered analysis was further reinforced through data triangulation, which incorporated primary and secondary research inputs. The market figures were also validated against the existing MarketsandMarkets repository for accuracy.

Artificial Intelligence in Cybersecurity Market : Top-Down and Bottom-Up Approach

Artificial Intelligence in Cybersecurity Market Top Down and Bottom Up Approach

Data Triangulation

The market was divided into several segments and subsegments after determining the overall market size using the market size estimation processes described above. To complete the overall market engineering process and determine the exact statistics for each market segment and subsegment, data triangulation and market segmentation procedures were employed, wherever applicable. The overall market size was then used in the top-down approach to estimate the size of other individual markets by applying percentage splits to the market segmentation.

Market Definition

According to NVIDIA, AI in cybersecurity represents an advanced approach that leverages accelerated computing and deep learning to detect, analyze, and respond to cyber threats in real time. It enables organizations to process vast volumes of security data across networks, endpoints, and cloud environments to identify anomalies and potential attacks with greater accuracy. By utilizing GPU-powered AI models and high-performance analytics, these solutions enhance threat intelligence, automate security operations, and improve response efficiency. AI-driven cybersecurity platforms support scalable, adaptive protection by continuously learning from evolving threat patterns and minimizing manual intervention. This approach plays a critical role in strengthening enterprise security posture, protecting digital assets, and ensuring resilient operations across modern IT infrastructures.

Key Stakeholders

  • Vendors offering AI-powered cybersecurity
  • Vendors offering cybersecurity for securing AI
  • Business analysts
  • Cloud hyperscalers
  • Consulting service providers
  • Enterprise end users
  • Distributors and value-added resellers
  • Government agencies
  • Independent software vendors
  • Managed service providers
  • Market research and consulting firms
  • Support & maintenance service providers
  • System integrators (SIs)/Migration service providers
  • Generative AI technology providers

Report Objectives

  • To define, describe, and predict the AI in the cybersecurity market by offering (software and services), security type, application, and vertical  
  • To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing market growth  
  • To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders  
  • To forecast the market size of segments with respect to five main regions: North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America  
  • To analyze each submarket with respect to individual growth trends, prospects, and contributions to the overall AI in cybersecurity market  
  • To analyze competitive developments, such as partnerships, product launches, mergers & acquisitions, in the AI in cybersecurity market  
  • To analyze the impact of macroeconomic factors on AI in cybersecurity market across all regions

Available customizations:

Using the provided market data, MarketsandMarkets offers customizations tailored to the company’s specific needs. The following customization options are available for the report.

Product Analysis

  • Product comparative analysis, which gives a detailed comparison of innovative products being offered by prominent vendors

Geographic Analysis

  • Further breakup of additional European countries by offering, security type, application, and vertical.
  • Further breakup of additional Asia Pacific countries by offering, security type, application, and vertical.
  • Further breakup of additional Middle East & African countries by offering, security type, application, and vertical.
  • Further breakup of additional Latin American countries by offering, security type, application, and vertical.

Company Information

  • Detailed analysis and profiling of additional market players (up to five)

 

Key Questions Addressed by the Report

What is the projected size of the global AI in cybersecurity market?

The global AI in cybersecurity market is projected to grow from USD 25.53 billion in 2026 to USD 50.83 billion by 2031, at a CAGR of 14.8% during the forecast period. Growth is driven by the increasing frequency of cyberattacks, expanding cloud adoption, and growing demand for AI-powered threat detection and automated security operations.

Which segment holds the largest share of the AI in cybersecurity market?

The software segment is projected to hold the largest share of the AI in cybersecurity market in 2026. By security type, the endpoint security & management segment leads the market with an 18.75% share, driven by the need for real-time endpoint protection and automated threat detection.

What are the key trends driving the AI in cybersecurity market?

Key trends include the adoption of AI-native security platforms, AI-enhanced threat detection, autonomous security operations, predictive threat intelligence, cloud workload protection, identity threat detection and response (ITDR), and AI-powered security analytics.

Which region holds the largest share of the AI in cybersecurity market?

North America is estimated to hold the largest share of the AI in cybersecurity market, accounting for 35.5% in 2026. The region's leadership is supported by early adoption of AI technologies, strong cybersecurity investments, and the presence of major technology providers.

Who are the key players in the AI in cybersecurity market?

Key companies operating in the AI in cybersecurity market include Microsoft (US), Palo Alto Networks (US), AWS (US), Google (US), IBM (US), Cisco (US), CrowdStrike (US), SentinelOne (US), Darktrace (UK), and Fortinet (US). These companies are investing heavily in AI-driven threat detection, automation, and next-generation cybersecurity platforms.

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