Artificial Intelligence In Cybersecurity Market Size to Reach US$ 91.7 Billion by 2032 | CAGR of 16.2% | FMI

According to estimates, the market for artificial intelligence in cybersecurity is valued at over $16.5 billion USD. The market is anticipated to have risen at a CAGR of 16.2% during the ensuing ten years by the end of 2032 and be valued at around US$ 91.7 Billion. One of the key factors driving the market’s growth is the increasing demand for sophisticated cybersecurity and privacy solutions.

It is now possible to fundamentally move away from signature-based detection in favour of more flexible and continuous network monitoring as it deviates from expected behaviour with the aid of AI-based cybersecurity solutions.

AI is used by businesses to detect malware, fraudulent payments, hacked machines, spam and phishing attacks, and network infrastructure. The availability-cost nexus is another facet of AI development that adds to the widening of the range of destructive actors.

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North America will see continued revenue growth in Artificial Intelligence in the Cybersecurity Market throughout the Analysis Period

Due to the concentration of key players and new start-ups in the region, the expansion of government initiatives aimed at advancing technologies like artificial intelligence, the widespread use of cloud-based services, the growing sophistication of cyberattacks, and the rise in cyber threats, North America currently holds a sizeable market share.

North America dominated the artificial intelligence in cyber security market ecology in 2020, accounting for 38.3% of global sales. The expansion is thought to have been aided by the presence of well-known companies like IBM, Cisco Systems Inc., Dell Root 9B, Check Point Software Technologies Ltd., and Palo Alto Networks, which provide cutting-edge solutions and services to all the local industries.

Artificial Intelligence in the Cybersecurity Market: Competition Insights

Artificial Intelligence in Cybersecurity companies is largely setting up Joint ventures and aiming for acquisition and mergers. The key companies operating in the Artificial Intelligence in Cybersecurity Market include NVIDIA Corporation, Intel Corporation, Xilinx Inc., Samsung Electronics Co Ltd, Micron Technology Inc., Amazon Web Services, Inc., IBM Corporation, Microsoft Corporation, FireEye, Inc., Palo Alto Networks, Inc., Juniper Networks, Inc., Fortinet, Inc., Cisco Systems, Inc., Check Point Software Technologies Ltd., Imperva, McAfee LLC, LogRhythm, Inc., Sophos Ltd., NortonLifeLock Inc., Crowdstrike Holdings, Inc., Darktrace, Cylance Inc., Vectra AI, Inc., ThreatMetrix Inc., Securonix Inc., Sift Science, Acalvio Technologies, SparkCognition Inc., and Symantec Corporation.

Some of the recent developments by key providers of Artificial Intelligence in the Cybersecurity Market are as follows:

  • In March 2019, The Jetson Nano, a machine that can construct countless intelligent systems, was unveiled by NVIDIA. Modern AI applications may be run on the compact but potent CUDA-X AI computer, which offers 472 GFLOPS of computational capability while using as low as 5 watts of power.
  • In Feb 2019, Cylance unveiled the Cylance native AI platform, which provides customers all over the world with automated threat detection, prevention, forensic investigation, and response capabilities. It is done by integrating deep-learning Al algorithms into a single, agile agent for comprehensive attack surface protection.

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Key Segments Covered In Artificial Intelligence In Cybersecurity Market Survey

Artificial Intelligence in Cybersecurity Market by Offering:

Hardware

    • Processors
    • Memory
    • Network

Software

    • AI Platform
    • AI Solutions

Service

    • Deployment & Integration
    • Support & Maintenance

Artificial Intelligence in Cybersecurity Market by Deployment Type:

  • Cloud
  • On-Premise

Artificial Intelligence in Cybersecurity Market by Security Type:

  • Network Security
  • Endpoint Security
  • Application Security
  • Cloud Security

Artificial Intelligence in Cybersecurity Market by Technology:

  • Machine Learning
  • Natural Language Processing
  • Context-Aware Computing

Artificial Intelligence in Cybersecurity Market by Application:

  • Identity & Access Management
  • Risk & Compliance Management
  • Data Loss Prevention
  • Unified Threat Management
  • Security & Vulnerability Management
  • Antivirus/Antimalware
  • Fraud Detection/Anti-Fraud
  • Intrusion Detection/Prevention System
  • Threat Intelligence
  • Others

Artificial Intelligence in Cybersecurity Market by End-User:

  • BFSI
  • Retail
  • Government & Defence
  • Manufacturing
  • Infrastructure
  • Enterprise
  • Healthcare
  • Automotive & Transportation
  • Others

Artificial Intelligence in Cybersecurity Market by Region:

  • North America Artificial Intelligence in Cybersecurity Market
  • Latin America Artificial Intelligence in Cybersecurity Market
  • Europe Artificial Intelligence in Cybersecurity Market
  • Asia Pacific Artificial Intelligence in Cybersecurity Market
  • Middle East & Africa Artificial Intelligence in Cybersecurity Market

Table of Content

1. Executive Summary | Artificial Intelligence In Cybersecurity Market

1.1. Global Market Outlook

1.2. Summary of Statistics

1.3. Key Market Characteristics & Attributes

1.4. Analysis and Recommendations

2. Market Overview

2.1. Market Coverage / Taxonomy

2.2. Market Definition / Scope / Limitations

3. Market Risks and Trends Assessment

3.1. Risk Assessment

3.1.1. COVID-19 Crisis and Impact on Demand

3.1.2. COVID-19 Impact Benchmark with Previous Crisis

3.1.3. Impact on Market Value (US$ Million)

3.1.4. Assessment by Key Countries

3.1.5. Assessment by Key Market Segments

3.1.6. Action Points and Recommendation for Suppliers

3.2. Key Trends Impacting the Market

3.3. Componentulation and Product Development Trends

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About the Author

Nikhil Kaitwade

Associate Vice President at Future Market Insights, Inc. has over a decade of experience in market research and business consulting. He has successfully delivered 1500+ client assignments, predominantly in Automotive, Chemicals, Industrial Equipment, Oil & Gas, and Service industries.
His core competency circles around developing research methodology, creating a unique analysis framework, statistical data models for pricing analysis, competition mapping, and market feasibility analysis. His expertise also extends wide and beyond analysis, advising clients on identifying growth potential in established and niche market segments, investment/divestment decisions, and market entry decision-making.
Nikhil holds an MBA degree in Marketing and IT and a Graduate in Mechanical Engineering. Nikhil has authored several publications and quoted in journals like EMS Now, EPR Magazine, and EE Times.

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