The Global AI Based Data Security Market size is expected to reach $11.3 billion by 2031, rising at a market growth of 34.7% CAGR during the forecast period.
As the retail and e-commerce sector expands, robust AI-driven security measures become paramount to protect consumer trust and ensure the seamless operation of digital commerce platforms. AI-based security solutions safeguard customer information, secure payment data, and prevent fraudulent activities. Consequently, in 2023, the retail & e-commerce segment held 15% revenue share in the market. The exponential expansion of digital payment systems and online purchasing has resulted in heightened risks of data breaches and cyberattacks for retailers. These solutions enable retailers to monitor real-time transactions, detect anomalies, and promptly respond to potential threats.
The major strategies followed by the market participants are Product Launches as the key developmental strategy to keep pace with the changing demands of end users. For instance, In September, 2024, Oracle Corporation unveiled Oracle Intelligent Data Lake, a key feature of its Data Intelligence Platform. It will facilitate unified data management, integrating diverse data sources with advanced analytics and AI, enhancing decision-making while ensuring robust governance and security for organizations. Additionally, in October, 2024, Fortinet, Inc. unveiled FortiDLP, an advanced data loss prevention, and insider risk management solution. This AI-driven, cloud-native platform, integrated into Fortinet Security Fabric, consolidates data protection needs and enhances the company's DLP capabilities.
As the digital landscape evolves, businesses increasingly turn to AI for its capacity to handle large-scale, complex threats in real time. This automation level helps bridge the gap between the time threats are detected and the time it takes to respond, reducing vulnerabilities significantly. The growing emphasis on fast, automated responses to cyber threats is accelerating the demand for AI-based data security solutions. Hence, the need for real-time threat detection and automated responses to security incidents is a primary driver behind the adoption of AI in data security.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market Product Launches and Product Expansions.
The AI-Based Data Security Market is highly competitive, driven by the need for advanced protection against evolving cyber threats. Providers are focused on delivering AI-powered solutions that detect, predict, and respond to threats in real time, enhancing data security across digital platforms. As businesses increasingly rely on AI to manage sensitive data, competition centers on offering solutions that combine high accuracy with adaptability to emerging threats. Continuous advancements in machine learning and automation are essential for maintaining a competitive position in this critical market.
As the retail and e-commerce sector expands, robust AI-driven security measures become paramount to protect consumer trust and ensure the seamless operation of digital commerce platforms. AI-based security solutions safeguard customer information, secure payment data, and prevent fraudulent activities. Consequently, in 2023, the retail & e-commerce segment held 15% revenue share in the market. The exponential expansion of digital payment systems and online purchasing has resulted in heightened risks of data breaches and cyberattacks for retailers. These solutions enable retailers to monitor real-time transactions, detect anomalies, and promptly respond to potential threats.
The major strategies followed by the market participants are Product Launches as the key developmental strategy to keep pace with the changing demands of end users. For instance, In September, 2024, Oracle Corporation unveiled Oracle Intelligent Data Lake, a key feature of its Data Intelligence Platform. It will facilitate unified data management, integrating diverse data sources with advanced analytics and AI, enhancing decision-making while ensuring robust governance and security for organizations. Additionally, in October, 2024, Fortinet, Inc. unveiled FortiDLP, an advanced data loss prevention, and insider risk management solution. This AI-driven, cloud-native platform, integrated into Fortinet Security Fabric, consolidates data protection needs and enhances the company's DLP capabilities.
KBV Cardinal Matrix - Market Competition Analysis
Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation is the forerunner in the AI Based Data Security Market. In March, 2024, Microsoft Corporation unveiled the availability of Microsoft Copilot. This generative AI solution helps security professionals enhance efficiency and accuracy, processing over 78 trillion security signals daily. With support for eight languages, it enables faster response times and deeper insights, marking a significant advancement in security operations. Companies such as Cisco Systems, Inc., Oracle Corporation, and IBM Corporation are some of the key innovators in AI Based Data Security Market.
Market Growth Factors
Integrating AI into cloud security strategies also provides valuable insights into optimizing data security measures for diverse infrastructures. It ensures that cloud environments are protected, and data flows and transactions remain secure across hybrid or multi-cloud environments. As cloud adoption continues to rise, so does the opportunity for AI to play a pivotal role in securing complex data systems, which is essential for organizations aiming to maintain business continuity and meet data protection standards. In conclusion, the growing shift to cloud-based systems and big data analytics is a major driver for adopting AI-based data security solutions to safeguard vulnerable environments.As the digital landscape evolves, businesses increasingly turn to AI for its capacity to handle large-scale, complex threats in real time. This automation level helps bridge the gap between the time threats are detected and the time it takes to respond, reducing vulnerabilities significantly. The growing emphasis on fast, automated responses to cyber threats is accelerating the demand for AI-based data security solutions. Hence, the need for real-time threat detection and automated responses to security incidents is a primary driver behind the adoption of AI in data security.
Market Restraining Factors
The rapid pace of technological advancements in AI means that businesses must continually invest in upgrades to stay ahead of evolving threats. As AI technologies mature, it may become increasingly difficult for companies to keep up with the latest innovations without additional costs. Therefore, the high implementation and maintenance costs represent a significant barrier to adopting AI-based security solutions, particularly in organizations.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market Product Launches and Product Expansions.
Driving and Restraining Factors
Drivers
- Rising Cybersecurity Threats Increasing Demand for Advanced Security Solutions
- Need for Real-Time Threat Detection and Automated Response to Security Incidents
- Growing Adoption of Cloud-Based Systems and Big Data Leading to Increased Vulnerabilities
Restraints
- High Implementation and Maintenance Costs of AI-based Security Solutions
- Complexity in Integrating AI-based Security Solutions with Existing it Infrastructure
Opportunities
- Ai-Enhanced Security for Remote Work Environments and Distributed Networks
- Rise in Digital Transformation and the Need for Securing IoT Networks
Challenges
- Lack of Skilled Workforce and Expertise to Operate AI-based Security Solutions
- Privacy Concerns and Ethical Issues Around AI's Use in Monitoring and Data Protection
Security Type Outlook
Based on security type, the market is categorized into network security, endpoint security, application security, database security, cloud security, and others. The endpoint security segment witnessed 23% revenue share in the market in 2023. The rise in remote work and the proliferation of connected devices have heightened the need for advanced endpoint protection. AI-driven endpoint security solutions offer enhanced detection of malware, zero-day exploits, and other threats by analyzing vast amounts of endpoint data and identifying suspicious activities, thus ensuring comprehensive protection for devices such as laptops, smartphones, and IoT devices.Technology Outlook
On the basis of technology, the market is segmented into machine learning (ML), natural language processing (NLP), and context-aware computing. In 2023, the natural language processing (NLP) segment attained 23% revenue share in the security market. NLP technologies are crucial for analyzing and understanding human language, enabling the detection of phishing attempts, fraudulent communications, and other text-based threats. NLP's security application includes email filtering, sentiment analysis, and automated monitoring of textual data across various communication channels.Component Outlook
Based on component, the market is divided into software, hardware, and services. In 2023, the software segment garnered 48% revenue share in the AI based data security market. This significant share can be attributed to the increasing adoption of AI-driven software solutions designed to detect, prevent, and respond to cybersecurity threats in real time. These solutions are favored for their ability to analyze vast amounts of data, identify patterns indicative of security breaches, and provide automated responses to mitigate risks.
Deployment Type Outlook
By deployment type, the market is divided into cloud-based and on-premises. In 2023, the cloud-based segment registered 54% revenue share in the market. The increasing adoption of cloud services by businesses of all sizes has driven the demand for robust cloud-based security solutions. These solutions leverage AI to provide scalable, flexible, and efficient protection against cyber threats. The benefits of real-time threat detection, automated responses, and continuous monitoring make cloud-based AI data security attractive for organizations seeking to secure their cloud environments.Organization Size Outlook
Based on organization size, the market is divided into large enterprises and small and medium enterprises (SMEs). In 2023, the small and medium enterprises (SMEs) segment procured 37% revenue share in the AI based data security market. SMEs increasingly recognize the importance of data security as they become targets for cyberattacks. AI-based security solutions provide cost-effective, scalable options tailored to smaller organizations' unique needs.End-user Industry Outlook
By end-user industry, the market is segmented into BFSI, healthcare, retail & e-commerce, IT & telecom, government & defense, energy & utilities, and others. In 2023, the BFSI segment acquired 28% revenue share in the market. This significant share is attributed to the BFSI sector's critical need for robust data security solutions to protect sensitive financial information and ensure regulatory compliance. The increasing sophistication of cyber threats targeting financial institutions has driven the demand for advanced AI-based security measures.Regional Outlook
Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America region witnessed 38% revenue share in the market in 2023. The dominance of North America can be attributed to the early adoption of advanced technologies, a high concentration of leading AI and cybersecurity companies, and significant investments in R&D. The region's strong regulatory environment, which mandates stringent data protection measures, also drives the demand for AI-based data security solutions.Market Competition and Attributes
The AI-Based Data Security Market is highly competitive, driven by the need for advanced protection against evolving cyber threats. Providers are focused on delivering AI-powered solutions that detect, predict, and respond to threats in real time, enhancing data security across digital platforms. As businesses increasingly rely on AI to manage sensitive data, competition centers on offering solutions that combine high accuracy with adaptability to emerging threats. Continuous advancements in machine learning and automation are essential for maintaining a competitive position in this critical market.
Recent Strategies Deployed in the Market
- Oct-2024: Palo Alto Networks, Inc. teamed up with Deloitte to enhance access to AI-powered cybersecurity solutions for clients. This collaboration aims to streamline cybersecurity through platformization, addressing complex challenges and improving security outcomes by integrating advanced technologies and industry insights for enhanced operational efficiency.
- Oct-2024: Fortinet, Inc. unveiled Lacework FortiCNAPP, integrating its cloud-native application protection platform with the Fortinet Security Fabric. This solution enhances visibility and automates threat remediation, providing organizations with insights into emerging threats. Consolidating security tools, streamlines cloud security and improves the detection of cloud-native vulnerabilities through AI-driven analysis.
- Sep-2024: CrowdStrike Holdings, Inc. unveiled AI Security Posture Management (AI-SPM) and made Data Security Posture Management (DSPM) generally available, enhancing Falcon Cloud Security. These innovations provide comprehensive protection across cloud infrastructure and applications. Additionally, updates to Falcon Identity Protection enhance security against cross-domain attacks, addressing rising threats to cloud environments and AI services.
- Aug-2024: Fortinet, Inc. announced the acquisition of Next DLP, a data security firm to enhance its data loss prevention offerings. The integration will include Next DLP’s cloud-native. This acquisition will bolster their ability to manage insider risks and protect enterprises across various deployments.
- Jun-2024: Trend Micro announced a partnership with Nvidia, an American software company, to provide cybersecurity tools safeguarding private AI clouds, emphasizing data privacy, real-time analysis, and swift threat response.
List of Key Companies Profiled
- IBM Corporation
- Microsoft Corporation
- Cisco Systems, Inc.
- Oracle Corporation
- Palo Alto Networks, Inc.
- CrowdStrike Holdings, Inc.
- McAfee Corp.
- Trend Micro, Inc.
- Fortinet, Inc.
- Check Point Software Technologies Ltd.
Market Report Segmentation
By Organization Size
- Large Enterprises
- Small and Medium Enterprises (SMEs)
By Component
- Software
- Hardware
- Services
By Technology
- Machine Learning (ML)
- Natural Language Processing (NLP)
- Context-Aware Computing
By Deployment Type
- Cloud-Based
- On-Premises
By Security Type
- Network Security
- Endpoint Security
- Application Security
- Database Security
- Cloud Security & Others
By End-User Industry
- BFSI
- Healthcare
- Retail & E-commerce
- IT & Telecom
- Government & Defense
- Energy & Utilities
- Other End-User Industry
By Geography
- North America
- US
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
- LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market at a Glance
Chapter 3. Market Overview
Chapter 4. Competition Analysis - Global
Chapter 5. Global AI Based Data Security Market by Organization Size
Chapter 6. Global AI Based Data Security Market by Component
Chapter 7. Global AI Based Data Security Market by Technology
Chapter 8. Global AI Based Data Security Market by Deployment Type
Chapter 9. Global AI Based Data Security Market by Security Type
Chapter 10. Global AI Based Data Security Market by End-User Industry
Chapter 11. Global AI Based Data Security Market by Region
Chapter 12. Company Profiles
Companies Mentioned
- IBM Corporation
- Microsoft Corporation
- Cisco Systems, Inc.
- Oracle Corporation
- Palo Alto Networks, Inc.
- CrowdStrike Holdings, Inc.
- McAfee Corp.
- Trend Micro, Inc.
- Fortinet, Inc.
- Check Point Software Technologies Ltd.
Methodology
LOADING...
