Dublin, Oct. 23, 2025 (GLOBE NEWSWIRE) — The “Artificial Intelligence in Cybersecurity Market – Global Forecast 2025-2032” report has been added to ResearchAndMarkets.com’s offering.
Artificial intelligence in cybersecurity is reshaping enterprise defense strategies, equipping organizations with greater resilience, automation, and threat response. Senior decision-makers now recognize AI as a catalyst for safeguarding digital assets, enabling proactive management of sophisticated risks within modern business environments.
Market Snapshot: Artificial Intelligence in Cybersecurity Market
The Artificial Intelligence in Cybersecurity Market expanded from USD 23.12 billion in 2024 to USD 28.51 billion in 2025 and is projected to reach USD 136.18 billion by 2032, exhibiting a CAGR of 24.81%. This growth reflects the surge in advanced cyber threats, multiplication of digital transformation initiatives, and the critical role AI now plays in pre-emptive security and automated incident response. As businesses advance cloud adoption and digitize core operations, the market’s momentum is sustained by the integration of AI solutions into organizational risk frameworks, driving the transformation of legacy security postures across every major sector.
Scope & Segmentation of the AI Cybersecurity Market
This report delivers a detailed segmentation of the AI in cybersecurity market, offering essential context for executive planning and investment across multiple domains:
- Offering Types: Services, including consulting, integration, and managed detection, as well as packaged software and security hardware solutions.
- Technologies: Computer vision, machine learning, natural language processing, neural networks, predictive analytics, and robotic process automation power key applications in cyber defense.
- Security Types: Application security, cloud security, data protection, endpoint security, identity and access management, network security, and threat intelligence form the backbone of organizational defense strategies.
- Deployment Modes: Cloud and on-premise deployment platforms allow organizations to address scalability needs and governance preferences.
- Applications: Endpoint protection, fraud detection, identity and access management, malware detection, network monitoring, security automation, threat intelligence, and vulnerability management help organizations tackle evolving attack surfaces.
- End-User Verticals: BFSI, education, energy and utilities, entertainment and media, government and defense, healthcare, IT and telecom, manufacturing, and retail and e-commerce demonstrate broad market applicability.
- Regions Covered: Americas (United States, Canada, Mexico, Brazil, Argentina, Chile, Colombia, Peru), Europe, Middle East and Africa (United Kingdom, Germany, France, Russia, Italy, Spain, Netherlands, Sweden, Poland, Switzerland, United Arab Emirates, Saudi Arabia, Qatar, Turkey, Israel, South Africa, Nigeria, Egypt, Kenya), and Asia-Pacific (China, India, Japan, Australia, South Korea, Indonesia, Thailand, Malaysia, Singapore, Taiwan) highlight global reach and regulatory diversity.
Key Takeaways for Senior Decision-Makers
- AI integration automates and refines threat detection, enabling quicker and more accurate responses to rising security challenges for agile security postures.
- Machine learning and behavioral analytics facilitate a shift from reliance on traditional signature-based models to dynamic anomaly and pattern recognition approaches.
- Robotic process automation combined with AI-driven threat intelligence accelerates predictive risk management and enhances visibility across digital assets.
- The fusion of AI with big data and scalable cloud architectures ensures organizations can analyze network activity in real time and transition toward adaptive security models.
- Regional differences in regulatory and data privacy frameworks require organizations to tailor their AI adoption strategies, balancing compliance, scalability, and localized controls.
- Strategic partnerships, including mergers and acquisitions, continue to shape innovation as leading providers embed AI into service offerings and product portfolios.
Tariff Impact on Global AI Cybersecurity Supply Chains
Recent tariffs imposed by the United States on imported semiconductors and AI-specific hardware in 2025 have redirected supply chain strategies worldwide. To mitigate higher component costs, suppliers are reconsidering sourcing and evaluating domestic production for critical hardware. Software and cloud service vendors have responded with new pricing models, leading enterprises to reassess technology acquisition and long-term budget planning. Collaborative agreements between North American and international firms are becoming more prevalent, adapting the competitive landscape and bolstering localized supply chain resilience.
Methodology & Data Sources
A multi-tiered research approach underpins this report, combining direct interviews with AI cybersecurity executives and technology specialists with in-depth secondary analysis from proprietary datasets and validated industry sources. Statistical modeling and scenario analysis support robust, data-driven forecasting.
Why This Report Matters
- Empowers leaders to benchmark AI cybersecurity adoption rates, risk priorities, and operational strategies against peers globally for informed decision-making.
- Delivers actionable recommendations on aligning AI deployments with data governance and regulatory mandates.
- Supports investment planning by mapping strategic shifts, industry alliances, and evolving supply chain impacts arising from tariff and regulatory trends.
Key Attributes
Key Topics Covered
1. Preface
2. Research Methodology
3. Executive Summary
4. Market Overview
5. Market Insights
5.1. Integration of generative AI models for real-time dynamic threat detection across network environments
5.2. Autonomous incident response systems leveraging reinforcement learning to mitigate cyberattacks
5.3. Explainable AI frameworks for regulatory compliance in enterprise security operations centers
5.4. Deep learning-driven anomaly detection for uncovering advanced persistent threats in cloud infrastructures
5.5. AI-powered identity and access management with continuous behavioral risk scoring
5.6. Machine learning-based predictive vulnerability management for proactive patch prioritization
5.7. Adversarial machine learning defenses to protect models from poisoning and evasion attacks
5.8. Zero trust architecture enhanced by AI analytics for adaptive network segmentation and policy enforcement
5.9. Zero trust security guided by AI behavioral analytics across hybrid cloud environments
5.10. Generative AI models for automated vulnerability discovery and patch prioritization
6. Cumulative Impact of United States Tariffs 2025
7. Cumulative Impact of Artificial Intelligence 2025
8. Artificial Intelligence in Cybersecurity Market, by Offering Type
8.1. Services
8.2. Solution
9. Artificial Intelligence in Cybersecurity Market, by Technology
9.1. Computer Vision
9.2. Machine Learning (ML)
9.3. Natural Language Processing (NLP)
9.4. Neural Networks
9.5. Predictive Analytics
9.6. Robotic Process Automation (RPA)
10. Artificial Intelligence in Cybersecurity Market, by Security Type
10.1. Application Security
10.2. Cloud Security
10.3. Data Security
10.4. Endpoint Security
10.5. Identity and Access Management (IAM)
10.6. Network Security
10.7. Threat Intelligence
11. Artificial Intelligence in Cybersecurity Market, by Deployment Mode
11.1. Cloud
11.2. On-Premise
12. Artificial Intelligence in Cybersecurity Market, by Application
12.1. Endpoint Protection
12.2. Fraud Detection
12.2.1. Financial Fraud Detection
12.2.2. Identity Theft Prevention
12.2.3. Payment Fraud Detection
12.3. Identity & Access Management (IAM)
12.4. Malware Detection
12.4.1. Behavioral Malware Detection
12.4.2. Heuristic-Based Malware Detection
12.4.3. Signature-Based Malware Detection
12.5. Network Monitoring & Defense
12.6. Security Automation & Orchestration
12.7. Threat Intelligence & Management
12.8. Vulnerability Management
13. Artificial Intelligence in Cybersecurity Market, by End-User
13.1. BFSI
13.2. Education
13.3. Energy & Utilities
13.4. Entertainment & Media
13.5. Government & Defense
13.6. Healthcare
13.7. IT & Telecom
13.8. Manufacturing
13.9. Retail & E-commerce
14. Artificial Intelligence in Cybersecurity Market, by Region
14.1. Americas
14.1.1. North America
14.1.2. Latin America
14.2. Europe, Middle East & Africa
14.2.1. Europe
14.2.2. Middle East
14.2.3. Africa
14.3. Asia-Pacific
15. Artificial Intelligence in Cybersecurity Market, by Group
15.1. ASEAN
15.2. GCC
15.3. European Union
15.4. BRICS
15.5. G7
15.6. NATO
16. Artificial Intelligence in Cybersecurity Market, by Country
16.1. United States
16.2. Canada
16.3. Mexico
16.4. Brazil
16.5. United Kingdom
16.6. Germany
16.7. France
16.8. Russia
16.9. Italy
16.10. Spain
16.11. China
16.12. India
16.13. Japan
16.14. Australia
16.15. South Korea
17. Competitive Landscape
17.1. Market Share Analysis
17.2. FPNV Positioning Matrix
17.3. Competitive Analysis
The key companies profiled in this Artificial Intelligence in Cybersecurity market report include:
- Acalvio Technologies, Inc.
- Advanced Micro Devices, Inc.
- Amazon Web Services, Inc.
- BitSight Technologies, Inc.
- BlackBerry Limited
- Capgemini Services SAS
- Continental AG
- Darktrace Holdings Ltd.
- Dassault Systemes S.E.
- Deep Instinct Ltd.
- Feedzai
- Gen Digital Inc.
- High-Tech Bridge SA
- Infosys Limited
- Intel Corporation
- International Business Machines Corp.
- Micron Technology, Inc.
- Nozomi Networks Inc.
- NVIDIA Corporation
- Samsung Electronics Co., Ltd.
- Securonix, Inc.
- Sentinelone Inc.
- SparkCognition Inc.
- Tenable, Inc.
- Vectra AI, Inc.
- Wipro Limited
- Zimperium, Inc.
For more information about this report visit https://www.researchandmarkets.com/r/gyaej8
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