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Edge AI For Cybersecurity Market Size Forecast: How Big Could The Market Get By 2030?
The edge AI for cybersecurity market has experienced substantial growth in recent years. It is projected to expand from $45.38 billion in 2025 to $62.94 billion in 2026, at a compound annual growth rate (CAGR) of 38.7%. This historical growth can be attributed to various factors, including the increasing number of connected devices, a rise in cyberattack frequency, the early adoption of endpoint security, the expansion of IoT networks, and the limitations of cloud latency.
The edge AI for cybersecurity market size is anticipated to undergo significant expansion in the coming years. This market is predicted to reach $228.77 billion by 2030, demonstrating a compound annual growth rate (CAGR) of 38.1%. The increase observed within the forecast period can be attributed to factors such as the growing implementation of edge computing, the demand for immediate cybersecurity measures, the heightened regulatory focus on data privacy, the adoption of self-governing security systems, and the integration of AI-driven threat intelligence. Prominent trends expected during this period encompass real-time threat identification at the edge, autonomous security analytics on edge devices, low-latency cyber threat reduction, privacy-centric security processing, and distributed AI security frameworks.
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Edge AI For Cybersecurity Market Growth Backed By Core Demand Fundamentals
The increasing need for data privacy is anticipated to fuel the expansion of the edge AI for the cybersecurity market in the future. Data privacy pertains to safeguarding confidential information against unauthorized access, improper use, or revelation, simultaneously granting individuals authority over the collection, storage, and sharing of their personal data. The requirement for data privacy is escalating as both companies and individuals prioritize security due to heightened cyber threats, stricter data protection regulations, and concerns regarding digital surveillance. Edge AI for cybersecurity contributes significantly to data privacy, given that organizations are implementing AI-driven security measures to secure sensitive data, improve instantaneous threat identification, and adhere to rigorous privacy mandates. As an illustration, in November 2023, the Australian Signals Directorate, an Australia-based government agency, reported that during the 2022-23 financial year, approximately 94,000 cybercrime reports were lodged with Report Cyber. This represented a 23% rise from the preceding financial year, with a report being received on average every 6 minutes. Consequently, the increasing need for data privacy is propelling the expansion of the edge AI for the cybersecurity market.
Edge AI For Cybersecurity Market Segment Breakdown: Which Categories Lead On Revenue?
The edge AI for cybersecurity market covered in this report is segmented –
1) By Offering: Hardware, Software, Services
2) By Application: Identity And Access Management, Natural Language Processing, Data Loss Prevention, Unified Threat Management, Fraud Detection Or Anti-Fraud, Threat Intelligence, Other Applications
3) By Vertical: Banking, Financial Services And Insurance, Retail, Government And Defense, Manufacturing, Enterprise, Healthcare, Automotive And Transportation, Other Verticals
Subsegments:
1) By Hardware: Edge AI Chips, Security Modules, Network Appliances, Gateways
2) By Software: Threat Detection Software, Anomaly Detection Algorithms, AI-Based Security Analytics, Endpoint Protection Platforms
3) By Services: Deployment & Integration Services, Consulting Services, Support & Maintenance, Managed Security Services
Edge AI For Cybersecurity Market Growth Trends Reshaping The Competitive Landscape
Companies operating significantly within the edge AI for cybersecurity market are concentrating on developing innovative solutions, including the integration of TinyML advancements, to improve real-time threat detection and reduce computational demands. TinyML (Tiny Machine Learning) allows for ultra-efficient AI models to run on low-power edge devices, providing faster security responses with minimal energy consumption. For example, in March 2025, CISO Global Inc., a US-based IT service management company, launched CISO Edge, an AI-powered cloud security solution intended to strengthen enterprise cyber resilience. It employs AI-driven analytics to offer real-time threat detection, continuous monitoring, and adaptive risk management across cloud-first, hybrid, and remote environments. CISO Edge incorporates advanced machine learning to automate security responses, thereby reducing human intervention and enhancing operational efficiency while ensuring adherence to stringent cybersecurity regulations.
Edge AI For Cybersecurity Market Leading Players And Competitive Positioning
Major companies operating in the edge AI for cybersecurity market are Samsung Electronics Co Ltd., NVIDIA Corporation, Intel Corporation, IBM Corporation, Cisco Systems Inc., Fortinet Inc., Check Point Software Technologies, FireEye Inc., CrowdStrike Holdings Inc, CyberArk Software Ltd., SentinelOne Inc., Darktrace Holdings Ltd., Cybereason, Exabeam, Securonix Inc., Vectra AI Inc., Nozomi Networks, Sophos Ltd., Acalvio Technologies Inc., Cylance Inc., AI EdgeLabs
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Edge AI For Cybersecurity Market Geographic Analysis: Where Is Demand Rising Fastest?
North America was the largest region in the edge AI for cybersecurity market in 2025. The regions covered in the edge AI for cybersecurity market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.
