The Artificial Intelligence (AI) In Cybersecurity Market Size was valued at USD 21.89 Billion in 2023 and is expected to reach USD 111.27 Billion by 2031 and grow at a CAGR of 22.4 % over the forecast period 2024-2031.
The increasing prevalence of artificial intelligence (AI) technologies, such as natural language processing (NLP) and machine learning (ML), has become crucial in protecting, detecting, and responding to threats. The exponential surge in cyberattacks targeting high-tech companies, defense organizations, and government agencies has emphasized the necessity for advanced AI in cybersecurity.
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The integration of automation trends and intelligent data utilization in security solutions presents the opportunity for enhanced real-time threat protection. This technological advancement in sophisticated security solutions is driving the need for real-time security solutions, thereby contributing to market growth. The integration of automation and intelligent data analysis in security offerings is driving the development of more effective real-time protection mechanisms, propelling market expansion.
With speech recognition technology, Facebook facial recognition software, and Google's search engine, artificial intelligence in cyber security enables experts to examine, investigate, and comprehend cybercrime. Artificial intelligence is improving cybersecurity technology and being used to act against cybercriminals. It is built in such a way that it responds to cyber-attacks in a matter of milliseconds. The notion has a wide range of applications, including anti-fraud measures, security and vulnerability management, and others.
Provide me Drivers Restrain Opportunities and challenges for AI in the cybersecurity market.
Drivers:
The shortage of cybersecurity professionals, which makes it challenging for organizations to manually manage and respond to security incidents.
Cybercriminals are increasingly employing sophisticated techniques, such as polymorphic malware and zero-day exploits, making traditional security measures less effective.
The Continuously in cyberattacks has become a major concern worldwide, because of this the urgent need for Quick Performing cybersecurity measures. The attacks are impacting individuals, enterprises, and governments, resulting in significant financial losses. Cybercriminals are targeting endpoints, networks, and data for various reasons, including political rivalry, financial gain, damaging reputation, and advancing radical religious group interests. Cybersecurity threat trends report, showing a high percentage of organizations facing phishing attempts, malicious browser ads, crypto mining, and ransomware-related activities. The increasing sophistication of cyber threats, especially ransomware, is pushing organizations worldwide to prioritize cybersecurity solutions and services to protect critical IT infrastructure and sensitive data.
Restraints:
Integrating AI-powered cybersecurity solutions into existing infrastructure can be complex.
AI algorithms may exhibit biases based on only the data they are trained in.
Implementing AI-driven cybersecurity solutions requires significant investment in technology, resources, and training.
Opportunities
The AI-powered systems automatically respond to security incidents in real-time, minimizing response time and reducing the impact of cyber-attacks.
AI can monitor user and system behavior to identify suspicious activities or deviations.
AI can continuously learn and adapt to new cyber threats and attack techniques, enhancing the resilience of cybersecurity defenses.
Challenges
Integrating AI into existing cybersecurity infrastructure can be complex and challenging, requiring specialized skills and expertise.
Complexity To understand is an important challenge.
Compliance with cybersecurity regulations and standards may be complicated using AI.
The tensions between Russia and Ukraine have sent ripples throughout the cybersecurity realm, reshaping strategies for both nation-states and private sector firms. Rather than being standalone weapons, cyber operations are now seen as tools for coercion and deception in modern warfare. Russia's historical cyber activities have leaned towards long-term competition, blending political warfare, espionage, and disruptive campaigns to sway political outcomes. Cybersecurity companies are adopting diverse strategies tailored to their specialties. Security Operations Center (SOC) teams are on high alert, gathering actionable intelligence on Russian activities and responding swiftly to increased alerts. The focus is on fortifying defensive measures to thwart potential breaches before they occur.
Technological advancements are also underway, with companies like Palo Alto Networks expanding their arsenals to counter emerging threats from the crisis. This involves beefing up threat prevention, malware detection, and incident response capabilities to fend off ransomware, destructive attacks, and other cyber threats associated with Russian operations. The global fallout from the conflict has prompted countries and enterprises to shore up their security measures. Businesses are advised to implement multi-factor authentication, keep software updated, and stay vigilant against phishing attempts. For the long haul, adopting a Zero Trust Security Framework and Extended Detection and Response (XDR) is recommended to elevate security standards and mitigate threats. The Russia-Ukraine crisis serves as a stark reminder of the ever-changing landscape of cyber warfare and its profound impact on national security and cybersecurity practices in the private sector. The emphasis on proactive defense, technological prowess, and international collaboration underscores the adaptive response of the global cybersecurity community to these evolving challenges.
During an economic slowdown, the AI in cybersecurity market may face challenges, but it generally maintains growth. This is driven by the growing complexity of cyber threats and the increasing need for advanced security solutions. Factors like heightened mobile device usage, remote work arrangements, and greater awareness of cybersecurity contribute to its resilience. Despite economic uncertainties, the AI in cybersecurity sector continues to expand, albeit possibly at a slower pace.
By Component
Software
Service
Hardware
By Deployment
Cloud
On-Premise
By Security Type
Network Security
Endpoint Security
Application Security
Cloud Security
By Technology
Context-Aware Computing
Machine Learning
Natural Language Processing
On the basis of technology, the machine learning segment dominates the Artificial Intelligence (AI) in cybersecurity market, holding more than 45% share. This dominance stems from machine learning's capability to autonomously learn and improve from data patterns, enhancing threat detection and response mechanisms. Its ability to identify complex and evolving threats in real-time significantly bolsters cybersecurity efforts. Moreover, machine learning algorithms can continuously adapt to new attack methods, making them indispensable tools for modern cybersecurity strategies.
By Application
Identity and Access Management
Risk and Compliance Management
Data Loss Prevention
Unified Threat Management
Security and Vulnerability Management
Antivirus
Fraud Detection
Intrusion Detection and Prevention System
Threat Intelligence
Others
On the Basis Of application Fraud Detection Segment dominates the Artificial Intelligence (AI) in Cybersecurity Market with the Holding more than 20% share, Machine Learning (ML) technology is expected to experience significant growth due to the increasing use of Deep Learning (DL) across various industries. Major companies like Google and IBM are utilizing ML for email filtering and threat detection, give results of the power of these technologies in enhancing cybersecurity practices.
Organizations are increasingly shifting towards ML and DL to strengthen their cybersecurity measures. The Natural Language Processing (NLP) segment is projected to witness substantial growth in the forecast period. the critical role that NLP plays in enhancing cybersecurity practices and protecting organizations from potential threats.
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By Industry Vertical
Automotive & Transportation
Retail
BFSI
Manufacturing
Government & Defense
Enterprise
Oil & Gas
Education
Others
North America dominated the market with a holding revenue share of More than 32%. Because of the increasing number of network-connected devices, driven by the increasing of Internet of Things (IoT), 5G, and Wi-Fi 6 technologies. Industries such as automotive, healthcare, government, energy, and mining have been actively expanding their 5G networks, which has also opened potential vulnerabilities for cyber-attacks.
The leading companies are projected to invest in platforms for machine learning (ML), advanced analytics, and tools for asset mapping and visualization to monitor and evaluate in real-time. North America leads in the adoption of natural language processing (NLP), ML, and neural networks to bolster security measures and identify abnormal user behaviors and patterns. Throughout the forecast period, the global market for artificial intelligence in cybersecurity is anticipated to witness rapid growth in the Asia Pacific region. Emerging economies in the region are primarily focused on integrating new technologies.
REGIONAL COVERAGE:
North America
US
Canada
Mexico
Europe
Eastern Europe
Poland
Romania
Hungary
Turkey
Rest of Eastern Europe
Western Europe
Germany
France
UK
Italy
Spain
Netherlands
Switzerland
Austria
Rest of Western Europe
Asia Pacific
China
India
Japan
South Korea
Vietnam
Singapore
Australia
Rest of Asia Pacific
Middle East & Africa
Middle East
UAE
Egypt
Saudi Arabia
Qatar
Rest of the Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
Rest of Latin America
The major key players are NVIDIA Corporation, Intel Corporation, Xilinx Inc., Samsung Electronics Co., Ltd, Micron Technology, Inc., IBM Corporation, Amazon Web Services, Inc., Darktrace, Cylance Inc., Vectra AI, Inc.
In November 2021, NVIDIA unveiled a cutting-edge zero-trust cybersecurity platform designed to empower industry leaders in cybersecurity to bolster security measures and protect customer data centers in real-time.
In August 2022, reports surfaced that Thoma Bravo was considering acquiring Darktrace.
Microsoft announced the official launch of Microsoft Defender Experts for Hunting in August 2022, a proactive threat-hunting tool.
NVIDIA and Oracle have joined forces to empower customers in overcoming business challenges through accelerated computing and AI. This collaboration is focused on integrating the complete NVIDIA accelerated computing stack—comprising GPUs, systems, and software—into Oracle Cloud Infrastructure (OCI).
| Report Attributes | Details |
| Market Size in 2022 | US$ 21.89 Billion |
| Market Size by 2031 | US$ 111.27 Billion |
| CAGR | CAGR of 22.4% From 2024 to 2031 |
| Base Year | 2022 |
| Forecast Period | 2024-2031 |
| Historical Data | 2020-2023 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Component (Software, Service, And Hardware) • By Deployment (Cloud And On-Premise) • By Technology (Context-Aware Computing, Machine Learning, Natural Language Processing) • By Security Type (Network Security, Endpoint Security, Application Security, Cloud Security) • By Application (Identity And Access Management, Risk And Compliance Management, Data Loss Prevention, Unified Threat Management, Security And Vulnerability Management, Antivirus, Fraud Detection, Intrusion Detection, And Prevention System, Threat Intelligence, Others) • By Industry Vertical (Automotive & Transportation, Retail, BFSI, Manufacturing, Government & Defense, Enterprise, Oil & Gas, Education, Others) |
| Regional Analysis/Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia, Rest of Latin America) |
| Company Profiles | NVIDIA Corporation, Intel Corporation, Xilinx Inc., Samsung Electronics Co., Ltd, Micron Technology, Inc., IBM Corporation, Amazon Web Services, Inc., Darktrace, Cylance Inc., Vectra AI, Inc. |
| Key Drivers | • Growing IoT Adoption and the Number of Connected Devices • Increased Incidence of Cyber Threats |
| Market Opportunity | • SMEs are increasingly in need of cloud-based security solutions • Growing Use of Social-Media for Business Purposes |
Ans. The projected market size for the Artificial Intelligence (AI) In Cybersecurity Market is USD 111.27 billion by 2031.
Ans: Growing IoT Adoption and the Number of Connected Devices, Increased Incidence of Cyber Threats, Rising Data Security Concerns, and Increasing Wi-Fi Network Vulnerability to Security Threats are the growth factors of Artificial Intelligence (AI) in the Cybersecurity Market.
Ans: The leading players in the Artificial Intelligence (AI) in Cybersecurity Market include NVIDIA Corporation, Intel Corporation, Xilinx Inc., Samsung Electronics Co., Ltd, Micron Technology, Inc., IBM Corporation, Amazon Web Services, Inc., Darktrace, Cylance Inc., and Vectra AI, Inc.
Ans: North America region dominated the Artificial Intelligence (AI) in Cybersecurity Market.
Ans. The Compound Annual Growth rate for the Artificial Intelligence (AI) In Cybersecurity Market over the forecast period is 22.4 %.
TABLE OF CONTENTS
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Industry Flowchart
3. Research Methodology
4. Market Dynamics
4.1 Drivers
4.2 Restraints
4.3 Opportunities
4.4 Challenges
5. Impact Analysis
5.1 Impact of Russia-Ukraine Crisis
5.2 Impact of Economic Slowdown on Major Countries
5.2.1 Introduction
5.2.2 United States
5.2.3 Canada
5.2.4 Germany
5.2.5 France
5.2.6 UK
5.2.7 China
5.2.8 Japan
5.2.9 South Korea
5.2.10 India
6. Value Chain Analysis
7. Porter’s 5 Forces Model
8. Pest Analysis
9. Artificial Intelligence (AI) In Cybersecurity Market, By Component
9.1 Introduction
9.2 Trend Analysis
9.3 Software
9.4 Service
9.5 Hardware
10. Artificial Intelligence (AI) In Cybersecurity Market, By Deployment
10.1 Introduction
10.2 Trend Analysis
10.3 On-premises
10.4 Cloud
11. Artificial Intelligence (AI) In Cybersecurity Market, By Security Type
11.1 Introduction
11.2 Trend Analysis
11.3 Network Security
11.4 Endpoint Security
11.5 Application Security
11.6 Cloud Security
12. Artificial Intelligence (AI) In Cybersecurity Market, By technology
12.1 Introduction
12.2 Trend analysis
12.3 Context-Aware Computing
12.4 Machine Learning
12.5 Natural Language Processing
13. Artificial Intelligence (AI) In Cybersecurity Market, By Application
13.1 Introduction
13.2 Trend analysis
13.3 Identity and Access Management
13.4 Risk and Compliance Management
13.5 Data Loss Prevention
13.6 Unified Threat Management
13.7 Security and Vulnerability Management
13.8 Antivirus
13.9 Fraud Detection
13.10 Intrusion Detection and Prevention System
13.11 Threat Intelligence
13.12 Others
14. Artificial Intelligence (AI) In Cybersecurity Market, By Industry Vertical
14.1 Introduction
14.2 Trend analysis
14.3 Automotive & Transportation
14.4 Retail
14.5 BFSI
14.6 Manufacturing
14.7 Government & Défense
14.8 Enterprise
14.9 Oil & Gas
14.10 Education
14.11 Others
15. Regional Analysis
15.1 Introduction
15.2 North America
15.2.1 USA
15.2.2 Canada
15.2.3 Mexico
15.3 Europe
15.3.1 Eastern Europe
15.3.1.1 Poland
15.3.1.2 Romania
15.3.1.3 Hungary
15.3.1.4 Turkey
15.3.1.5 Rest of Eastern Europe
15.3.2 Western Europe
15.3.2.1 Germany
15.3.2.2 France
15.3.2.3 UK
15.3.2.4 Italy
15.3.2.5 Spain
15.3.2.6 Netherlands
15.3.2.7 Switzerland
15.3.2.8 Austria
15.3.2.10 Rest of Western Europe
15.4 Asia-Pacific
15.4.1 China
15.4.2 India
15.4.3 Japan
15.4.4 South Korea
15.4.5 Vietnam
15.4.6 Singapore
15.4.7 Australia
15.4.8 Rest of Asia Pacific
15.5 The Middle East & Africa
15.5.1 Middle East
15.5.1.1 UAE
15.5.1.2 Egypt
15.5.1.3 Saudi Arabia
15.5.1.4 Qatar
15.5.1.5 Rest of the Middle East
15.5.2 Africa
15.5.2.1 Nigeria
15.5.2.2 South Africa
15.5.2.3 Rest of Africa
15.6 Latin America
15.6.1 Brazil
15.6.2 Argentina
15.6.3 Colombia
15.6.4 Rest of Latin America
16. Company Profiles
16.1 NVIDIA Corporation.
16.1.1 Company Overview
16.1.2 Financials
16.1.3 Products/ Services Offered
16.1.4 SWOT Analysis
16.1.5 The SNS View
16.2 Intel Corporation.
16.2.1 Company Overview
16.2.2 Financials
16.2.3 Products/ Services Offered
16.2.4 SWOT Analysis
16.2.5 The SNS View
16.3 Xilinx Inc.
16.3.1 Company Overview
16.3.2 Financials
16.3.3 Products/ Services Offered
16.3.4 SWOT Analysis
16.3.5 The SNS View
16.4 Samsung Electronics Co., Ltd.
16.4 Company Overview
16.4.2 Financials
16.4.3 Products/ Services Offered
16.4.4 SWOT Analysis
16.4.5 The SNS View
16.5 Micron Technology, Inc.
16.5.1 Company Overview
16.5.2 Financials
16.5.3 Products/ Services Offered
16.5.4 SWOT Analysis
16.5.5 The SNS View
16.6 IBM Corporation.
16.6.1 Company Overview
16.6.2 Financials
16.6.3 Products/ Services Offered
16.6.4 SWOT Analysis
16.6.5 The SNS View
16.7 Amazon Web Services, Inc.
16.7.1 Company Overview
16.7.2 Financials
16.7.3 Products/ Services Offered
16.7.4 SWOT Analysis
16.7.5 The SNS View
16.8 Darktrace.
16.8.1 Company Overview
16.8.2 Financials
16.8.3 Products/ Services Offered
16.8.4 SWOT Analysis
16.8.5 The SNS View
16.9 Cylance Inc.
16.9.1 Company Overview
16.9.2 Financials
16.9.3 Products/ Services Offered
16.9.4 SWOT Analysis
16.9.5 The SNS View
16.10 Vectra AI, Inc.
16.10.1 Company Overview
16.10.2 Financials
16.10.3 Products/ Services Offered
16.10.4 SWOT Analysis
16.10.5 The SNS View
17. Competitive Landscape
17.1 Competitive Benchmarking
17.2 Market Share Analysis
17.3 Recent Developments
17.3.1 Industry News
17.3.2 Company News
17.3.3 Mergers & Acquisitions
18. USE Cases and Best Practices
19. Conclusion
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