Artificial Intelligence (AI) in Cybersecurity Market - Global Size, Share, Trend Analysis, Opportunity and Forecast Report, 2019–2029, Segmented By Type (Network Security, Endpoint Security, Offering Security, Cloud Security); By Offering (Hardware, Software, Services); By Technology (Machine Learning (ML), Natural Language Processing (NLP), Context-aware Computing); By Application (Identity & Access Management, Risk & Compliance Management, Data Loss Prevention, Unified Threat Management, Fraud Detection/Anti-Fraud, Threat Intelligence, Others); By Vertical (BFSI, Retail, Government & Defense, Manufacturing, Enterprise, Healthcare, Automotive & Transportation, Others); By Region (North America, Europe, Asia Pacific, Latin America, Middle East and Africa)
Global Artificial Intelligence (AI) in Cybersecurity Market Size Zooming More Than 3.5X to Cross USD 79.2 Billion by 2029
Global artificial intelligence (AI) in cybersecurity market is flourishing because of increasing use of social media for business functions and a spurring demand for advanced cybersecurity solutions and privacy.
BlueWeave Consulting, a leading strategic consulting and market research firm, in its recent study, estimated the global artificial intelligence (AI) in cybersecurity market size at USD 20.26 billion in 2022. During the forecast period between 2023 and 2029, BlueWeave expects the global artificial intelligence (AI) in cybersecurity market size to grow at a robust CAGR of 21.63% reaching a value of USD 79.23 billion by 2029. Major growth drivers for the global artificial intelligence (AI) in cybersecurity market include an increasing demand for advanced security solutions, a growing number of cyberattacks, and the increasing sophistication of cybercriminals. Cyber AI is now in demand, as it can provide a proactive defense mechanism with precise detection. For instance, there is a high demand for AI to perform constant user authentication using behavioral biometrics. Industry players should prioritize machine learning (ML) algorithms to take advantage of AI's power to strengthen security intelligence. Also, rise in privacy concerns, the significance of AI-based cybersecurity solutions in the banking sector, and the frequency and complexity of cyberthreats are expected to propel the growth of global artificial intelligence (AI) in cybersecurity market during the period in analysis. However, advanced demonstrative data requirement is anticipated to restrain the growth of the overall market.
Global Artificial Intelligence (AI) in Cybersecurity Market – Overview
Artificial intelligence (AI) in cybersecurity refers to the application of AI-based technologies to enhance the security of computer systems, networks, and data from cyber threats, such as malware, phishing, hacking, and insider threats. AI is used in cybersecurity to automate and improve various security processes, such as threat detection, incident response, and vulnerability assessment. AI-based systems use machine learning (ML) algorithms to analyze substantial amounts of data from various sources, including network logs, security events, and user behavior, to identify patterns and potential threats.
Impact of COVID-19 on Global Artificial Intelligence (AI) in Cybersecurity Market
COVID-19 pandemic had a dual impact on the global artificial intelligence (AI) in cybersecurity market. While the pandemic led to economic uncertainties and disruptions across industries, it also highlighted the importance of cybersecurity as more businesses and individuals shifted to remote work and digital communications. As businesses and individuals became more reliant on technology during the pandemic, the demand for cybersecurity solutions increased. It led to increased investments in AI-based cybersecurity solutions, which can provide real-time threat detection and response capabilities. The pandemic also highlighted the need for automation in cybersecurity, as security teams were forced to work remotely and handle a higher volume of security incidents. AI-based cybersecurity solutions can automate routine security tasks, allowing security teams to focus on more complex tasks.
Global Artificial Intelligence (AI) in Cybersecurity Market – By Technology
By technology, the global artificial intelligence (AI) market is divided into Machine Learning (ML), Natural Language Processing (NLP), and Context-aware computing segments. The machine learning (ML) segment took the lead. With deep learning becoming increasingly prevalent across end-use sectors, the ML technology will experience rapid growth. Leading businesses, including Google and IBM, have been using ML for threat detection and email filtering. Businesses are leveraging machine intelligence and deep learning to improve cybersecurity procedures. During the period in analysis, the natural language processing (NLP) segment may boost the growth of the global AI in cybersecurity market. The surge in popularity of sentiment analysis, natural language inference, text summarization, and question-answering systems is major drivers for the rise.
Competitive Landscape
Major players operating in the global artificial intelligence (AI) in cybersecurity market include Acalvio Technologies Inc., Amazon Web Services, Inc., Cylance Inc. (BlackBerry), Darktrace, FireEye, Inc., Fortinet, Inc., IBM Corporation, Intel Corporation, LexisNexis, Micron Technology, Inc., Palo Alto Networks Inc., Trellix, CrowdStrike, NortonLifeLock, ThreatMetrix, Securonix Inc., and Microsoft. To further enhance their market share, these companies employ various strategies, including mergers and acquisitions, partnerships, joint ventures, license agreements, and new product launches.
The report's in-depth analysis provides information about growth potential, upcoming trends, and the Global Artificial Intelligence (AI) in Cybersecurity Market statistics. It also highlights the factors driving forecasts of total market size. The report promises to provide recent technology trends in the Global Artificial Intelligence (AI) in Cybersecurity Market along with industry insights to help decision-makers make sound strategic decisions. Furthermore, the report also analyses the growth drivers, challenges, and competitive dynamics of the market.
- 1. Research Framework
- 1.1. Research Objective
- 1.2. Product Overview
- 1.3. Market Segmentation
- 2. Executive Summary
- 3. Global Buy Now Pay Later (BNPL) Market Insights
- 3.1. Industry Value Chain Analysis
- 3.2. DROC Analysis
- 3.2.1. Growth Drivers
- 3.2.1.1. Growing digitization in overall market
- 3.2.1.2. Increase in Adoption of Online Payment Methods
- 3.2.2. Restraints
- 3.2.2.1. High availability of multiple payment options
- 3.2.2.2. High late fee charges on delayed repayment
- 3.2.3. Opportunity
- 3.2.3.1. Increasing adoption by retailers
- 3.2.3.2. Increasing adoption of smartphone among consumers
- 3.2.4. Challenges
- 3.2.4.1. Lack awareness regarding these services
- 3.2.4.2. Integration of BPNL is expensive
- 3.3. Technology Advancements/Recent Developments
- 3.4. Regulatory Framework
- 3.5. Porter’s Five Forces Analysis
- 3.5.1. Bargaining Power of Suppliers
- 3.5.2. Bargaining Power of Buyers
- 3.5.3. Threat of New Entrants
- 3.5.4. Threat of Substitutes
- 3.5.5. Intensity of Rivalry
- 4. Global Buy Now Pay Later (BNPL) Market Overview
- 4.1. Market Size & Forecast, 2019–2029
- 4.1.1. By Value (USD Million)
- 4.2. Market Share and Forecast
- 4.2.1. By Channel
- 4.2.1.1. Online
- 4.2.1.2. POS
- 4.2.2. By Enterprise Size
- 4.2.2.1. Large Enterprises
- 4.2.2.2. Small & Medium Enterprises
- 4.2.3. By Application
- 4.2.3.1. Access Control
- 4.2.3.2. Time and Attendance Management
- 4.2.3.3. Identity Verification
- 4.2.3.4. Border Control
- 4.2.3.5. Others
- 4.2.4. By End User
- 4.2.4.1. Retail Goods
- 4.2.4.2. Media & Entertainment
- 4.2.4.3. Healthcare & Wellness
- 4.2.4.4. Automotive
- 4.2.4.5. Home Improvement
- 4.2.4.6. Others
- 4.2.5. By Region
- 4.2.5.1. North America
- 4.2.5.2. Europe
- 4.2.5.3. Asia Pacific (APAC)
- 4.2.5.4. Latin America (LATAM)
- 4.2.5.5. Middle East and Africa (MEA)
- 5. North America Buy Now Pay Later (BNPL) Market
- 5.1. Market Size & Forecast, 2019–2029
- 5.1.1. By Value (USD Million)
- 5.2. Market Share & Forecast
- 5.2.1. By Channel
- 5.2.2. By Enterprise Size
- 5.2.3. By Application
- 5.2.4. By End User
- 5.2.5. By Country
- 5.2.5.1. United States
- 5.2.5.1.1. By Channel
- 5.2.5.1.2. By Enterprise Size
- 5.2.5.1.3. By Application
- 5.2.5.1.4. By End User
- 5.2.5.2. Canada
- 5.2.5.2.1. By Channel
- 5.2.5.2.2. By Enterprise Size
- 5.2.5.2.3. By Application
- 5.2.5.2.4. By End User
- 6. Europe Buy Now Pay Later (BNPL) Market
- 6.1. Market Size & Forecast, 2019–2029
- 6.1.1. By Value (USD Million)
- 6.2. Market Share & Forecast
- 6.2.1. By Channel
- 6.2.2. By Enterprise Size
- 6.2.3. By Application
- 6.2.4. By End User
- 6.2.5. By Country
- 6.2.5.1. Germany
- 6.2.5.1.1. By Channel
- 6.2.5.1.2. By Enterprise Size
- 6.2.5.1.3. By Application
- 6.2.5.1.4. By End User
- 6.2.5.2. United Kingdom
- 6.2.5.2.1. By Channel
- 6.2.5.2.2. By Enterprise Size
- 6.2.5.2.3. By Application
- 6.2.5.2.4. By End User
- 6.2.5.3. Italy
- 6.2.5.3.1. By Channel
- 6.2.5.3.2. By Enterprise Size
- 6.2.5.3.3. By Application
- 6.2.5.3.4. By End User
- 6.2.5.4. France
- 6.2.5.4.1. By Channel
- 6.2.5.4.2. By Enterprise Size
- 6.2.5.4.3. By Application
- 6.2.5.4.4. By End User
- 6.2.5.5. Spain
- 6.2.5.5.1. By Channel
- 6.2.5.5.2. By Enterprise Size
- 6.2.5.5.3. By Application
- 6.2.5.5.4. By End User
- 6.2.5.6. Belgium
- 6.2.5.6.1. By Channel
- 6.2.5.6.2. By Enterprise Size
- 6.2.5.6.3. By Application
- 6.2.5.6.4. By End User
- 6.2.5.7. Russia
- 6.2.5.7.1. By Channel
- 6.2.5.7.2. By Enterprise Size
- 6.2.5.7.3. By Application
- 6.2.5.7.4. By End User
- 6.2.5.8. The Netherlands
- 6.2.5.8.1. By Channel
- 6.2.5.8.2. By Enterprise Size
- 6.2.5.8.3. By Application
- 6.2.5.8.4. By End User
- 6.2.5.9. Rest of Europe
- 6.2.5.9.1. By Channel
- 6.2.5.9.2. By Enterprise Size
- 6.2.5.9.3. By Application
- 6.2.5.9.4. By End User
- 7. Asia Pacific Buy Now Pay Later (BNPL) Market
- 7.1. Market Size & Forecast, 2019–2029
- 7.1.1. By Value (USD Million)
- 7.2. Market Share & Forecast
- 7.2.1. By Channel
- 7.2.2. By Enterprise Size
- 7.2.3. By Application
- 7.2.4. By End User
- 7.2.5. By Country
- 7.2.5.1. China
- 7.2.5.1.1. By Channel
- 7.2.5.1.2. By Enterprise Size
- 7.2.5.1.3. By Application
- 7.2.5.1.4. By End User
- 7.2.5.2. India
- 7.2.5.2.1. By Channel
- 7.2.5.2.2. By Enterprise Size
- 7.2.5.2.3. By Application
- 7.2.5.2.4. By End User
- 7.2.5.3. Japan
- 7.2.5.3.1. By Channel
- 7.2.5.3.2. By Enterprise Size
- 7.2.5.3.3. By Application
- 7.2.5.3.4. By End User
- 7.2.5.4. South Korea
- 7.2.5.4.1. By Channel
- 7.2.5.4.2. By Enterprise Size
- 7.2.5.4.3. By Application
- 7.2.5.4.4. By End User
- 7.2.5.5. Australia & New Zealand
- 7.2.5.5.1. By Channel
- 7.2.5.5.2. By Enterprise Size
- 7.2.5.5.3. By Application
- 7.2.5.5.4. By End User
- 7.2.5.6. Indonesia
- 7.2.5.6.1. By Channel
- 7.2.5.6.2. By Enterprise Size
- 7.2.5.6.3. By Application
- 7.2.5.6.4. By End User
- 7.2.5.7. Malaysia
- 7.2.5.7.1. By Channel
- 7.2.5.7.2. By Enterprise Size
- 7.2.5.7.3. By Application
- 7.2.5.7.4. By End User
- 7.2.5.8. Singapore
- 7.2.5.8.1. By Channel
- 7.2.5.8.2. By Enterprise Size
- 7.2.5.8.3. By Application
- 7.2.5.8.4. By End User
- 7.2.5.9. Vietnam
- 7.2.5.9.1. By Channel
- 7.2.5.9.2. By Enterprise Size
- 7.2.5.9.3. By Application
- 7.2.5.9.4. By End User
- 7.2.5.10. Rest of APAC
- 7.2.5.10.1. By Channel
- 7.2.5.10.2. By Enterprise Size
- 7.2.5.10.3. By Application
- 7.2.5.10.4. By End User
- 8. Latin America Buy Now Pay Later (BNPL) Market
- 8.1. Market Size & Forecast, 2019–2029
- 8.1.1. By Value (USD Million)
- 8.2. Market Share & Forecast
- 8.2.1. By Channel
- 8.2.2. By Enterprise Size
- 8.2.3. By Application
- 8.2.4. By End User
- 8.2.5. By Country
- 8.2.5.1. Brazil
- 8.2.5.1.1. By Channel
- 8.2.5.1.2. By Enterprise Size
- 8.2.5.1.3. By Application
- 8.2.5.1.4. By End User
- 8.2.5.2. Mexico
- 8.2.5.2.1. By Channel
- 8.2.5.2.2. By Enterprise Size
- 8.2.5.2.3. By Application
- 8.2.5.2.4. By End User
- 8.2.5.3. Argentina
- 8.2.5.3.1. By Channel
- 8.2.5.3.2. By Enterprise Size
- 8.2.5.3.3. By Application
- 8.2.5.3.4. By End User
- 8.2.5.4. Peru
- 8.2.5.4.1. By Channel
- 8.2.5.4.2. By Enterprise Size
- 8.2.5.4.3. By Application
- 8.2.5.4.4. By End User
- 8.2.5.5. Rest of LATAM
- 8.2.5.5.1. By Channel
- 8.2.5.5.2. By Enterprise Size
- 8.2.5.5.3. By Application
- 8.2.5.5.4. By End User
- 9. Middle East & Africa Buy Now Pay Later (BNPL) Market
- 9.1. Market Size & Forecast, 2019–2029
- 9.1.1. By Value (USD Million)
- 9.2. Market Share & Forecast
- 9.2.1. By Channel
- 9.2.2. By Enterprise Size
- 9.2.3. By Application
- 9.2.4. By End User
- 9.2.5. By Country
- 9.2.5.1. Saudi Arabia
- 9.2.5.1.1. By Channel
- 9.2.5.1.2. By Enterprise Size
- 9.2.5.1.3. By Application
- 9.2.5.1.4. By End User
- 9.2.5.2. UAE
- 9.2.5.2.1. By Channel
- 9.2.5.2.2. By Enterprise Size
- 9.2.5.2.3. By Application
- 9.2.5.2.4. By End User
- 9.2.5.3. Qatar
- 9.2.5.3.1. By Channel
- 9.2.5.3.2. By Enterprise Size
- 9.2.5.3.3. By Application
- 9.2.5.3.4. By End User
- 9.2.5.4. Kuwait
- 9.2.5.4.1. By Channel
- 9.2.5.4.2. By Enterprise Size
- 9.2.5.4.3. By Application
- 9.2.5.4.4. By End User
- 9.2.5.5. South Africa
- 9.2.5.5.1. By Channel
- 9.2.5.5.2. By Enterprise Size
- 9.2.5.5.3. By Application
- 9.2.5.5.4. By End User
- 9.2.5.6. Nigeria
- 9.2.5.6.1. By Channel
- 9.2.5.6.2. By Enterprise Size
- 9.2.5.6.3. By Application
- 9.2.5.6.4. By End User
- 9.2.5.7. Algeria
- 9.2.5.7.1. By Channel
- 9.2.5.7.2. By Enterprise Size
- 9.2.5.7.3. By Application
- 9.2.5.7.4. By End User
- 9.2.5.8. Rest of MEA
- 9.2.5.8.1. By Channel
- 9.2.5.8.2. By Enterprise Size
- 9.2.5.8.3. By Application
- 9.2.5.8.4. By End User
- 10. Competitive Landscape
- 10.1. List of Key Players and Their Offerings
- 10.2. Global Buy Now Pay Later (BNPL) Market Share Analysis, 2022
- 10.3. Competitive Benchmarking, By Operating Parameters
- 10.4. Key Strategic Developments (Mergers, Acquisitions, Partnerships, etc.)
- 11. Impact of Covid-19 on India Worm Gear Reducers Market
- 12. Company Profile (Company Overview, Financial Matrix, Competitive Landscape, Key Personnel, Key Competitors, Contact Address, Strategic Outlook, SWOT Analysis)
- 12.1. Affirm Holdings Inc.
- 12.2. Afterpay
- 12.3. Klarna Bank AB
- 12.4. Laybuy Group Holdings Limited
- 12.5. PayPal Holdings Inc.
- 12.6. Payl8r (Social Money Ltd.)
- 12.7. Perpay Table,
- 12.8. LazyPay
- 12.9. Sezzle
- 12.10. Splitit
- 12.11. Other Prominent Players
- 13. Key Strategic Recommendations
- 14. Research Methodology
- 14.1. Qualitative Research
- 14.1.1. Primary & Secondary Research
- 14.2. Quantitative Research
- 14.3. Market Breakdown & Data Triangulation
- 14.3.1. Secondary Research
- 14.3.2. Primary Research
- 14.4. Breakdown of Primary Research Respondents, By Region
- 14.5. Assumptions & Limitations
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