AI Cyber Security Market Size, Share, Opportunities, And Trends By Application (Verification, Identity, And Access Management, Fraud Detection And Identifying Phishing, Incident Response, Others), By Deployment (Cloud, On-Premise), By End-User (Retail And E-commerce, BFSI, Government, Automotive And Transportation, Healthcare, Others), And By Geography - Forecasts From 2024 To 2029

  • Published : Feb 2024
  • Report Code : KSI061616661
  • Pages : 141

The AI cyber security market is expected to witness significant growth during the forecasted period.

AI cyber security, also known as artificial intelligence cyber security, refers to the application of artificial intelligence (AI) and machine learning techniques to enhance the security of digital systems, networks, and data against cyber threats. It involves the use of AI algorithms to detect, prevent, and respond to various types of cyber-attacks, vulnerabilities, and security incidents.

AI cyber security combines threat intelligence streams and databases to improve security analytics and decision-making. AI-powered systems may give organizations timely insights into emerging risks and attack trends by aggregating and analyzing threat data from many sources, such as open-source intelligence (OSINT), dark web monitoring, and security research. User and Entity Behaviour Analytics (UEBA) solutions employ artificial intelligence and machine learning to analyze user behavior and detect insider threats, account compromises, and unauthorized access. By combining user activity data with contextual information and risk indicators, UEBA platforms may detect anomalous behavior patterns that indicate possible security breaches or malicious actions.

In today's complex and dynamic threat landscape, AI cybersecurity is crucial in assisting organizations in defending against cyber attacks, improving threat detection and response capabilities, and increasing overall security resilience. By leveraging AI technology, organizations may improve their cybersecurity posture and reduce the risks associated with cyber assaults and data breaches.

Market Drivers

  • Increasing cyber threat is fueling the AI cyber security market growth

The rise of cyber threats, such as malware, ransomware, phishing assaults, and insider threats, continues to provide substantial difficulties to organizations worldwide. The increasing sophistication and frequency of cyber assaults create a demand for sophisticated cyber security solutions, such as AI-powered threat detection and prevention systems. According to data from the Ministry of Home Affairs, Government of India, more than 16 lakh cybercrime incidences were recorded, and over 32 thousand FIRs were lodged between January 1, 2020 and December 7, 2022.

The growing cyber threat landscape emphasizes the need for modern cybersecurity systems that can deliver real-time threat detection, proactive threat prevention, and adaptive defense capabilities. AI-powered cybersecurity solutions enable organizations to detect and respond fast to developing cyber threats, reducing risks and safeguarding against possible data breaches and security events. As the threat environment evolves, demand for AI cybersecurity solutions is projected to rise as organizations prioritize cybersecurity as an essential component of their risk management strategy.

  • Growing demand for cloud-based security solutions is contributing to the AI cyber security market growth

Cloud security is crucial in modern-day cloud systems, providing real-time protection against emerging cyber threats. AI cybersecurity providers offer cloud-native solutions that safeguard users and data across various access points. Cisco Umbrella is one such product, a cloud security solution provided by Cisco, known as Secure Access Service Edge (SASE). This solution provides networking and security capabilities in the cloud, allowing businesses to scale up or down seamlessly, irrespective of their location. Another such product, the SASE security model is placed at the cloud edge and offers end-to-end security, including data centers, remote offices, roaming users, and more. SASE provides secure access to cloud-based collaboration applications or on-premise applications inside the corporate data center. Thus, the growing demand for cloud-based security solutions is driving the adoption of AI cybersecurity technologies, enabling organizations to enhance security, streamline operations, and mitigate cyber risks effectively.

Market Restraints

  • High resource intensity and cost of AI cyber security solutions hampering the market growth

Developing, installing, and maintaining AI cyber security systems may be time-consuming and expensive for businesses. AI algorithms demand large computing resources for training and inference activities, necessitating the purchase of high-performance hardware, cloud services, and storage infrastructure. AI cyber security market, vendors and organizations must focus on improving the affordability, accessibility, and usability of AI-driven security solutions which will help organizations maximize the benefits of AI-driven security

AI cyber security market is segmented based on its applications

The AI cyber security industry, based on its applications, is divided into three major segments: threat detection and prevention, incident response, and identity and access management. Threat detection and prevention systems make use of threat information feeds and databases to improve security analytics and decision-making capabilities. Incident Response tools analyze and rebuild digital evidence from security incidents, easing the investigation and repair process. Security orchestration, automation, and response systems improve incident response workflows and foster collaboration between security teams and IT operations. AI-based User and Entity Behaviour Analytics are used in Identity and Access Management solutions to detect anomalous behavior patterns and associated security risks. AI-powered adaptive authentication systems tailor authentication requirements to user behavior, context, and risk factors, therefore enhancing access restrictions and minimizing unauthorized access threats.

North America region is anticipated to hold a significant share of the AI cyber security market.

The North American region is expected to have a sizable proportion of the AI cyber security market due to the spike in network-connected devices and the rising use of the Internet of Things, 5G, and Wi-Fi. Organizations in the automotive, healthcare, government, energy, and mining industries have accelerated 5G network deployment, creating a potential access point for hackers. The region is home to numerous AI startup research institutions, and technology giants, such as Anthropic, Adept AI, Berkeley AI research lab, Berkeley AI research lab, University Of Arizona Artificial Intelligence Lab, and Wysa are driving advancements in AI-driven cybersecurity technologies. Government initiatives, public-private partnerships, and cybersecurity investment programs aim to enhance cybersecurity resilience and protect critical infrastructure from cyber threats. The region faces diverse ranges of cyber threats, including nation-state-sponsored attacks, cyber espionage, ransomware, and insider threats. The demand for AI-powered threat detection, incident response, and risk mitigation solutions is high, driving demand for AI-powered cybersecurity solutions.

Key Developments

  • April 2023 - IBM revealed its new security suite, which aims to unify and expedite the security analyst experience throughout the incident lifecycle. The IBM Security QRadar Suite is a substantial extension and expansion of the QRadar brand, encompassing all key threat detection, investigation, and response capabilities, with considerable investment in innovation throughout the portfolio. The IBM Security QRadar Suite is developed on an open platform and is particularly intended to meet the needs of a hybrid cloud. It has a single, modernized user interface across all products that are infused with powerful AI and automation, allowing analysts to operate with increased speed, efficiency, and precision across their core toolsets.
  • September 2022 – NVIDIA launched the NVIDIA IGX platform for high-precision edge AI, delivering superior security and proactive safety to sensitive industries including manufacturing, shipping, and healthcare. Previously, such sectors required costly custom-built solutions for unique used cases, but the IGX platform was simply programmable and flexible to meet a variety of requirements. This platform was a strong mix of hardware and software and used NVIDIA IGX Orin, the world's most powerful, compact, and energy-efficient AI supercomputer for self-driving industrial equipment and medical devices.

Company Products

  • Guardium – IBM Security Guardium is a set of data security software products in the IBM Security portfolio that detects vulnerabilities and protects sensitive on-premises and cloud data. It is a data security solution that adapts to changing threat environments, ensuring total visibility, compliance, and protection across the data security lifecycle. Some of its advantages include automated data finding and classification, real-time monitoring and data security, and accelerated data compliance tasks.
  • Sophos Cloud Native Security –  Sophos Cloud Native Security offers extensive cloud security coverage across diverse environments, workloads, and identities. It seamlessly incorporates security technologies for workloads, cloud environments, and entitlement management. The integration with SIEM, workflow, and DevOps technologies enhances organizational agility. It effectively prioritizes resources by utilizing risk-assessed and color-coded warnings, along with providing comprehensive alerts and guided remediation to support teams in enhancing their cloud security capabilities.

Market Segmentation

  • By Application
    • Verification, Identity, and Access Management
    • Fraud Detection and Identifying Phishing
    • Incident Response
    • Others
  • By Deployment
    • Cloud
    • On-Premise
  • By End-User
    • Retail and E-commerce
    • BFSI
    • Government
    • Automotive and Transportation
    • Healthcare
    • Others
  • By Geography
    • North America
      • USA
      • Canada
      • Mexico
    • South America
      • Brazil
      • Argentina
      • Others
    • Europe
      • Germany
      • France
      • UK
      • Spain
      • Others
    • Middle East and Africa
      • Saudi Arabia
      • UAE
      • Israel
      • Others
    • Asia Pacific
      • China
      • Japan
      • India
      • South Korea
      • Indonesia
      • Taiwan
      • Others

1. INTRODUCTION

1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base, and Forecast Years Timeline

1.8. Key benefits to the stakeholder

2. RESEARCH METHODOLOGY

2.1. Research Design

2.2. Research Process

3. EXECUTIVE SUMMARY

3.1. Key Findings

3.2. Analyst View

4. MARKET DYNAMICS

4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

4.5. Analyst View

5. AI CYBER SECURITY MARKET BY APPLICATION

5.1. Introduction

5.2. Verification, Identity and Access Management

5.2.1. Market opportunities and trends

5.2.2. Growth prospects

5.2.3. Geographic lucrativeness 

5.3. Fraud Detection and Identifying Phishing  

5.3.1. Market opportunities and trends

5.3.2. Growth prospects

5.3.3. Geographic lucrativeness 

5.4. Incident Response

5.4.1. Market opportunities and trends

5.4.2. Growth prospects

5.4.3. Geographic lucrativeness 

5.5. Others

5.5.1. Market opportunities and trends

5.5.2. Growth prospects

5.5.3. Geographic lucrativeness 

6. AI CYBER SECURITY MARKET BY DEPLOYMENT

6.1. Introduction

6.2. Cloud

6.2.1. Market opportunities and trends

6.2.2. Growth prospects

6.2.3. Geographic lucrativeness 

6.3. On-Premise

6.3.1. Market opportunities and trends

6.3.2. Growth prospects

6.3.3. Geographic lucrativeness 

7. AI CYBER SECURITY MARKET BY END-USER

7.1. Introduction

7.2. Retail and Ecommerce

7.2.1. Market opportunities and trends

7.2.2. Growth prospects

7.2.3. Geographic lucrativeness 

7.3. BFSI

7.3.1. Market opportunities and trends

7.3.2. Growth prospects

7.3.3. Geographic lucrativeness 

7.4. Government

7.4.1. Market opportunities and trends

7.4.2. Growth prospects

7.4.3. Geographic lucrativeness 

7.5. Automotive and Transportation

7.5.1. Market opportunities and trends

7.5.2. Growth prospects

7.5.3. Geographic lucrativeness 

7.6. Healthcare

7.6.1. Market opportunities and trends

7.6.2. Growth prospects

7.6.3. Geographic lucrativeness 

7.7. Others

7.7.1. Market opportunities and trends

7.7.2. Growth prospects

7.7.3. Geographic lucrativeness 

8. AI CYBER SECURITY MARKET BY GEOGRAPHY

8.1. Introduction

8.2. North America

8.2.1. By Application

8.2.2. By Deployment

8.2.3. By End-user

8.2.4. By Country

8.2.4.1. United States

8.2.4.1.1. Market Trends and Opportunities

8.2.4.1.2. Growth Prospects

8.2.4.2. Canada

8.2.4.2.1. Market Trends and Opportunities

8.2.4.2.2. Growth Prospects

8.2.4.3. Mexico

8.2.4.3.1. Market Trends and Opportunities

8.2.4.3.2. Growth Prospects

8.3. South America

8.3.1. By Application

8.3.2. By Deployment

8.3.3. By End-user

8.3.4. By Country

8.3.4.1. Brazil

8.3.4.1.1. Market Trends and Opportunities

8.3.4.1.2. Growth Prospects

8.3.4.2. Argentina

8.3.4.2.1. Market Trends and Opportunities

8.3.4.2.2. Growth Prospects

8.3.4.3. Others

8.3.4.3.1. Market Trends and Opportunities

8.3.4.3.2. Growth Prospects

8.4. Europe

8.4.1. By Application

8.4.2. By Deployment

8.4.3. By End-user

8.4.4. By Country

8.4.4.1. Germany

8.4.4.1.1. Market Trends and Opportunities

8.4.4.1.2. Growth Prospects

8.4.4.2. France

8.4.4.2.1. Market Trends and Opportunities

8.4.4.2.2. Growth Prospects

8.4.4.3. United Kingdom

8.4.4.3.1. Market Trends and Opportunities

8.4.4.3.2. Growth Prospects

8.4.4.4. Spain

8.4.4.4.1. Market Trends and Opportunities

8.4.4.4.2. Growth Prospects

8.4.4.5. Others

8.4.4.5.1. Market Trends and Opportunities

8.4.4.5.2. Growth Prospects

8.5. Middle East and Africa

8.5.1. By Application

8.5.2. By Deployment

8.5.3. By End-user

8.5.4. By Country

8.5.4.1. Saudi Arabia

8.5.4.1.1. Market Trends and Opportunities

8.5.4.1.2. Growth Prospects

8.5.4.2. UAE

8.5.4.2.1. Market Trends and Opportunities

8.5.4.2.2. Growth Prospects

8.5.4.3. Israel

8.5.4.3.1. Market Trends and Opportunities

8.5.4.3.2. Growth Prospects  

8.5.4.4. Others

8.5.4.4.1. Market Trends and Opportunities

8.5.4.4.2. Growth Prospects

8.6. Asia Pacific

8.6.1. By Application

8.6.2. By Deployment

8.6.3. By End-user

8.6.4. By Country

8.6.5. China

8.6.5.1. Market Trends and Opportunities

8.6.5.2. Growth Prospects

8.6.6. Japan

8.6.6.1. Market Trends and Opportunities

8.6.6.2. Growth Prospects

8.6.7. India

8.6.7.1.1. Market Trends and Opportunities

8.6.7.1.2. Growth Prospects

8.6.8. South Korea

8.6.8.1.1. Market Trends and Opportunities

8.6.8.1.2. Growth Prospects

8.6.9. Indonesia

8.6.9.1.1. Market Trends and Opportunities

8.6.9.1.2. Growth Prospects

8.6.10. Taiwan

8.6.10.1.1. Market Trends and Opportunities

8.6.10.1.2. Growth Prospects

8.6.11. Others

8.6.11.1. Market Trends and Opportunities

8.6.11.2. Growth Prospects

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

9.1. Major Players and Strategy Analysis

9.2. Market Share Analysis

9.3. Mergers, Acquisition, Agreements, and Collaborations

9.4. Competitive Dashboard

10. COMPANY PROFILES

10.1. IBM

10.2. Symantex

10.3. Check Point Software Technologies Ltd.

10.4. CyberAI

10.5. Flexxon Pte Ltd

10.6. Cisco


IBM

Symantex

Check Point Software Technologies Ltd.

CyberAI

Flexxon Pte Ltd

Cisco