The updated ‘Artificial Intelligence in Cybersecurity Market Report 2030’ is now available with Market Industry Reports (MIR). Researchers have provided detailed analysis on ongoing trends and developments in the product, product preference by large end-users, and strategies adopted by the key players for the competitors to identify opportunities and expand considerably.
New York, NY -- (SBWIRE) -- 01/24/2020 -- Latest research report on 'Artificial Intelligence in Cybersecurity Market' delivers essential information on current consumer buying behavior, product specifications, details to help execute growth strategies, and more. The report is now available with Market Industry Reports (MIR) titled as "Artificial Intelligence in Cybersecurity Market - Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2019–2030."
According to the report, the global artificial intelligence in cybersecurity market is estimated to account for over US$ 8.5 billion in 2019. It is anticipated to grow at a CAGR of ~22.3% from 2019 to 2030.
The growth of the AI in cybersecurity market can be attributed to several factors which have led to the wide-scale adoption of these services by large enterprise and SMEs. The rising number of cyber-attacks due to the growing trend of digitalization coupled with increasing adoption of cloud-based services is further anticipated to fuel the demand for AI in cybersecurity.
Some Of The Prominent Market Players Include:
Intel Corporation, NVIDIA Corporation, IBM, SAMSUNG, Xilinx, Micron Technology, Inc., Cylance (BlackBerry Limited.), F-Secure, LexisNexis Risk Solutions, and Sift, among others.
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The globally IoT adoption is not merely limited to offices and finds applications across various other types of infrastructures. IoT devices are used extensively by the healthcare, finance, and infrastructure sectors. The increasing number of connected devices and the growing need for the IoT have significantly contributed to the growing demand for cybersecurity worldwide. For instance, F-Secure, a Finnish cybersecurity company, uses "honeypots" network to get information about attacks. The company estimated more than 2.9 billion events of cyber-attacks globally.
The global Artificial Intelligence in Cybersecurity market is segmented by offering, technology, security type, deployment type, application, end user, and region.
Artificial Intelligence in Cybersecurity by Offering
Based on offering, the AI in cybersecurity market can be segmented into hardware, software and, services. The software segment is estimated to account for the largest share in the AI in cybersecurity market globally. This large share of the segment can be attributed to the development of several AI-based software and tools for a broad range of applications.
Artificial Intelligence in Cybersecurity by Technology
Based on technology, the market can be segmented into machine learning, natural language processing, and others. The machine learning segment is estimated to account for the largest market share owing to high computational capabilities and widespread applications across diverse sectors.
Artificial Intelligence in Cybersecurity by Security Type
Based on type, the market can be segmented into cloud security, network security, application security, and others. The application security segment is estimated to grow at a robust CAGR during the forecast period as many large organizations have started using several cybersecurity applications.
Artificial Intelligence in Cybersecurity by Deployment Type
Based on deployment type, the market has been segmented into cloud and on-premise. The market for cloud deployment is expected to grow at a high CAGR due to the increased adoption of cloud-based deployment by companies worldwide.
Artificial Intelligence in Cybersecurity by Application
Similarly, in terms of application the market can be segmented into risk & compliance management, data loss prevention, antivirus/antimalware, identity & access management, and security & vulnerability management. The identity & access management segment is estimated to account for the largest market share as it integrates functionalities that are frequently used by individuals as well as companies including authentication, authorization, user management, and central user repository techniques.
Artificial Intelligence in Cybersecurity by End User
Based on end-user, the market is segmented into Banking, Financial Services, & Insurance (BFSI), IT & telecommunication, healthcare, retail, government & defense, automotive & transportation, and others. The BFSI segment is estimated to grow at a robust CAGR during the forecast period as data breach incidences are more common in this sector.
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Research Report Objectives Analysis:
-To estimate and analyze the global size of the Artificial Intelligence in Cybersecurity Market
-To provide a clear picture of segments in the global Artificial Intelligence in Cybersecurity Market and
assess the market size of the segments
-To assist readers understand current and future industry scenarios
-To provide essential information about latest trends in the global Artificial Intelligence in Cybersecurity
Market and its major segments
-To provide details on key drivers, restraints, and opportunities of the global Artificial Intelligence in
Cybersecurity Market
-To accurately calculate the market shares of major segments, regions, and companies in the global Artificial
Intelligence in Cybersecurity Market
-To provide details regarding crucial strategies adopted by leading players of the global Artificial
Intelligence in Cybersecurity Market
-To examine the contribution of each region or country to the global Artificial Intelligence in Cybersecurity
Market
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Some points from Table of Contents:
1.INTRODUCTION
1.1 Market Definition
1.2 Market Classification
1.3 Geographic Scope
1.4 Years Considered for the Study: Historical Years – 2016 & 2017; Base Year – 2018; Forecast Years – 2019 to
2030
1.5 Currency Used
2.RESEARCH METHODOLOGY
2.1 Research Framework
2.2 Data Collection Technique
2.3.Data Sources
2.3.1.Secondary Sources
2.3.2.Primary Sources
2.4 Market Estimation Methodology
2.4.1 Bottom Up Approach
2.4.2 Top Down Approach
2.5 Data Validation and Triangulation
2.5.1 Market Forecast Model
2.5.2 Limitations/Assumptions of the Study
3.ABSTRACT OF THE STUDY
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