Artificial Intelligence In Cybersecurity Market
Artificial Intelligence in Cybersecurity Market Forecasts to 2030 - Global Analysis By Component (Hardware, Software and Services), Security Type, Deployment Type, Technology, Application, End User and By Geography
|
Years Covered |
2021-2030 |
|
Estimated Year Value (2023) |
US $22.4 BN |
|
Projected Year Value (2030) |
US $100.4 BN |
|
CAGR (2023 - 2030) |
23.9% |
|
Regions Covered |
North America, Europe, Asia Pacific, South America, and Middle East & Africa |
|
Countries Covered |
US, Canada, Mexico, Germany, UK, Italy, France, Spain, Japan, China, India, Australia, New Zealand, South Korea, Rest of Asia Pacific, South America, Argentina, Brazil, Chile, Middle East & Africa, Saudi Arabia, UAE, Qatar, and South Africa |
|
Largest Market |
North America |
|
Highest Growing Market |
Asia Pacific |
According to Stratistics MRC, the Global Artificial Intelligence in Cybersecurity Market is accounted for $22.4 billion in 2023 and is expected to reach $100.4 billion by 2030 growing at a CAGR of 23.9% during the forecast period. Artificial intelligence (AI) has a big impact on cybersecurity, by making it easier to identify, stop, and respond to cyber threats. Massive amounts of data can be analysed in real-time by AI systems, which can then spot odd patterns or behaviors that can point to a cyberattack. Malware, viruses, and other dangerous software are among the things that can be found. Algorithms for machine learning can be taught to detect known risks and adjust to new ones. Anomaly detection systems powered by AI provide a baseline of typical network behavior and issue alarms when this baseline is violated. This can be used to find previously undiscovered attack methods or insider risks.
According to the Consumer Technology Association, 44% of organizations across the globe are implementing AI applications to detect and deter security intrusions.
Market Dynamics:
Driver:
Increase in demand for better security measures
As cyberattacks are becoming more sophisticated and frequent, organizations are rapidly feeling the need for improved and modern security solutions. Nowadays, a number of stakeholders are very concerned about cyber dangers. As a result, implementing safeguards to reduce the identified hazards is urgently needed for an organization's systems, networks, and data. Due to the increasing frequency of cyberattacks and data breaches, there is a growing need for security solutions. Additionally, the need of proactive cyber security measures, such as better cyber security and threat modelling solutions, is increasingly being recognized by enterprises, which is fuelling market expansion.
Restraint:
False alarms with defamatory attacks
Security systems powered by AI run the risk of producing false alarms or failing to identify genuine threats. These errors may result in the loss of time and resources or the failure to identify vulnerabilities. AI can be used by hackers to create attacks that are intended to especially harm AI-based security systems. These assaults, often referred to as adversarial attacks, might fudge the input data to lead AI algorithms to draw the wrong conclusions thus hampering the growth of the market.
Opportunity:
Requirements for regulatory compliance and industry standards
Threat modeling is frequently required of organizations as part of security programs by regulatory compliance standards and industry standards like the General Data Protection Regulation (GDPR), Payment Card Industry Data Security Standard (PCI-DSS), and National Institute of Standards and Technology (NIST). Government agencies now have an even greater need for improved security solutions, which in turn is fueling the market for AI in cybersecurity. The growing technical investment of both public and private companies is also encouraging the use of AI in the cybersecurity market.
Threat:
AI's inability to combat modern and complex dangers
AI techniques and methods, such as deep learning, neural networks, genetic algorithms, and machine learning, are founded on prior experiences. An advanced persistent threat (APT) is a network attack where a user gains access to a network without authorization and remains hidden for a considerable amount of time. While some APT behaviors may be similar to past events that AIs can detect them, new APTs have no prior experiences and are therefore equipped with novel ways to invoke application programming interfaces (APIs) and cutting-edge approaches to access system resources. Real defence against complex, modern dangers cannot rely on previous viruses or assaults. This market is being constrained by AI's incapacity to counter advanced threats.
Covid-19 Impact
A lot of top cybersecurity organizations see the current crisis as a chance to review and restructure their current strategies and develop more complex product portfolios. The COVID-19 outbreak has boosted the demand for cutting-edge solutions as firms commit more to work-from-home policies. Due to a rise in demand for digital goods and services brought on by telecommuting workers and other users of potentially risky networks and devices, businesses have been pushed to invest money in machine learning and deep learning algorithms.
The machine learning segment is expected to be the largest during the forecast period
The machine learning segment is estimated to have a lucrative growth, as these deep learning spreads quickly throughout end-use industries, machine-learning technologies will grow dramatically. Leading corporations like Google and IBM are beginning to use machine learning for threat detection and email filtering. Businesses are making use of machine learning and deep learning to enhance cybersecurity protocols. Additionally, ML platforms are becoming more and more well-liked as a tool to automate monitoring, identify anomalies, and navigate the vast amounts of data generated by security systems.
The fraud detection/anti-fraud segment is expected to have the highest CAGR during the forecast period
The fraud detection/anti-fraud segment is anticipated to witness the highest CAGR growth during the forecast period, as the use of artificial intelligence (AI) in cybersecurity will be pushed as preventative measures for fraud detection and anti-fraud. As a result of an increase in fraud incidences, machine learning has become a beneficial technique for enhancing the capacity of governments and other end users to prevent fraudulent actions. AI tools may therefore be used more frequently to get rid of fraud, email phishing, and fraudulent records. To safeguard their digital assets from threats including spyware-infected files, phishing assaults, unauthorized website access, and trojans (UTM), businesses are more interested in unified threat management thereby encouraging the market.
Region with largest share:
North America is projected to hold the largest market share during the forecast period owing to the increase in network-connected devices brought on by the adoption of IoT, 5G, and Wi-Fi 6 is primarily responsible for the rise. The expansion of the 5G network has been driven by businesses in the automotive, healthcare, government, energy, and mining industries, which might be a point of access for hackers. Leading companies are likely to invest money in platforms for machine learning, sophisticated analytics, asset mapping, and visualization for a real-time evaluation. Natural language processing, machine learning (ML), and neural networks are expected to be widely used in North America to thwart assaults, detect odd user behaviour, and identify other anomalous patterns thus enhancing the growth of the market in this region.
Region with highest CAGR:
Asia Pacific is projected to have the highest CAGR over the forecast period as this region has been a hotspot for cyberattacks because of its economic expansion and rising level of digitalisation. To protect against emerging threats, there is now a larger demand for advanced cybersecurity solutions, particularly those that are AI-powered. Numerous governments in the APAC area have started initiatives to encourage the creation and use of AI in cybersecurity because they understand how important it is. These projects frequently include financing for R&D as well as regulatory assistance which drive the market.
Key players in the market
Some of the key players profiled in the Artificial Intelligence in Cybersecurity Market include Micron Technology, Inc., Amazon Web Services, Inc., Cylance Inc. (BlackBerry), FireEye, Inc., Fortinet, Inc., Acalvio Technologies, Inc, Intel Corporation, IBM Corporation, LexisNexis, Darktrace, Microsoft Corporation, Samsung Electronics Co. Ltd., Cisco Systems, Inc., Gen Digital Inc., NVIDIA Corporation, McAfee LLC, Palo Alto Networks Inc. and Cylance Inc.
Key Developments:
In September 2023, Cylance Inc. (BlackBerry) Launches ‘Intrinsically Safe’ Certified Solution for Hazardous Materials Carriers the new series is backed by an ‘Intrinsically Safe’ certification designation, enabling BlackBerry Radar, an asset tracking solution, to target transportation and logistics companies that move hazardous materials, including fuel haulers, tank carriers, ocean shipping lines and railroads.
In September 2023, Intel presents a software-defined, silicon-accelerated approach built on a foundation of openness, choice, trust and security. which allows the hardware to process the data without it ever being decrypted. In essence, the processor performs calculations directly on the encrypted data.
In August 2023, Micron Launches Memory Expansion Module Portfolio to Accelerate CXL 2.0 Adoption. Additionally, the CZ120 modules are capable of running up to 36GB/s memory read/write bandwidth1 and augment standard server systems when incremental memory capacity and bandwidth is required.
Components Covered:
• Hardware
• Software
• Services
Security Types Covered:
• Application Security
• Endpoint Security
• Network Security
• Cloud Security
Deployment Types Covered:
• On-Premises
• Cloud
Technologies Covered:
• Context-Aware Computing
• Machine Learning
• Natural Language Processing (NLP)
• Other Technologies
Applications Covered:
• Antivirus/ Malware
• Data Loss Prevention
• Fraud Detection/Anti-Fraud
• Identity And Access Management
• Intrusion Detection/ Prevention System
• Risk And Compliance Management
• Security & Vulnerability Management
• Threat Intelligence
• Unified Threat Management
• Other Applications
End Users Covered:
• BFSI
• Automotive & Transportation
• Enterprise
• Government & Defense
• Healthcare
• Infrastructure
• Manufacturing
• Retail
• Other End Users
Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances
Table of Contents
1 Executive Summary
2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions
3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 Technology Analysis
3.7 Application Analysis
3.8 End User Analysis
3.9 Emerging Markets
3.10 Impact of Covid-19
4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry
5 Global Artificial Intelligence in Cybersecurity Market, By Component
5.1 Introduction
5.2 Hardware
5.2.1 Processors
5.2.1.1 Application-Specific Integrated Circuit (ASIC)
5.2.1.2 Field Programmable Gate Array (FPGA)
5.2.1.3 Graphics Processing Unit (GPU)
5.2.1.4 Memory Protection Unit (MPU)
5.2.2 Memory
5.2.3 Network
5.3 Software
5.3.1 AI Solutions
5.3.2 AI Platform
5.3.2.1 Application Program Interface (API)
5.3.2.2 Machine Learning Framework
5.4 Services
5.4.1 Support & Maintenance
5.4.2 Deployment & Integration
6 Global Artificial Intelligence in Cybersecurity Market, By Security Type
6.1 Introduction
6.2 Application Security
6.3 Endpoint Security
6.4 Network Security
6.5 Cloud Security
7 Global Artificial Intelligence in Cybersecurity Market, By Deployment Type
7.1 Introduction
7.2 On-Premises
7.3 Cloud
8 Global Artificial Intelligence in Cybersecurity Market, By Technology
8.1 Introduction
8.2 Context-Aware Computing
8.3 Machine Learning
8.3.1 Deep Learning
8.3.2 Reinforcement Learning
8.3.3 Supervised Learning
8.3.4 Unsupervised Learning
8.4 Natural Language Processing (NLP)
8.5 Other Technologies
9 Global Artificial Intelligence in Cybersecurity Market, By Application
9.1 Introduction
9.2 Antivirus/ Malware
9.3 Data Loss Prevention
9.4 Fraud Detection/Anti-Fraud
9.5 Identity And Access Management
9.6 Intrusion Detection/ Prevention System
9.7 Risk And Compliance Management
9.8 Security & Vulnerability Management
9.9 Threat Intelligence
9.10 Unified Threat Management
9.11 Other Applications
10 Global Artificial Intelligence in Cybersecurity Market, By End User
10.1 Introduction
10.2 Banking, Financial Services and Insurance (BFSI)
10.3 Automotive & Transportation
10.4 Enterprise
10.5 Government & Defense
10.6 Healthcare
10.7 Infrastructure
10.8 Manufacturing
10.9 Retail
10.10 Other End Users
11 Global Artificial Intelligence in Cybersecurity Market, By Geography
11.1 Introduction
11.2 North America
11.2.1 US
11.2.2 Canada
11.2.3 Mexico
11.3 Europe
11.3.1 Germany
11.3.2 UK
11.3.3 Italy
11.3.4 France
11.3.5 Spain
11.3.6 Rest of Europe
11.4 Asia Pacific
11.4.1 Japan
11.4.2 China
11.4.3 India
11.4.4 Australia
11.4.5 New Zealand
11.4.6 South Korea
11.4.7 Rest of Asia Pacific
11.5 South America
11.5.1 Argentina
11.5.2 Brazil
11.5.3 Chile
11.5.4 Rest of South America
11.6 Middle East & Africa
11.6.1 Saudi Arabia
11.6.2 UAE
11.6.3 Qatar
11.6.4 South Africa
11.6.5 Rest of Middle East & Africa
12 Key Developments
12.1 Agreements, Partnerships, Collaborations and Joint Ventures
12.2 Acquisitions & Mergers
12.3 New Product Launch
12.4 Expansions
12.5 Other Key Strategies
13 Company Profiling
13.1 Micron Technology, Inc.
13.2 Amazon Web Services, Inc.
13.3 Cylance Inc. (BlackBerry)
13.4 FireEye, Inc.
13.5 Fortinet, Inc.
13.6 Acalvio Technologies, Inc
13.7 Intel Corporation
13.8 IBM Corporation
13.9 LexisNexis
13.10 Darktrace
13.11 Microsoft Corporation
13.12 Samsung Electronics Co. Ltd.
13.13 Cisco Systems, Inc.
13.14 Gen Digital Inc.
13.15 NVIDIA Corporation
13.16 McAfee LLC
13.17 Palo Alto Networks Inc.
13.18 Cylance Inc.
List of Tables
1 Global Artificial Intelligence in Cybersecurity Market Outlook, By Region (2021-2030) ($MN)
2 Global Artificial Intelligence in Cybersecurity Market Outlook, By Component (2021-2030) ($MN)
3 Global Artificial Intelligence in Cybersecurity Market Outlook, By Hardware (2021-2030) ($MN)
4 Global Artificial Intelligence in Cybersecurity Market Outlook, By Processors (2021-2030) ($MN)
5 Global Artificial Intelligence in Cybersecurity Market Outlook, By Application-Specific Integrated Circuit (ASIC) (2021-2030) ($MN)
6 Global Artificial Intelligence in Cybersecurity Market Outlook, By Field Programmable Gate Array (FPGA) (2021-2030) ($MN)
7 Global Artificial Intelligence in Cybersecurity Market Outlook, By Graphics Processing Unit (GPU) (2021-2030) ($MN)
8 Global Artificial Intelligence in Cybersecurity Market Outlook, By Memory Protection Unit (MPU) (2021-2030) ($MN)
9 Global Artificial Intelligence in Cybersecurity Market Outlook, By Memory (2021-2030) ($MN)
10 Global Artificial Intelligence in Cybersecurity Market Outlook, By Network (2021-2030) ($MN)
11 Global Artificial Intelligence in Cybersecurity Market Outlook, By Software (2021-2030) ($MN)
12 Global Artificial Intelligence in Cybersecurity Market Outlook, By AI Solutions (2021-2030) ($MN)
13 Global Artificial Intelligence in Cybersecurity Market Outlook, By AI Platform (2021-2030) ($MN)
14 Global Artificial Intelligence in Cybersecurity Market Outlook, By Application Program Interface (API) (2021-2030) ($MN)
15 Global Artificial Intelligence in Cybersecurity Market Outlook, By Machine Learning Framework (2021-2030) ($MN)
16 Global Artificial Intelligence in Cybersecurity Market Outlook, By Services (2021-2030) ($MN)
17 Global Artificial Intelligence in Cybersecurity Market Outlook, By Support & Maintenance (2021-2030) ($MN)
18 Global Artificial Intelligence in Cybersecurity Market Outlook, By Deployment & Integration (2021-2030) ($MN)
19 Global Artificial Intelligence in Cybersecurity Market Outlook, By Security Type (2021-2030) ($MN)
20 Global Artificial Intelligence in Cybersecurity Market Outlook, By Application Security (2021-2030) ($MN)
21 Global Artificial Intelligence in Cybersecurity Market Outlook, By Endpoint Security (2021-2030) ($MN)
22 Global Artificial Intelligence in Cybersecurity Market Outlook, By Network Security (2021-2030) ($MN)
23 Global Artificial Intelligence in Cybersecurity Market Outlook, By Cloud Security (2021-2030) ($MN)
24 Global Artificial Intelligence in Cybersecurity Market Outlook, By Deployment Type (2021-2030) ($MN)
25 Global Artificial Intelligence in Cybersecurity Market Outlook, By On-Premises (2021-2030) ($MN)
26 Global Artificial Intelligence in Cybersecurity Market Outlook, By Cloud (2021-2030) ($MN)
27 Global Artificial Intelligence in Cybersecurity Market Outlook, By Technology (2021-2030) ($MN)
28 Global Artificial Intelligence in Cybersecurity Market Outlook, By Context-Aware Computing (2021-2030) ($MN)
29 Global Artificial Intelligence in Cybersecurity Market Outlook, By Machine Learning (2021-2030) ($MN)
30 Global Artificial Intelligence in Cybersecurity Market Outlook, By Deep Learning (2021-2030) ($MN)
31 Global Artificial Intelligence in Cybersecurity Market Outlook, By Reinforcement Learning (2021-2030) ($MN)
32 Global Artificial Intelligence in Cybersecurity Market Outlook, By Supervised Learning (2021-2030) ($MN)
33 Global Artificial Intelligence in Cybersecurity Market Outlook, By Unsupervised Learning (2021-2030) ($MN)
34 Global Artificial Intelligence in Cybersecurity Market Outlook, By Natural Language Processing (NLP) (2021-2030) ($MN)
35 Global Artificial Intelligence in Cybersecurity Market Outlook, By Other Technologies (2021-2030) ($MN)
36 Global Artificial Intelligence in Cybersecurity Market Outlook, By Application (2021-2030) ($MN)
37 Global Artificial Intelligence in Cybersecurity Market Outlook, By Antivirus/ Malware (2021-2030) ($MN)
38 Global Artificial Intelligence in Cybersecurity Market Outlook, By Data Loss Prevention (2021-2030) ($MN)
39 Global Artificial Intelligence in Cybersecurity Market Outlook, By Fraud Detection/Anti-Fraud (2021-2030) ($MN)
40 Global Artificial Intelligence in Cybersecurity Market Outlook, By Identity And Access Management (2021-2030) ($MN)
41 Global Artificial Intelligence in Cybersecurity Market Outlook, By Intrusion Detection/ Prevention System (2021-2030) ($MN)
42 Global Artificial Intelligence in Cybersecurity Market Outlook, By Risk And Compliance Management (2021-2030) ($MN)
43 Global Artificial Intelligence in Cybersecurity Market Outlook, By Security & Vulnerability Management (2021-2030) ($MN)
44 Global Artificial Intelligence in Cybersecurity Market Outlook, By Threat Intelligence (2021-2030) ($MN)
45 Global Artificial Intelligence in Cybersecurity Market Outlook, By Unified Threat Management (2021-2030) ($MN)
46 Global Artificial Intelligence in Cybersecurity Market Outlook, By Other Applications (2021-2030) ($MN)
47 Global Artificial Intelligence in Cybersecurity Market Outlook, By End User (2021-2030) ($MN)
48 Global Artificial Intelligence in Cybersecurity Market Outlook, By Banking, Financial Services and Insurance (BFSI) (2021-2030) ($MN)
49 Global Artificial Intelligence in Cybersecurity Market Outlook, By Automotive & Transportation (2021-2030) ($MN)
50 Global Artificial Intelligence in Cybersecurity Market Outlook, By Enterprise (2021-2030) ($MN)
51 Global Artificial Intelligence in Cybersecurity Market Outlook, By Government & Defense (2021-2030) ($MN)
52 Global Artificial Intelligence in Cybersecurity Market Outlook, By Healthcare (2021-2030) ($MN)
53 Global Artificial Intelligence in Cybersecurity Market Outlook, By Infrastructure (2021-2030) ($MN)
54 Global Artificial Intelligence in Cybersecurity Market Outlook, By Manufacturing (2021-2030) ($MN)
55 Global Artificial Intelligence in Cybersecurity Market Outlook, By Retail (2021-2030) ($MN)
56 Global Artificial Intelligence in Cybersecurity Market Outlook, By Other End Users (2021-2030) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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