Al in Cybersecurity Market worth $60.6 billion by 2028, growing at a CAGR of 21.9%: Report by MarketsandMarkets™


Chicago, Jan. 05, 2024 (GLOBE NEWSWIRE) — The global Al in Cybersecurity Market is projected to grow from USD 22.4 billion in 2023 to USD 60.6 billion by 2028, at a CAGR of 21.9% during the forecast period, according to a new report by MarketsandMarkets™.

Artificial Intelligence (AI) is revolutionizing cybersecurity, offering real-time threat detection, incident response automation, and user identity protection. It identifies shadow data, monitors data access, and prevents phishing and malware, ensuring a high-security posture. AI optimizes analysts’ time, expediting threat detection and response. Through automation, AI provides a competitive advantage, meeting the needs of today’s heightened security requirements. As AI technology advances, cybersecurity professionals need to stay ahead and adapt their strategies to leverage the benefits of AI in cybersecurity.

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List of Key Players in Al in Cybersecurity Market:

  • Intel (US)
  • Xilinx Inc. (US)
  • Samsung Electronics Co., Ltd (South Korea)
  • Micron Technology, Inc. (US)
  • IBM Corporation (US)
  • Amazon Web Services, Inc. (US)
  • Microsoft (US)
  • Palo Alto Networks Inc. (US)

Based on the offering, The offering section is further segmented into hardware, solutions and services. The hardware segment is further bifurcated into accelerators, processors, storage and network. The processors are further bifurcated into Microprocessing Unit (MPU), Graphics Processing Unit (GPU), Field Programmable Gate Arrays (FPGA), Application-Specific Integrated Circuit (ASIC), Tensor Processing Unit (TPU), and other processors. The solution segment of the report is sub-segmented into by type and by deployment mode. The by-type segment of the report is sub-segmented into software and platform. The software is split into integrated and standalone, whereas the platform is split into Application program interface (API), and machine learning framework. By deployment mode has been segmented into cloud and on-premises. The services segment is bifurcated into professional and managed services. The professional services section is segmented into consulting, training & integration, and support & maintenance.

Based on the Security Type, the market is segmented into infrastructure security, data security, application security, and other security types. The infrastructure security types include network security, endpoint security, cloud security, and other infrastructure security. Different security types play a pivotal role in shaping the AI in cybersecurity market. Endpoint security is witnessing increased integration of AI for threat detection and response, bolstering protection against evolving attacks. Network security benefits from AI-driven analytics, enhancing the ability to identify and mitigate complex threats in real-time. Cloud security relies on AI for dynamic threat intelligence, providing proactive defense mechanisms. Application security leverages AI for code analysis and vulnerability detection, ensuring robust protection. The convergence of these security types underscores the comprehensive integration of AI, contributing to the market’s growth. The dynamic interplay between AI and varied security paradigms fortifies cybersecurity frameworks, addressing multifaceted threats.

Based on the Technology, the market is segmented into machine learning, natural language processing (NLP), context-aware computing and computer vision. Machine learning is further bifurcated into deep learning, supervised learning, unsupervised learning, reinforcement learning, and neural networks. Deep learning is further bifurcated into Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Generative AI. Generative AI is further segmented into generative adversarial networks, variational autoencoders, transformative AI, and others. Natural language processing is further segmented into text analysis, chatbot security, sentiment analysis, Natural Language Generation (NLG), Named Entity Recognition (NER), And Natural Language Understanding (NLU). The context-aware computing is bifurcated into automated threat intelligence, threat hunting, and automation and orchestration. Automation and Orchestration is further segmented into Security Orchestration, Automation, and Response (SOAR) and Robotic Process Automation (RPA). Computer vision is further split into image recognition, object detection, anomaly detection, video analysis, facial recognition, and security surveillance optimization.

Based on the Application, the market is segmented into Identity and Access Management , Risk and Compliance Management [Automated Compliance Auditing, Audit Trail Generation, Regulatory Compliance Reporting, Threat Modelling, Incident Response Planning, and Others], Data Loss Prevention [Data Encryption And Tokenization, Content Discovery and Classification, User Activity Monitoring, Insider Threat Detection, Data Leak Detection, and Others], Unified Threat Management [Network Monitoring and Reporting,  Bandwidth Management, Gateway Antivirus, Bot Identification, Spam Filtering, and Others], Security & Vulnerability Management [Patch Management, Vulnerability Scanning and assessment,Security Information and Event Management (SIEM), Breach Risk Prediction, Configuration Management, and Others], Fraud Detection [Endpoint Detection and Response (EDR), Pattern Recognition, Transaction Monitoring, Geolocation Analysis, Phishing Detection, and Others], Intrusion Detection/Prevention Systems [Threshold Monitoring, Protocol-Based Intrusion Detection System (PIDS), User And Entity Behavior Analytics (UEBA), File Integrity Monitoring, Host-Based Intrusion Prevention System (HIPS), and Others] and Other Applications.  

Based on industry verticals, the AI in Cybersecurity market is segmented into BFSI, retail & eCommerce, government & defense, manufacturing, automotive, telecommunication, healthcare & life sciences, media & and entertainment, IT/ITeS and other verticals (oil & gas, energy & and utilities, and education). Across diverse industry verticals, the adoption of AI in cybersecurity is gaining traction. In finance, AI is utilized for fraud detection and risk management, enhancing transaction security. Healthcare leverages AI for patient data protection and detection of anomalies in medical records. The manufacturing sector employs AI to secure industrial control systems and prevent disruptions. Retail incorporates AI-driven solutions for threat detection in online transactions and safeguarding customer information. The widespread adoption across verticals underscores AI’s versatility, providing tailored cybersecurity solutions to address sector-specific challenges and fortify digital ecosystems.

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The AI in Cybersecurity market has been segmented into five regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America. Global regions are exhibiting varied but growing adoption of AI in cybersecurity. North America leads, with a strong focus on AI-driven threat detection and response across industries. Europe emphasizes AI for data protection, particularly in GDPR compliance. Asia-Pacific witnesses a surge in AI adoption to counter evolving cyber threats, with a focus on the financial and technology sectors. The Middle East and Africa prioritize AI for critical infrastructure protection. Latin America is increasingly integrating AI into cybersecurity strategies, with a focus on bolstering e-commerce and financial systems. The regional disparities reflect a universal trend towards leveraging AI’s capabilities to enhance cybersecurity resilience.

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