Artificial Intelligence in Cybersecurity Market

Artificial Intelligence in Cybersecurity Market by Offering (Hardware, Software, and Service), Deployment Type, Security Type, Technology (ML, NLP, and Context-Aware), Application (IAM, DLP, and UTM), End User and Geography - Global Forecast to 2028

Report Code: SE 5851 Dec, 2022, by marketsandmarkets.com

Updated on : September 10 , 2023

The artificial intelligence in cybersecurity market size is valued at USD 22.4 Billion in 2023 and is anticipated to be USD 60.6 Billion by 2028; growing at a CAGR of 21.9%.

Factors such as the growing adoption of IoT and increasing number of connected devices, increasing instances of cyber threat, rising concerns of data protection, and increasing vulnerability of Wi-Fi networks to security threats are driving the growth of the AI in cybersecurity industry during the forecast period.

Artificial Intelligence in Security Market

Artificial Intelligence in Cybersecurity Market Forecast to 2028

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Artificial intelligence in cybersecurity Market Dynamics

Driver: Increasing instances of cyber threats

The instances of cyberattacks are gradually increasing globally. Cybercriminals attack endpoints, networks, data, and other IT infrastructure that lead to a huge financial loss for individuals, enterprises, and governments. The primary motive of cybercriminals includes political rivalry, financial gain, harm reputation, international rivalry, and radical religious group interest. The majority of cyberattacks are for financial gains. WannaCry, Petya, NotPetya, and BadRabbit are among the significant ransomware that have affected enterprises and government organizations on a large scale.

According to the CISCO cybersecurity threat trends report 2021, 86% of the organizations of organizations had at least one user try to connect to a phishing site, 70% of organizations had users that were served malicious browser ads, 69% of organizations experienced some level of unsolicited crypto mining, and 50% of organizations encountered ransomware-related activity.

Cyber threats are not only hampering the productivity of businesses but also damaging the critical IT infrastructure and sensitive data of organizations. Owing to the rapid rise in the digital transaction globally across various industries, there is an increase in the frequency of cybercrimes. The increase in enterprise data breaches or data leakage is fueling the market for cybersecurity products and services. Therefore, safeguarding against cyber threats has become essential for enterprises’ business growth. Nowadays, cyber attackers are using sophisticated techniques to launch ransomware attacks and aim to raise money through small ransoms comprising a few hundred dollars each. With the advancements of technologies, automated and sophisticated cyberattacks are accelerating. The increasing sophistication of attacks is triggering organizations across the world to adopt cybersecurity solutions and services to combat with swarm cyberattacks. According to Microsoft US was the target of 46% of cyberattacks in 2020, more than double any other country.

Restraint: Inability of AI to stop zero-day and advanced threats

All algorithms or approaches used in AI, including machine learning, genetics algorithm, deep learning, or neural networks, are based on experiences from the past. This means that AI in cybersecurity is based on learning from past malware about what malware looks like and how it behaves. A zero-day threat exploits an unknown computer security vulnerability. An advanced persistent threat (APT) is a network attack in which an unauthorized person gains access to a network and stays undetected for a long period of time. APTs are armed with new methods to invoke application programming interfaces (APIs) and innovative techniques to access system resources, while a few APT behaviors might be similar to past events that AIs can recognize them, new APTs have no past events. Real protection against sophisticated, advanced threats must not rely on prior malware or prior attacks. The inability of AI to stop advanced threats is thus acting as a restraint in this market.

Opportunity: Zero trust framework providing advanced security

Zero trust is a framework that considers that the security of complex networks is constantly under threat from both internal and external threats. A zero-trust security model validates and authorizes each connection made by a user to an application or software that connects to a data set via an application programming interface (API). It helps organize and strategize a thorough approach to counter cyber threats. According to the zero-trust principle, no one or any application should ever be presumed to be trustworthy. According to the principle of least-privileged access, which is a cornerstone of zero trust, trust should be established in accordance with the context (such as user identification and location, endpoint security posture, and the app or service being requested), with policy checks at each level. It utilizes deep learning which reveals document meaning and context to provide accurate, granular categories that reflect business criticality. Once categorized, deep learning can establish a security baseline for each category. That baseline encompasses how files are permissioned, shared, stored, and managed, and it reflects the policy decisions made by the people who know those files best – the owners and end-users

Challenge: Shortcomings of AI

AI is sometimes just useful for detecting threats; it does not always remove threats. However, issues can occur even when AI is used to detect threats as AI and ML are often positioned to perform anomaly detection, which highlights unknowns while also highlighting additional unknowns that are unrelated to security. To avoid this, security teams must constantly train the existing model using training data that includes a strong feedback loop. However, it requires additional effort and cost in addition to looking into the finding itself. The idea that artificial intelligence and machine learning can take the place of human judgment is a misconception. Human decision-making is unmatched. For instance, creating detection criteria based on attack paths, new vulnerabilities, and emerging threat intelligence involves context, research, and creativity. Being aware of impending attacks via research, replicating them, determining where detectability can occur across the stack, and building detections and playbooks are all distinctly human tasks that AI can assist with but cannot fully perform on its own.

Software to hold the largest market share of artificial intelligence in cybersecurity market during the forecast period

Software holds a major share of the overall AI in cybersecurity market owing to developments in AI software and related software development kits. AI systems require different types of software, including application program interfaces, such as language, speech, vision, and sensor data, along with machine learning algorithms, to realize the applications for cybersecurity. The software platforms and solutions are available at higher costs as there are only a limited number of experts that develop machine learning algorithms. Companies such as Darktrace (UK), Cylance (US), Securonix (US), and IBM (US) are among the frontrunners in the development of software for the AI in cybersecurity market.

Cloud-based deployment held the largest share of the market during the forecast period

Cloud deployment is gaining popularity among SMEs as it is cost-effective. Organizations can avoid costs related to hardware, software, storage, and technical staff by using cloud-based cybersecurity solutions. Cloud-based platforms offer a unified way in the form of SaaS-based security services to secure business applications. These platforms are beneficial for organizations that have strict budgets for security investments. SMEs deploy their solutions on the cloud as it enables them to focus on their core competencies, rather than investing their capital on security infrastructure. The cloud-based deployment is growing as cloud-cybersecurity solutions are easy to maintain and upgrade. IBM (US), Cylance (US), Microsoft (US), Amazon (US), and Darktrace (UK) are among the major providers of cloud-based deployment services.

Application security expected to grow at the second fastest rate

Application security solutions enable enterprises to secure their business-sensitive applications through greater visibility and control. The use of existing security solutions, such as IAM, web filtering, and application whitelisting, enables the security of enterprise applications and software codes from external and internal threats, such as web attacks, DDoS, site scraping, and fraud. Business-sensitive applications are among the primary targets of attackers as they carry information about critical assets, as well as processes that are followed by an enterprise. Several organizations rely on network security and neglect applications, which create a security gap and make them susceptible to attacks. The cybersecurity solutions and services prevent user applications from being attacked. These solutions and services collect the security and the event information from all web applications, after which they analyze the data for vulnerable or malicious events and study the event behavior to protect user applications.  This security type includes mobile application security and web application security. The mobile application security ensures the confidentiality of the data that is transferred among mobile applications, along with transparency and visibility among the business processes. Increasing number of mobile devices is expected to drive the market for application security.

North America to hold the largest share of the artificial intelligence in cybersecurity market during the forecast period

North America being a technologically advanced region, tops the world in terms of the presence of security vendors and cyber incidents. North America is the early adopter of cybersecurity solutions and services across the world. Increasing instances of cyberattacks are identified as the most crucial economic and national security challenge by governments in the region.  Businesses in this region top the world in terms of adoption of advanced technologies and infrastructures, such as cloud computing, big data analytics, and IoT. The attacks are increasing dramatically and becoming more sophisticated in nature, and targeting business applications in various industries. Sophisticated cyberattacks include DDoS, ransomware, bot attacks, malware, zero-day attacks, and spear phishing attacks.  Growing trends, such as IoT, Internet of Everything (IoE), Industrial Internet of Things (IIoT), and BYOD, have brought tremendous growth in the region, but have also triggered the rise in cyberattacks and added more complexities and concerns for enterprises. The rise in threats and vulnerabilities, and government compliances have made North America the most lucrative market for different categories of vendors.

Artificial Intelligence in Security Market Size, and Share

Artificial Intelligence in Security Market by Region

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Key Market Players:

The AI in cybersecurity Companies is dominated by a few globally established players such as NVIDIA Corporation (US), Intel Corporation (US), Xilinx Inc. (US), Samsung Electronics Co., Ltd (South Korea), Micron Technology, Inc. (US), IBM Corporation (US), Amazon Web Services, Inc. (US), Microsoft (US), Palo Alto Networks Inc. (US), Trellix (US), CrowdStrike (US), NortonLifeLock (US), Cylance Inc. (US), ThreatMetrix Inc. (US), Securonix Inc. (US), Sift Science (US), Acalvio Technologies (US), Darktrace (UK), SparkCognition Inc. (US), Fortinet (US), Check Point Software Technologies, Ltd (US), High-Tech Bridge (Switzerland), Deep Instinct (US), SentinelOne (US), Feedzai (US), Vectra Networks (US) Zimperium (US), Argus Cyber Security (Israel), Nozomi Networks (US), BitSight Technologies (US), and Antivirus companies such as Kaspersky Lab (Russia), Bitdefender (Romania), and ESET (US).

AI in cybersecurity Market Report Scope :

Report Metric

Details

Market size value in 2023  USD 24.4 Billion
Market size value in 2028  USD 60.6 Billion
CAGR (2023-2028)  21.9%

Years Considered

2023–2028

On Demand Data Available

2030

Forecast Period

2023–2028

Forecast Units

Value (USD Million/USD Billion)

Segments Covered

Offering, Deployment Type, Security Type, Technology, Application, End User and Geography

Geographies Covered

North America, Europe, Asia Pacific, and RoW

 

Companies Covered

  • NVIDIA Corporation (US),
  • Intel Corporation (US),
  • Xilinx Inc. (US),
  • Samsung Electronics Co., Ltd (South Korea),
  • Micron Technology, Inc. (US),
  • IBM Corporation (US),
  • Amazon Web Services, Inc. (US),
  • Microsoft (US),

    Palo Alto Networks Inc. (US), Trellix (US), CrowdStrike (US), NortonLifeLock (US), Cylance Inc. (US), ThreatMetrix Inc. (US), Securonix Inc. (US), Sift Science (US), Acalvio Technologies (US), Darktrace (UK), SparkCognition Inc. (US), Fortinet (US), Check Point Software Technologies, Ltd (US), High-Tech Bridge (Switzerland), Deep Instinct (US), SentinelOne (US), Feedzai (US), Vectra Networks (US) Zimperium (US), Argus Cyber Security (Israel), Nozomi Networks (US), BitSight Technologies (US), and Antivirus companies such as Kaspersky Lab (Russia), Bitdefender (Romania), and ESET (US).

Other players include in AI in Cybersecurity Companies.

Total 36 Major Players are covered.

 

Artificial Intelligence in Cybersecurity Market Highlights

The study categorizes the artificial intelligence in cybersecurity  market based on  offering, Deployment Type, Security Type, Applications, End Users, Technology, and Geography

Aspect

Details

By Offering

  • Hardware
  • Software
  • Services

BY Deployment Type

  • On-premise
  • Cloud

BY Security Type

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

By Technology

  • Machine learning
  • Natural Language Processing (NLP)
  • Context-Aware Computing

By Application

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

By End Users

  • BFSI
  • Retail
  • Government & Defense
  • Manufacturing
  • Infrastructure
  • Enterprise
  • Healthcare
  • Automotive & Transportation
  • Other

By Geography

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • France
    • Italy
    • Spain
    • Rest of Europe
  • Asia Pacific (APAC)
    • China
    • Japan
    • South Korea
    • India
    • Rest of APAC
  • Rest of the World (RoW)
    • Middle East and Africa (MEA)
    • South America

Recent Developments

  • In September 2022, NVIDIA launched NVIDIA IGX, which is a platform for high-precision edge AI, bringing advanced security and proactive safety to sensitive industries such as manufacturing, logistics and healthcare.
  • In November 2021, IBM launched QRadar XDR Connect which is a cloud-native, open XDR solution. Advanced analytics, along with artificial intelligence (AI), automation, and connected workflows from XDR offer deeper insights, quick action, and automatic response to stop and slow the progression of threats.
  • In March 2021, Samsung collaborated with Mastercard (US) to work on a biometric scanning payment card with a built-in fingerprint reader,
  • In December 2019, Intel acquired Habana Labs (Israel), an Israel-based developer of programmable deep learning accelerators for data centers

Frequently Asked Questions (FAQ):

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TABLE OF CONTENTS
 
1 INTRODUCTION (Page No. - 35)
    1.1 STUDY OBJECTIVES 
    1.2 MARKET DEFINITION 
           1.2.1 INCLUSIONS AND EXCLUSIONS
           1.2.2 COMPANY: INCLUSIONS AND EXCLUSIONS
           1.2.3 OFFERING: INCLUSIONS AND EXCLUSIONS
           1.2.4 DEPLOYMENT TYPE: INCLUSIONS AND EXCLUSIONS
           1.2.5 SECURITY TYPE: INCLUSIONS AND EXCLUSIONS
           1.2.6 TECHNOLOGY: INCLUSIONS AND EXCLUSIONS
           1.2.7 APPLICATION: INCLUSIONS AND EXCLUSIONS
           1.2.8 END USER: INCLUSIONS AND EXCLUSIONS
           1.2.9 REGION: INCLUSIONS AND EXCLUSIONS
    1.3 STUDY SCOPE 
           1.3.1 MARKETS COVERED
                    FIGURE 1 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET SEGMENTATION
           1.3.2 REGIONAL SCOPE
           1.3.3 YEARS CONSIDERED
    1.4 CURRENCY CONSIDERED 
           TABLE 1 CURRENCY CONVERSION RATES
    1.5 LIMITATIONS 
    1.6 STAKEHOLDERS 
    1.7 SUMMARY OF CHANGES 
 
2 RESEARCH METHODOLOGY (Page No. - 43)
    2.1 RESEARCH DATA 
           FIGURE 2 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY: RESEARCH DESIGN
           2.1.1 SECONDARY AND PRIMARY RESEARCH
                    2.1.1.1 Key industry insights
           2.1.2 SECONDARY DATA
                    2.1.2.1 List of major secondary sources
                    2.1.2.2 Secondary sources
           2.1.3 PRIMARY DATA
                    2.1.3.1 Breakdown of primaries
                    2.1.3.2 Primary sources
    2.2 MARKET SIZE ESTIMATION 
           FIGURE 3 PROCESS FLOW OF MARKET SIZE ESTIMATION
           2.2.1 BOTTOM-UP APPROACH
           FIGURE 4 BOTTOM-UP APPROACH
           2.2.2 TOP-DOWN APPROACH
           FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY: APPROACH 1 (SUPPLY SIDE)−REVENUE GENERATED BY KEY PLAYERS IN ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET
           FIGURE 6 TOP-DOWN APPROACH
    2.3 MARKET BREAKDOWN AND DATA TRIANGULATION 
           FIGURE 7 DATA TRIANGULATION
    2.4 RESEARCH ASSUMPTIONS 
           2.4.1 LIMITATIONS
           FIGURE 8 RESEARCH LIMITATIONS
    2.5 RISK ASSESSMENT 
           TABLE 2 RISK ASSESSMENT
 
3 EXECUTIVE SUMMARY (Page No. - 55)
    FIGURE 9 SOFTWARE TO HOLD LARGEST MARKET SHARE OF ARTIFICIAL INTELLIGENCE IN CYBERSECURITY DURING 2023–2028
    FIGURE 10 CLOUD-BASED DEPLOYMENT OF AI IN CYBERSECURITY TO GROW AT HIGHER CAGR DURING 2023–2028
    FIGURE 11 CLOUD SECURITY IN AI IN CYBERSECURITY MARKET TO GROW AT HIGHEST CAGR DURING 2023–2028
    FIGURE 12 ENTERPRISE TO DOMINATE ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET IN 2022
    FIGURE 13 NORTH AMERICA TO HOLD LARGEST MARKET SHARE OF ARTIFICIAL INTELLIGENCE IN CYBERSECURITY DURING 2023–2028
 
4 PREMIUM INSIGHTS (Page No. - 60)
    4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET 
           FIGURE 14 ASIA PACIFIC TO GROW AT HIGHEST CAGR IN ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET DURING 2023–2028
    4.2 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY TECHNOLOGY 
           FIGURE 15 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR MACHINE LEARNING TO GROW AT HIGHEST CAGR FROM 2023−2028
    4.3 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY APPLICATION 
           FIGURE 16 IDENTITY AND ACCESS MANAGEMENT TO HOLD LARGEST SIZE DURING FORECAST PERIOD
    4.4 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET IN ASIA PACIFIC, BY APPLICATION AND COUNTRY 
           FIGURE 17 CHINA TO HOLD LARGEST SHARE OF ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET IN ASIA PACIFIC
    4.5 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY COUNTRY 
           FIGURE 18 MARKET IN CHINA TO GROW AT HIGHEST CAGR FROM 2023 TO 2028
 
5 MARKET OVERVIEW (Page No. - 63)
    5.1 INTRODUCTION 
    5.2 MARKET DYNAMICS 
           FIGURE 19 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET DYNAMICS
           5.2.1 DRIVERS
                    5.2.1.1 Growing adoption of IoT and increasing number of connected devices
                    5.2.1.2 Increasing instances of cyber threats
                               FIGURE 20 US: NUMBER OF CYBERATTACKS, 2015–2021
                    5.2.1.3 Rising concerns of data protection
                    5.2.1.4 Increasing vulnerability of Wi-Fi networks to security threats
           5.2.2 RESTRAINTS
                    5.2.2.1 Inability of AI to stop zero-day and advanced threats
                    5.2.2.2 Rise in insider cyber threats
           5.2.3 OPPORTUNITIES
                    5.2.3.1 Growing need for cloud-based security solutions among SMEs
                    5.2.3.2 Increasing use of social media for business functions
                    5.2.3.3 Zero trust framework providing advanced security
           5.2.4 CHALLENGES
                    5.2.4.1 Limited number of cybersecurity and AI professionals
                    5.2.4.2 Lack of interoperability with existing information systems
                    5.2.4.3 Shortcomings of AI
    5.3 TECHNOLOGY ANALYSIS 
           5.3.1 DEEP LEARNING
           5.3.2 MACHINE LEARNING
           5.3.3 USER AND ENTITY BEHAVIOR ANALYTICS (UEBA)
           5.3.4 TOKENIZATION
           5.3.5 BLOCKCHAIN
    5.4 PORTER'S FIVE FORCES ANALYSIS 
           TABLE 3 IMPACT OF PORTER'S FIVE FORCES
           5.4.1 THREAT OF NEW ENTRANTS
           5.4.2 THREAT OF SUBSTITUTES
           5.4.3 BARGAINING POWER OF SUPPLIERS
           5.4.4 BARGAINING POWER OF BUYERS
           5.4.5 INTENSITY OF COMPETITIVE RIVALRY
    5.5 TRADE DATA 
           TABLE 4 EXPORTS DATA FOR PRODUCTS UNDER HS CODE 8471, BY COUNTRY, 2017–2021 (USD MILLION)
           TABLE 5 IMPORTS DATA FOR PRODUCTS UNDER HS CODE 8471, BY COUNTRY, 2017–2021 (USD MILLION)
    5.6 REGULATORY IMPLICATIONS 
           5.6.1 GENERAL DATA PROTECTION REGULATION
           5.6.2 PAYMENT CARD INDUSTRY DATA SECURITY STANDARD
           5.6.3 HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY ACT
           5.6.4 FEDERAL INFORMATION SECURITY MANAGEMENT ACT
           5.6.5 GRAMM-LEACH-BLILEY ACT
           5.6.6 SARBANES-OXLEY ACT
           5.6.7 INTERNATIONAL ORGANIZATION FOR STANDARDIZATION 27001
           5.6.8 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
                    TABLE 6 NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
                    TABLE 7 EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
                    TABLE 8 ASIA PACIFIC: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
                    TABLE 9 REST OF THE WORLD: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    5.7 KEY STAKEHOLDERS AND BUYING PROCESS 
           5.7.1 KEY STAKEHOLDERS IN BUYING PROCESS
                    FIGURE 21 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE APPLICATIONS
                    TABLE 10 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE APPLICATIONS (%)
           5.7.2 BUYING CRITERIA
                    FIGURE 22 KEY BUYING CRITERIA FOR TOP THREE APPLICATIONS
                    TABLE 11 KEY BUYING CRITERIA FOR TOP THREE APPLICATIONS
    5.8 CASE STUDY ANALYSIS 
           5.8.1 CARGILLS BANK IMPLEMENTS IBM QRADAR SIEM
           5.8.2 INFOSYS IMPLEMENTS INFRASTRUCTURE SECURITY ENDPOINT MANAGEMENT (ISEM) FOR INVESTMENT GIANT
           5.8.3 SIEMENS USES AMAZON WEB SERVICES (AWS) TO BUILD DATA ANALYTICS PLATFORM
           5.8.4 INFOSYS CREATES UNIFIED DATA LOSS PREVENTION PLATFORM USING GCP (GOOGLE CLOUD PLATFORM)
    5.9 KEY CONFERENCES AND EVENTS, 2022–2023 
           TABLE 12 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: KEY CONFERENCES AND EVENTS, 2022-2032
    5.10 REVENUE SHIFT AND NEW REVENUE POCKETS FOR CUSTOMERS' BUSINESSES 
           FIGURE 23 REVENUE SHIFT IN AI IN CYBERSECURITY MARKET
    5.11 ECOSYSTEM ANALYSIS 
           TABLE 13 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: ECOSYSTEM
           FIGURE 24 KEY PLAYERS IN ARTIFICIAL INTELLIGENCE IN CYBERSECURITY ECOSYSTEM
    5.12 VALUE CHAIN ANALYSIS 
           FIGURE 25 VALUE CHAIN ANALYSIS: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET
           5.12.1 RESEARCH, DESIGN, AND DEVELOPMENT
           5.12.2 COMPONENT PROVIDERS
           5.12.3 SYSTEM INTEGRATORS
           5.12.4 MARKETING AND SALES EXECUTIVES
           5.12.5 END USER INDUSTRIES
           5.12.6 SERVICE PROVIDERS
    5.13 PATENT ANALYSIS 
           TABLE 14 IMPORTANT PATENT REGISTRATIONS, 2017–2021
           FIGURE 26 COMPANIES WITH HIGHEST NUMBER OF PATENT APPLICATIONS IN LAST 10 YEARS
           FIGURE 27 ANNUAL NUMBER OF PATENTS GRANTED OVER LAST FIVE YEARS
           TABLE 15 TOP 10 PATENT OWNERS
    5.14 PRICING ANALYSIS 
           FIGURE 28 PRICING BY KEY PLAYERS
           FIGURE 29 AVERAGE SELLING PRICING
 
6 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY OFFERING (Page No. - 96)
    6.1 INTRODUCTION 
           FIGURE 30 SOFTWARE TO DOMINATE AI IN CYBERSECURITY MARKET DURING FORECAST PERIOD
           TABLE 16 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY OFFERING, 2019–2022 (USD MILLION)
           TABLE 17 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY OFFERING, 2023–2028 (USD MILLION)
    6.2 HARDWARE 
           TABLE 18 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR HARDWARE, BY REGION, 2019–2022 (USD MILLION)
           TABLE 19 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR HARDWARE, BY REGION, 2023–2028 (USD MILLION)
           TABLE 20 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY HARDWARE, 2019–2022 (USD MILLION)
           TABLE 21 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY HARDWARE, 2023–2028 (USD MILLION)
           6.2.1 PROCESSORS
                    TABLE 22 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR PROCESSORS, BY TYPE, 2019–2022 (USD MILLION)
                    TABLE 23 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR PROCESSORS, BY TYPE, 2023–2028 (USD MILLION)
                    6.2.1.1 MPU
                               6.2.1.1.1 Performs arithmetic and logic operations that use registers
                    6.2.1.2 GPU
                               6.2.1.2.1 Rapidly manipulates and alters memory to accelerate image creation
                    6.2.1.3 FPGA
                               6.2.1.3.1 Enables rapid prototyping, shorter time-to-market, reprogram ability, and longevity
                    6.2.1.4 ASIC
                               6.2.1.4.1 Affordable and enables improved performance
           6.2.2 MEMORY
                    6.2.2.1 Memory solutions help store large volume of data
           6.2.3 NETWORK
                    6.2.3.1 High-bandwidth networks enable ultrafast communication between CPU and GPU
    6.3 SOFTWARE 
           TABLE 24 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR SOFTWARE, BY REGION, 2019–2022 (USD MILLION)
           TABLE 25 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR SOFTWARE, BY REGION, 2023–2028 (USD MILLION)
           FIGURE 31 AI PLATFORM TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
           TABLE 26 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR SOFTWARE, BY TYPE, 2019–2022 (USD MILLION)
           TABLE 27 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR SOFTWARE, BY TYPE, 2023–2028 (USD MILLION)
           6.3.1 AI SOLUTIONS
                    6.3.1.1 Advancements in AI solutions boosting market growth
           6.3.2 AI PLATFORM
                    6.3.2.1 AI platforms are used to develop learning algorithms and intelligent applications
                               TABLE 28 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR AI PLATFORM, BY TYPE, 2019–2022 (USD MILLION)
                               TABLE 29 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR AI PLATFORM, BY TYPE, 2023–2028 (USD MILLION)
                    6.3.2.2 Application Program Interface (API)
                               6.3.2.2.1 Easily develops program by providing all building blocks
                    6.3.2.3 Machine learning framework
                               6.3.2.3.1 Enables developers to create machine learning models and algorithms
    6.4 SERVICES 
           TABLE 30 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR SERVICES, BY REGION, 2019–2022 (USD MILLION)
           TABLE 31 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR SERVICES, BY REGION, 2023–2028 (USD MILLION)
           TABLE 32 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR SERVICES, BY TYPE, 2019–2022 (USD MILLION)
           TABLE 33 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR SERVICES, BY TYPE, 2023–2028 (USD MILLION)
           6.4.1 DEPLOYMENT & INTEGRATION
                    6.4.1.1 Required for configuration of AI systems
           6.4.2 SUPPORT & MAINTENANCE
                    6.4.2.1 Help in maintaining acceptable standards of systems
 
7 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY DEPLOYMENT TYPE (Page No. - 108)
    7.1 INTRODUCTION 
           FIGURE 32 CLOUD-BASED DEPLOYMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
           TABLE 34 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY DEPLOYMENT TYPE, 2019–2022 (USD MILLION)
           TABLE 35 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY DEPLOYMENT TYPE, 2023–2028 (USD MILLION)
    7.2 CLOUD 
           7.2.1 COST-EFFECTIVENESS OF CLOUD-BASED SOLUTIONS TO BOOST MARKET
                    TABLE 36 CLOUD: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 37 CLOUD: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY REGION, 2023–2028 (USD MILLION)
    7.3 ON-PREMISE 
           7.3.1 FULL CONTROL OF PLATFORMS, APPLICATIONS, SYSTEMS, AND DATA TO DRIVE MARKET
                    TABLE 38 ON-PREMISE: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 39 ON-PREMISE: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY REGION, 2023–2028 (USD MILLION)
 
8 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY SECURITY TYPE (Page No. - 114)
    8.1 INTRODUCTION 
           FIGURE 33 CLOUD SECURITY TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
           TABLE 40 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY SECURITY TYPE, 2019–2022 (USD MILLION)
           TABLE 41 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY SECURITY TYPE, 2023–2028 (USD MILLION)
    8.2 NETWORK SECURITY 
           8.2.1 HELPS TO PROTECT DATA FROM NUMEROUS THREATS
                    TABLE 42 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR NETWORK SECURITY, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 43 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR NETWORK SECURITY, BY REGION, 2023–2028 (USD MILLION)
    8.3 ENDPOINT SECURITY 
           8.3.1 PROVIDES REAL-TIME THREAT DETECTION, PREVENTION, AND RESPONSE TO NETWORK DEVICES
                    TABLE 44 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR ENDPOINT SECURITY, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 45 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR ENDPOINT SECURITY, BY REGION, 2023–2028 (USD MILLION)
    8.4 APPLICATION SECURITY 
           8.4.1 ENABLES ENTERPRISES TO SECURE BUSINESS-SENSITIVE APPLICATIONS
                    FIGURE 34 APPLICATION SECURITY IN ASIA PACIFIC TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
                    TABLE 46 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR APPLICATION SECURITY, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 47 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR APPLICATION SECURITY, BY REGION, 2023–2028 (USD MILLION)
    8.5 CLOUD SECURITY 
           8.5.1 PROVIDES COMPLETE THREAT PROTECTION AGAINST RANSOMWARE, INTERNAL EMAIL RISKS, AND FILE-SHARING RISKS
                    TABLE 48 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR CLOUD SECURITY, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 49 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR CLOUD SECURITY, BY REGION, 2023–2028(USD MILLION)
 
9 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY TECHNOLOGY (Page No. - 123)
    9.1 INTRODUCTION 
           FIGURE 35 MACHINE LEARNING TO LEAD AI IN CYBERSECURITY MARKET DURING FORECAST PERIOD
           TABLE 50 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY TECHNOLOGY, 2019–2022 (USD MILLION)
           TABLE 51 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY TECHNOLOGY, 2023–2028 (USD MILLION)
    9.2 MACHINE LEARNING 
           9.2.1 MACHINE LEARNING HELP BUSINESSES DEAL WITH LARGE VOLUMES OF DATA
                    TABLE 52 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR MACHINE LEARNING, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 53 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR MACHINE LEARNING, BY REGION, 2023–2028 (USD MILLION)
                    TABLE 54 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR MACHINE LEARNING, BY TYPE, 2019–2022 (USD MILLION)
                    TABLE 55 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR MACHINE LEARNING, BY TYPE, 2023–2028 (USD MILLION)
           9.2.2 DEEP LEARNING
                    9.2.2.1 Growing application of deep learning algorithms
           9.2.3 SUPERVISED LEARNING
                    9.2.3.1 Classification and regression − major segments of supervised learning
           9.2.4 UNSUPERVISED LEARNING
                    9.2.4.1 Includes clustering methods consisting of algorithms with unlabeled training data
           9.2.5 REINFORCEMENT LEARNING
                    9.2.5.1 Allows systems and software to determine ideal behavior to maximize performance
           9.2.6 OTHERS
    9.3 NATURAL LANGUAGE PROCESSING 
           9.3.1 REAL-TIME TRANSLATION AND DEVELOPMENT OF SYSTEMS THAT CAN INTERACT THROUGH DIALOGUES
                    TABLE 56 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR NATURAL LANGUAGE PROCESSING, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 57 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR NATURAL LANGUAGE PROCESSING, BY REGION, 2023–2028 (USD MILLION)
                    FIGURE 36 CLASSIFICATION & CATEGORIZATION IN NLP TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
                    TABLE 58 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR NATURAL LANGUAGE PROCESSING, BY PROCESS, 2019–2022 (USD MILLION)
                    TABLE 59 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR NATURAL LANGUAGE PROCESSING, BY PROCESS, 2023–2028 (USD MILLION)
    9.4 CONTEXT-AWARE COMPUTING 
           9.4.1 DEVELOPMENT OF SOPHISTICATED HARD AND SOFT SENSORS
                    TABLE 60 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR CONTEXT-AWARE COMPUTING, BY REGION, 2019–2022 (USD MILLION)
                    TABLE 61 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR CONTEXT-AWARE COMPUTING, BY REGION, 2023–2028 (USD MILLION)
                    TABLE 62 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR CONTEXT-AWARE COMPUTING, BY PROCESS, 2019–2022 (USD MILLION)
                    TABLE 63 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR CONTEXT-AWARE COMPUTING, BY PROCESS, 2023–2028 (USD MILLION)
 
10 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY APPLICATION (Page No. - 135)
     10.1 INTRODUCTION 
             FIGURE 37 IDENTITY & ACCESS MANAGEMENT TO HOLD LARGEST SHARE OF MARKET DURING FORECAST PERIOD
             TABLE 64 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY APPLICATION, 2019–2022 (USD MILLION)
             TABLE 65 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
     10.2 IDENTITY & ACCESS MANAGEMENT 
             10.2.1 INCREASING THREAT OF DATA BREACHES DUE TO INSIDER ATTACKS
                        TABLE 66 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR IDENTITY & ACCESS MANAGEMENT, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 67 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR IDENTITY & ACCESS MANAGEMENT, BY REGION, 2023–2028 (USD MILLION)
     10.3 RISK & COMPLIANCE MANAGEMENT 
             10.3.1 GROWING NEED FOR INTERNAL AUDIT FEATURES AND REGULATORY COMPLIANCE MANDATES
                        TABLE 68 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR RISK & COMPLIANCE MANAGEMENT, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 69 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR RISK & COMPLIANCE MANAGEMENT, BY REGION, 2023–2028 (USD MILLION)
     10.4 DATA LOSS PREVENTION 
             10.4.1 STRICT IMPLEMENTATION OF GOVERNMENT REGULATIONS AND LAWS
                        TABLE 70 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR DATA LOSS PREVENTION, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 71 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR DATA LOSS PREVENTION, BY REGION, 2023–2028 (USD MILLION)
     10.5 UNIFIED THREAT MANAGEMENT 
             10.5.1 PROVIDES MULTIPLE SECURITY FUNCTIONS TO PROTECT ENTERPRISES FROM EVOLVING CYBER THREATS
                        TABLE 72 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR UNIFIED THREAT MANAGEMENT, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 73 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR UNIFIED THREAT MANAGEMENT, BY REGION, 2023–2028 (USD MILLION)
     10.6 SECURITY & VULNERABILITY MANAGEMENT 
             10.6.1 EXPANDING VOLUME OF DATA AND RISING ADOPTION OF BYOD TREND
                        TABLE 74 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR SECURITY & VULNERABILITY MANAGEMENT, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 75 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR SECURITY & VULNERABILITY MANAGEMENT, BY REGION, 2023–2028 (USD MILLION)
     10.7 ANTIVIRUS/ANTIMALWARE 
             10.7.1 RISING NUMBER OF MALWARE AND VIRUS ATTACKS
                        TABLE 76 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR ANTIVIRUS/ANTIMALWARE, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 77 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR ANTIVIRUS/ANTIMALWARE, BY REGION, 2023–2028 (USD MILLION)
     10.8 FRAUD DETECTION/ANTIFRAUD 
             10.8.1 NEED FOR ROBUST INFRASTRUCTURE WITH HIGH-PERFORMANCE COMPUTING AND SCALABILITY
                        TABLE 78 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR FRAUD DETECTION/ ANTIFRAUD, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 79 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR FRAUD DETECTION/ ANTIFRAUD, BY REGION, 2023–2028 (USD MILLION)
     10.9 INTRUSION DETECTION/PREVENTION SYSTEM 
             10.9.1 MONITORS NETWORK ACROSS ENTERPRISES FOR SUSPICIOUS ACTIVITY
                        TABLE 80 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR INTRUSION DETECTION/PREVENTION SYSTEM, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 81 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR INTRUSION DETECTION/PREVENTION SYSTEM, BY REGION, 2023–2028 (USD MILLION)
     10.10 THREAT INTELLIGENCE/DETECTION 
             10.10.1 PREDICTS CYBER THREATS IN ADVANCE
                        TABLE 82 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR THREAT INTELLIGENCE, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 83 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR THREAT INTELLIGENCE, BY REGION, 2023–2028 (USD MILLION)
     10.11 OTHERS 
             TABLE 84 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR OTHER APPLICATIONS, BY REGION, 2019–2022 (USD MILLION)
             TABLE 85 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR OTHER APPLICATIONS, BY REGION, 2023–2028 (USD MILLION)
 
11 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY END USER (Page No. - 152)
     11.1 INTRODUCTION 
             FIGURE 38 AUTOMOTIVE TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
             TABLE 86 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY END USER, 2019–2022 (USD MILLION)
             TABLE 87 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY END USER, 2023–2028 (USD MILLION)
     11.2 BFSI 
             11.2.1 INCREASED INSTANCES OF CYBER-ATTACKS IN FINANCIAL VERTICAL
                        TABLE 88 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR BFSI, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 89 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR BFSI, BY REGION, 2023–2028 (USD MILLION)
     11.3 RETAIL 
             11.3.1 LARGE NUMBER OF MONETARY TRANSACTIONS AND EXPANDING CONSUMER BASE
                        TABLE 90 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR RETAIL, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 91 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR RETAIL, BY REGION, 2023–2028 (USD MILLION)
     11.4 GOVERNMENT & DEFENSE 
             11.4.1 INCREASED SPENDING ON AI-BASED CYBERSECURITY SOLUTIONS
                        TABLE 92 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR GOVERNMENT & DEFENSE, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 93 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR GOVERNMENT & DEFENSE, BY REGION, 2023–2028 (USD MILLION)
     11.5 MANUFACTURING 
             11.5.1 HUGE INVESTMENTS IN INDUSTRY FOR AUTOMATION
                        TABLE 94 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR MANUFACTURING, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 95 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR MANUFACTURING, BY REGION, 2023–2028 (USD MILLION)
     11.6 INFRASTRUCTURE 
             11.6.1 GROWING FOCUS ON SMART INFRASTRUCTURE
                        TABLE 96 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR INFRASTRUCTURE, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 97 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR INFRASTRUCTURE, BY REGION, 2023–2028 (USD MILLION)
     11.7 ENTERPRISE 
             11.7.1 RAPID TECHNOLOGICAL ADVANCEMENTS IN IOT, CLOUD, AND TELECOM CONNECTIVITY
                        FIGURE 39 ASIA PACIFIC TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD IN ENTERPRISE SEGMENT
                        TABLE 98 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR ENTERPRISE, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 99 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR ENTERPRISE, BY REGION, 2023–2028 (USD MILLION)
     11.8 HEALTHCARE 
             11.8.1 INCREASING NUMBER OF DATA BREACHES AND COMPROMISED ELECTRONIC HEALTHCARE RECORDS
                        TABLE 100 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR HEALTHCARE, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 101 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR HEALTHCARE, BY REGION, 2023–2028 (USD MILLION)
     11.9 AUTOMOTIVE 
             11.9.1 INCREASING CYBERATTACKS DUE TO RISING NUMBER OF CONNECTED AND AUTONOMOUS CARS
                        TABLE 102 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR AUTOMOTIVE, BY REGION, 2019–2022 (USD MILLION)
                        TABLE 103 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR AUTOMOTIVE, BY REGION, 2023–2028 (USD MILLION)
     11.10 OTHERS 
             TABLE 104 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR OTHER END USERS, BY REGION, 2019–2022 (USD MILLION)
             TABLE 105 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET FOR OTHER END USERS, BY REGION, 2023–2028 (USD MILLION)
 
12 REGIONAL ANALYSIS (Page No. - 168)
     12.1 INTRODUCTION 
             FIGURE 40 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET IN ASIA PACIFIC TO GROW AT HIGHEST CAGR FROM 2023−2028
             TABLE 106 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY REGION, 2019–2022 (USD MILLION)
             TABLE 107 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY REGION, 2023–2028 (USD MILLION)
     12.2 NORTH AMERICA 
             FIGURE 41 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET SNAPSHOT
             TABLE 108 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY DEPLOYMENT TYPE, 2019–2022 (USD MILLION)
             TABLE 109 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY DEPLOYMENT TYPE, 2023–2028 (USD MILLION)
             TABLE 110 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY SECURITY TYPE, 2019–2022 (USD MILLION)
             TABLE 111 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY SECURITY TYPE, 2023–2028 (USD MILLION)
             TABLE 112 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY APPLICATION, 2019–2022 (USD MILLION)
             TABLE 113 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
             TABLE 114 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY COUNTRY, 2019–2022 (USD MILLION)
             TABLE 115 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY COUNTRY, 2023–2028 (USD MILLION)
             12.2.1 US
                        12.2.1.1 Rapid growth in technological innovations and increased use of internet
             12.2.2 CANADA
                        12.2.2.1 Investment in modern technologies to drive market
             12.2.3 MEXICO
                        12.2.3.1 Increasing connectivity to boost market
     12.3 EUROPE 
             FIGURE 42 EUROPE: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET SNAPSHOT
             TABLE 116 EUROPE: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY DEPLOYMENT TYPE, 2019–2022 (USD MILLION)
             TABLE 117 EUROPE: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY DEPLOYMENT TYPE, 2023–2028(USD MILLION)
             TABLE 118 EUROPE: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY SECURITY TYPE, 2019–2022 (USD MILLION)
             TABLE 119 EUROPE: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY SECURITY TYPE, 2023–2028 (USD MILLION)
             TABLE 120 EUROPE: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY APPLICATION, 2019–2022 (USD MILLION)
             TABLE 121 EUROPE: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
             TABLE 122 EUROPE: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY COUNTRY, 2019–2022 (USD MILLION)
             TABLE 123 EUROPE: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY COUNTRY, 2023–2028(USD MILLION)
             12.3.1 GERMANY
                        12.3.1.1 Increasing number of ransomware, spyware, and reconnaissance to fuel market
             12.3.2 UK
                        12.3.2.1 Threat to IT, telecom, and financial sectors to increase demand for cybersecurity
             12.3.3 FRANCE
                        12.3.3.1 Market growth attributed to increasing adoption of AI cybersecurity in BFSI, government, and retail
             12.3.4 ITALY
                        12.3.4.1 Rising spread of cloud computing, social media, wireless connectivity, e-commerce, and big data to provide opportunities
 
             12.3.5 SPAIN
                        12.3.5.1 Private and public sector companies’ initiatives to adopt AI in cybersecurity to fuel market
             12.3.6 REST OF EUROPE
     12.4 ASIA PACIFIC 
             FIGURE 43 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET SNAPSHOT
             TABLE 124 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY DEPLOYMENT TYPE, 2019–2022 (USD MILLION)
             TABLE 125 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY DEPLOYMENT TYPE, 2023–2028 (USD MILLION)
             TABLE 126 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY SECURITY TYPE, 2019–2022 (USD MILLION)
             TABLE 127 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY SECURITY TYPE, 2023–2028 (USD MILLION)
             TABLE 128 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET IN ASIA PACIFIC, BY APPLICATION, 2019–2022 (USD MILLION)
             TABLE 129 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
             TABLE 130 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY COUNTRY, 2019–2022 (USD MILLION)
             TABLE 131 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY COUNTRY, 2023–2028 (USD MILLION)
             12.4.1 CHINA
                        12.4.1.1 Increased instances of virus, worm, spyware, trojan, and ransomware attacks to drive market
             12.4.2 JAPAN
                        12.4.2.1 Significant number of ICT users to drive market
             12.4.3 SOUTH KOREA
                        12.4.3.1 Government initiatives to enhance cybersecurity driving market growth
             12.4.4 INDIA
                        12.4.4.1 Participation of SMEs and large enterprises
             12.4.5 REST OF ASIA PACIFIC
     12.5 REST OF THE WORLD 
             TABLE 132 ROW: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY DEPLOYMENT TYPE, 2019–2022 (USD MILLION)
             TABLE 133 ROW: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY DEPLOYMENT TYPE, 2023–2028 (USD MILLION)
             TABLE 134 ROW: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY SECURITY TYPE, 2019–2022 (USD MILLION)
             TABLE 135 ROW: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY SECURITY TYPE, 2023–2028 (USD MILLION)
             TABLE 136 ROW: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY APPLICATION, 2019–2022 (USD MILLION)
             TABLE 137 ROW: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY APPLICATION, 2023–2028 (USD MILLION)
             TABLE 138 ROW: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY REGION, 2019–2022 (USD MILLION)
             TABLE 139 ROW: ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET, BY REGION, 2023–2028 (USD MILLION)
             12.5.1 MIDDLE EAST AND AFRICA
                        12.5.1.1 Demand to protect critical infrastructure and industrial assets to aid market growth
             12.5.2 SOUTH AMERICA
                        12.5.2.1 Service-specific attacks, malware, phishing, DDoS, and reconnaissance are major threat vectors
 
13 COMPETITIVE LANDSCAPE (Page No. - 194)
     13.1 OVERVIEW 
             TABLE 140 COMPANIES ADOPTED ACQUISITIONS AND PARTNERSHIPS AS KEY GROWTH STRATEGIES FROM 2019−2022
     13.2 MARKET SHARE ANALYSIS 
             TABLE 141 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: DEGREE OF COMPETITION FOR SOFTWARE 2022
             TABLE 142 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: RANKING ANALYSIS FOR SOFTWARE 2022
             FIGURE 44 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET SHARE ANALYSIS FOR SOFTWARE (2022)
             TABLE 143 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: DEGREE OF COMPETITION FOR HARDWARE 2022
             TABLE 144 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: RANKING ANALYSIS FOR HARDWARE 2022
             FIGURE 45 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET SHARE ANALYSIS FOR HARDWARE (2022)
     13.3 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: REVENUE ANALYSIS, 2017–2021 
             FIGURE 46 FIVE-YEAR REVENUE SNAPSHOT OF KEY HARDWARE COMPANIES
             FIGURE 47 THREE-YEAR REVENUE SNAPSHOT OF KEY SOFTWARE COMPANIES
     13.4 COMPANY EVALUATION QUADRANT, 2022 
             13.4.1 STARS
             13.4.2 PERVASIVE PLAYERS
             13.4.3 EMERGING LEADERS
             13.4.4 PARTICIPANTS
                        FIGURE 48 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: GLOBAL COMPANY EVALUATION QUADRANT, 2022
     13.5 COMPETITIVE BENCHMARKING 
             13.5.1 PRODUCT FOOTPRINT (12 COMPANIES)
                        TABLE 145 SECURITY TYPE: COMPANY FOOTPRINT (33 COMPANIES)
                        TABLE 146 DEPLOYMENT TYPE: COMPANY FOOTPRINT (33 COMPANIES)
                        TABLE 147 REGION: COMPANY FOOTPRINT (33 COMPANIES)
                        TABLE 148 OVERALL: COMPANY FOOTPRINT (33 COMPANIES)
     13.6 STARTUP/SME EVALUATION QUADRANT, 2022 
             13.6.1 PROGRESSIVE COMPANIES
             13.6.2 RESPONSIVE COMPANIES
             13.6.3 DYNAMIC COMPANIES
             13.6.4 STARTING BLOCKS
                        FIGURE 49 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: GLOBAL STARTUP/SME EVALUATION QUADRANT, 2022
     13.7 COMPETITIVE SCENARIO AND TRENDS 
             13.7.1 PRODUCT LAUNCHES
                        TABLE 149 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: PRODUCT LAUNCHES, 2019–2022
             13.7.2 DEALS
                        TABLE 150 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: DEALS, 2018–2022
                        TABLE 151 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET: KEY STARTUPS/SMES
 
14 COMPANY PROFILES (Page No. - 228)
     14.1 INTRODUCTION 
(Business overview, Products offered, Recent Developments, MNM view)*  
     14.2 KEY PLAYERS 
             14.2.1 NVIDIA
                        TABLE 152 NVIDIA: BUSINESS OVERVIEW
                        FIGURE 50 NVIDIA: COMPANY SNAPSHOT
                        TABLE 153 NVIDIA: PRODUCTS OFFERED
                        TABLE 154 NVIDIA: PRODUCT LAUNCHES
                        TABLE 155 NVIDIA: DEALS
             14.2.2 INTEL
                        TABLE 156 INTEL: BUSINESS OVERVIEW
                        FIGURE 51 INTEL: COMPANY SNAPSHOT
                        TABLE 157 INTEL: PRODUCTS OFFERED
                        TABLE 158 INTEL: PRODUCT LAUNCHES
                        TABLE 159 INTEL: DEALS
             14.2.3 XILINX INC.
                        TABLE 160 XILINX INC.: BUSINESS OVERVIEW
                        FIGURE 52 XILINX INC.: COMPANY SNAPSHOT
                        TABLE 161 XILINX INC.: PRODUCTS OFFERED
                        TABLE 162 XILINX INC.: PRODUCT LAUNCHES
                        TABLE 163 XILINX INC.: DEALS
             14.2.4 SAMSUNG ELECTRONICS CO., LTD
                        TABLE 164 SAMSUNG ELECTRONICS CO., LTD: BUSINESS OVERVIEW
                        FIGURE 53 SAMSUNG ELECTRONICS CO., LTD: COMPANY SNAPSHOT
                        TABLE 165 SAMSUNG ELECTRONICS CO., LTD: PRODUCTS OFFERED
                        TABLE 166 SAMSUNG ELECTRONICS CO., LTD: PRODUCT LAUNCHES
                        TABLE 167 SAMSUNG ELECTRONICS CO., LTD: DEALS
             14.2.5 MICRON TECHNOLOGY
                        TABLE 168 MICRON TECHNOLOGY: BUSINESS OVERVIEW
                        FIGURE 54 MICRON TECHNOLOGY: COMPANY SNAPSHOT
                        TABLE 169 MICRON TECHNOLOGY: PRODUCTS OFFERED
                        TABLE 170 MICRON TECHNOLOGY: PRODUCT LAUNCHES
                        TABLE 171 MICRON TECHNOLOGY: DEALS
             14.2.6 INTERNATIONAL BUSINESS MACHINES CORPORATION (IBM)
                        FIGURE 55 IBM: COMPANY SNAPSHOT
                        TABLE 172 IBM: BUSINESS OVERVIEW
                        TABLE 173 IBM: PRODUCTS OFFERED
                        TABLE 174 IBM: PRODUCT LAUNCHES
                        TABLE 175 IBM: DEALS
             14.2.7 AMAZON WEB SERVICES (AWS)
                        TABLE 176 AMAZON WEB SERVICES: BUSINESS OVERVIEW
                        FIGURE 56 AMAZON WEB SERVICES: COMPANY SNAPSHOT
                        TABLE 177 AMAZON WEB SERVICES: PRODUCTS OFFERED
                        TABLE 178 AMAZON WEB SERVICES: PRODUCT LAUNCHES
                        TABLE 179 AMAZON WEB SERVICES: DEALS
             14.2.8 MICROSOFT CORPORATION
                        TABLE 180 MICROSOFT CORPORATION: BUSINESS OVERVIEW
                        FIGURE 57 MICROSOFT CORPORATION: COMPANY SNAPSHOT
                        TABLE 181 MICROSOFT CORPORATION: PRODUCTS OFFERED
                        TABLE 182 MICROSOFT CORPORATION: PRODUCT LAUNCHES
                        TABLE 183 MICROSOFT CORPORATION: DEALS
             14.2.9 PALO ALTO NETWORKS
                        TABLE 184 PALO ALTO NETWORKS: BUSINESS OVERVIEW
                        FIGURE 58 PALO ALTO NETWORKS: COMPANY SNAPSHOT
                        TABLE 185 PALO ALTO NETWORKS: PRODUCTS OFFERED
                        TABLE 186 PALO ALTO NETWORKS: PRODUCT LAUNCHES
                        TABLE 187 PALO ALTO NETWORKS: DEALS
             14.2.10 TRELLIX
                        TABLE 188 TRELLIX: BUSINESS OVERVIEW
                        TABLE 189 TRELLIX: PRODUCTS OFFERED
                        TABLE 190 TRELLIX: PRODUCT LAUNCHES
             14.2.11 CROWDSTRIKE
                        TABLE 191 CROWDSTRIKE: BUSINESS OVERVIEW
                        FIGURE 59 CROWDSTRIKE: COMPANY SNAPSHOT
                        TABLE 192 CROWDSTRIKE: PRODUCTS OFFERED
                        TABLE 193 CROWDSTRIKE: PRODUCT LAUNCHES
                        TABLE 194 CROWDSTRIKE: DEALS
             14.2.12 NORTON LIFELOCK
                        TABLE 195 NORTON LIFELOCK: BUSINESS OVERVIEW
                        FIGURE 60 NORTON LIFELOCK: COMPANY SNAPSHOT
                        TABLE 196 NORTON LIFELOCK: PRODUCTS OFFERED
                        TABLE 197 NORTON LIFELOCK: PRODUCT LAUNCHES
                        TABLE 198 NORTON LIFELOCK: DEALS
     14.3 OTHER PLAYERS 
             14.3.1 CYLANCE
             14.3.2 THREATMETRIX
             14.3.3 SECURONIX
             14.3.4 SIFT SCIENCE
             14.3.5 ACALVIO TECHNOLOGIES
             14.3.6 DARKTRACE
             14.3.7 SPARKCONGNITION
             14.3.8 FORTINET
             14.3.9 CHECK POINT SOFTWARE TECHNOLOGIES
             14.3.10 HIGH-TECH BRIDGE
             14.3.11 DEEP INSTINCT
             14.3.12 SENTINELONE
             14.3.13 FEEDZAI
             14.3.14 VECTRA
             14.3.15 ZIMPERIUM
             14.3.16 ARGUS CYBER SECURITY
             14.3.17 NOZOMI NETWORKS
             14.3.18 BITSIGHT TECHNOLOGIES
     14.4 ANTIVIRUS COMPANIES 
             14.4.1 KASPERSKY LAB
             14.4.2 BITDEFENDER
             14.4.3 ESET
*Details on Business overview, Products offered, Recent Developments, MNM view might not be captured in case of unlisted companies.  
 
15 APPENDIX (Page No. - 304)
     15.1 DISCUSSION GUIDE 
     15.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 
     15.3 CUSTOMIZATION OPTIONS 
     15.4 RELATED REPORTS 
     15.5 AUTHOR DETAILS 
 
 
 
 
 
     15.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 
     15.3 CUSTOMIZATION OPTIONS 
     15.4 RELATED REPORTS 
     15.5 AUTHOR DETAILS 
 
 
 
 
 

The study involved four major activities in estimating the size of the artificial intelligence in cybersecurity market. Exhaustive secondary research has been done to collect information on the market, peer market, and parent market. Validation of these findings, assumptions, and sizing with industry experts across the value chain through primary research has been the next step. Both top-down and bottom-up approaches have been employed to estimate the global market size. After that, market breakdown and data triangulation have been used to estimate the market sizes of segments and subsegments.

Secondary Research

The secondary sources referred to for this research study includes These secondary sources include biometric technologies journals and magazines; annual reports, press releases, and investor presentations of companies; white papers; certified publications and articles from recognized authors; and directories and databases such as Factiva, Hoovers, and OneSource.

Secondary research has been conducted to obtain key information about the supply chain of the artificial intelligence in cybersecurity industry, the monetary chain of the market, the total pool of key players, and market segmentation according to the industry trends to the bottommost level, regional markets, and key developments from both market- and technology oriented perspectives. The secondary data has been collected and analyzed to arrive at the overall market size, which has further been validated by primary research.

Primary Research

Extensive primary research has been conducted after acquiring an understanding of artificial intelligence in cybersecurity market scenario through secondary research. Several primary interviews have been conducted with market experts from both the demand- (consumers, industries) and supply-side (artificial intelligence in cybersecurity providers) players across four major regions, namely, North America, Europe, Asia Pacific, and the Rest of the World (the Middle East & Africa). Approximately 75% and 25% of primary interviews have been conducted from the supply and demand side, respectively. Primary data has been collected through questionnaires, emails, and telephonic interviews. In the canvassing of primaries, various departments within organizations, such as sales, operations, and administration, were covered to provide a holistic viewpoint in our report.

fter interacting with industry experts, brief sessions were conducted with highly experienced independent consultants to reinforce the findings from our primaries. This, along with the in-house subject matter experts’ opinions, has led us to the findings as described in the remainder of this report.

Artificial Intelligence in Security Market Size, and Share

Market Size Estimation

Both top-down and bottom-up approaches have been used to estimate and validate the total size of the artificial intelligence in cybersecurity market. These methods have also been extensively used to estimate the sizes of various market subsegments. The research methodology used to estimate the market sizes includes the following:

  • Identifying various applications that use or are expected to use artificial intelligence in cybersecurity market.
  • Analyzing historical and current data pertaining to the size of the artificial intelligence in the cybersecurity market for each application
  • Analyzing the average selling prices of artificial intelligence in cybersecurity based on different technologies
  • Studying various paid and unpaid sources, such as annual reports, press releases, white papers, and databases
  • Identifying leading providers of artificial intelligence in cybersecurity, studying their portfolios, and understanding features of their products and their underlying technologies, as well as the types of artificial intelligence in cybersecurity products offered
  • Tracking ongoing and identifying upcoming developments in the market through investments, research and development activities, product launches, expansions, and partnerships, and forecasting the market size based on these developments and other critical parameters
  • Carrying out multiple discussions with key opinion leaders to understand the technologies used in artificial intelligence in cybersecurity, and products wherein they are deployed, and analyze the break-up of the scope of work carried out by key manufacturers of artificial intelligence in cybersecurity solutions providers
  • Verifying and crosschecking estimates at every level through discussions with key opinion leaders, such as CXOs, directors, and operations managers, and finally with domain experts at MarketsandMarkets

Market Size Estimation Methodology-Bottom-Up Approach

Artificial Intelligence in Security Market Size, and Bottom-Up Approach

Data Triangulation

After arriving at the overall market size-using the market size estimation processes explained above-the market has been split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation, and market breakdown procedures have been employed, wherever applicable. The data has been triangulated by studying various factors and trends from both the demand and supply sides.

The main objectives of this study are as follows:

  • To define, describe, segment, and forecast the artificial intelligence in cybersecurity market, in terms of value, based on deployment type, security type, offering, applications, end users, and geography.
  • To forecast the size of the market and its segments with respect to four main regions, namely, North America, Europe, Asia Pacific (APAC), and the Rest of the World (RoW), along with their key countries
  • To strategically analyze micromarkets1 with respect to individual growth trends, prospects, and contributions to the total market
  • To provide detailed information regarding the key factors influencing market growth, such as drivers, restraints, opportunities, and challenges
  • To provide a detailed analysis of the artificial intelligence in the cybersecurity  value chain
  • To analyze the opportunities in the market for stakeholders and provide a detailed competitive landscape of the market leaders
  • To strategically profile the key players and comprehensively analyze their market ranking and core competencies2
  • To analyze key growth strategies such as expansions, contracts, joint ventures, acquisitions, product launches and developments, and research and development activities undertaken by players operating in the artificial intelligence in cybersecurity market.

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  • Further breakdown of the market in different regions to the country-level
  • Detailed analysis and profiling of additional market players (up to 5)
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