Artificial Intelligence-Based Cybersecurity Market Analysis APAC, North America, Europe, South America, Middle East and Africa - US, China, UK, Japan, Germany - Size and Forecast 2024-2028

Artificial Intelligence-Based Cybersecurity Market Size 2024-2028

The artificial intelligence-based cybersecurity market size is forecast to increase by USD 58.22 billion at a CAGR of 31.89% between 2023 and 2028.

• The market is experiencing vital growth, driven by several key factors. A significant contributor is the rapid proliferation of mobile and connected devices, which has created an expansive attack surface for cyber threats. Moreover, stringent regulatory compliance requirements are compelling organizations to invest in advanced cybersecurity solutions powered by artificial intelligence (AI) to protect sensitive data and ensure regulatory adherence.
• Rising demand for cloud-based applications highlights the need for AI-driven cybersecurity solutions to protect cloud environments from advanced cyberattacks. This market trends and analysis report explores key drivers, trends, and challenges, along with a market forecast supported by historical data from 2018 to 2022.

Artificial Intelligence-Based Cybersecurity Market Analysis

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How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD million" for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

• End-user
  • BFSI
  • Government
  • ICT
  • Healthcare
  • Others
• Deployment
  • Cloud
  • On-premises
• Geography
  • APAC
    • China
    • Japan
  • North America
    • US
  • Europe
    • Germany
    • UK
  • South America
  • Middle East and Africa

By End-user Insights

The BFSI segment is estimated to witness significant growth during the forecast period.In the financial services sector, safeguarding customer data is of utmost importance. With the rise of digital transactions, the risk of cyberattacks has grown significantly. To mitigate these threats, BFSI companies are turning to Artificial Intelligence (AI) technology for advanced cybersecurity solutions. AI-based systems can effectively identify and respond to potential threats in real-time, enhancing the overall security of company assets, which include both physical data and electronic devices. The Internet of Things (IoT) and IT systems in the BFSI sector generate vast amounts of data through data communication and interchange. AI solutions, such as Machine Learning (ML) and Deep Learning (DL), can analyze this data to detect anomalies and potential threats, ensuring the security of digital assets.

Endpoint solutions, which use AI to secure individual devices, are also gaining popularity in the sector. Regulations like the Sarbanes-Oxley Act of 2002 mandate financial organizations to implement cybersecurity measures to prevent data breaches. AI-based cybersecurity solutions are becoming essential for compliance, as they can provide real-time threat detection and response. Furthermore, the adoption of industrial communication protocols like MTConnect, EtherCAT, and MDIS in the BFSI sector necessitates advanced cybersecurity solutions to secure data interchange between systems. In conclusion, the BFSI sector's increasing reliance on digital transactions and data interchange necessitates advanced cybersecurity measures. AI-based cybersecurity solutions offer real-time threat detection and response, ensuring the confidentiality and integrity of customer data. Regulatory compliance and the need for secure data interchange further highlight the importance of investing in these solutions.

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The BFSI segment was valued at USD 3.15 billion in 2018 and showed a gradual increase during the forecast period.

Will APAC become the largest contributor to the Artificial Intelligence-Based Cybersecurity Market?-

APAC is estimated to contribute 47% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The market for cybersecurity solutions utilizing Artificial Intelligence (AI) and Machine Learning (ML) in the Asia Pacific (APAC) region is projected to expand at a significant pace. This growth can be attributed to the burgeoning IT sector, particularly in countries such as China, Japan, and South Korea. In China, the increasing number of startups, supportive government initiatives, and expansion of the government and financial services sector (BFSI) are driving the adoption of AI-based cybersecurity solutions. With a population of nearly 1.4 billion people, China represents a vast market for AI cybersecurity providers. Japan and South Korea also contribute significantly to the market due to their advanced IT infrastructure and emphasis on security.

Moreover, the key areas of focus include cloud security, zero-trust architecture, and endpoint security within the services segment. ML technology, including Deep Learning (DL), is essential for real-time security solutions against alarming statistics of cyberattacks targeting individuals, enterprises, and governments. Advanced technologies, such as AI and ML, are integral to automation trends and smart data utilization in cybersecurity processes. Technological advancements and digital transformation initiatives are driving the adoption of AI-based cybersecurity solutions to counteract political rivalry, financial gain, and damaging reputations through cyberattacks on networks, endpoints, and data. Hence, such factors are driving the market in APAC during the forecast period.

Our researchers analyzed the data with 2023 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive edge advantage.

Market Dynamics

• Artificial Intelligence (AI) in Cybersecurity: Market Trends and Technological Advancements Artificial Intelligence (AI) has emerged as a game-changer in the cybersecurity landscape, revolutionizing the way organizations protect their digital assets. AI technologies, including Machine Learning (ML) and Deep Learning (DL), are increasingly being adopted to enhance cybersecurity processes and counteract advanced threats. The integration of AI in cybersecurity solutions has significantly impacted various segments, such as cloud security, network security, and endpoint security. AI-powered cybersecurity solutions enable real-time threat detection and response, ensuring the security of critical data and infrastructure. One of the primary applications of AI in cybersecurity is the use of ML algorithms in behavioral biometrics.
• This technology analyzes user behavior patterns to detect anomalous activities and potential cyber threats. Behavioral biometrics is particularly effective in the Fintech sector, where the handling of sensitive financial data requires stringent security measures. Another area where AI is making a significant impact is in cloud solutions. Zero-trust architecture, an advanced security approach, is being enhanced by AI to provide continuous verification of user identity and access. AI-powered cloud security solutions offer real-time threat detection and response, ensuring the security of data in the cloud. The services segment is also witnessing a wave in AI adoption. Security operations centers (SOCs) are increasingly leveraging AI technologies to automate routine tasks, freeing up resources for more complex security issues.
• AI-powered security solutions enable smart data utilization, enabling organizations to make informed decisions based on real-time threat intelligence. The adoption of AI in cybersecurity is driven by technological advancements and digital transformation initiatives. Organizations are recognizing the need for advanced security solutions to counteract the alarming statistics of cyberattacks. According to recent reports, the number of cyberattacks increased by 30% in the last year alone. AI-powered security solutions offer real-time threat detection and response, ensuring organizations are better prepared to mitigate cyber threats. In conclusion, AI is transforming the cybersecurity market by enabling real-time threat detection and response, enhancing security processes, and automating routine tasks.
• The integration of AI in cybersecurity solutions is particularly effective in cloud security, network security, and endpoint security. As the threat landscape continues to evolve, the adoption of AI in cybersecurity is expected to grow, ensuring organizations are better equipped to protect their digital assets.

What are the key market drivers leading to the rise in adoption of Artificial Intelligence-Based Cybersecurity Market ?

The rapid increase in the use of mobile and other connected devices is notably driving market growth.

• With the advent of AI, machine learning, and high-end data networks, the sales volume of connected devices, including routers, tablets, and smartwatches, is increasing. IoT devices have a security system that is vulnerable to cyberattacks. It is not designed to pre-detect or prevent threats, such as hacking. Thus, these devices could be prime targets for hackers to obtain usernames and passwords and access other confidential information.
• AI risk management plays a critical role in securing the information on these devices. AI-based cybersecurity, when implemented on IoT devices, will help users get a predetermined notification regarding threats. This will help them avoid cyber threats and attacks. Therefore, the increasing adoption of IoT devices will likely be a major driver for the market during the forecast period.

What are the trends shaping the Artificial Intelligence-Based Cybersecurity Market?

The implementation of cloud-based services is an emerging trend in the market.

• Cloud-based services are adopted for purposes such as authentication, video management systems, and storing biometric information. As banks and hospitals store large volumes of confidential data in the cloud, it is important to secure the data from unauthorized access. The flexibility and scalability of cloud-based security solutions accommodate the varying needs of consumers, which is a reason for their increased adoption.
• With the increased employee mobility, a number of organizations have implemented cloud-based services for business functions, such as customer relationship management (CRM), payroll, and enterprise communication, to ensure remote access to data. The need to protect the information stored in the cloud is increasing, which is leading to a greater demand for security solutions. Furthermore, governments worldwide are also implementing stringent regulations, such as the Payment Card Industry Data Security Standard (PCI DSS) Act and HIPAA, to enforce data security for banking and healthcare organizations. Therefore, these factors will drive the market growth and trends during the forecast period.

What challenges does Artificial Intelligence-Based Cybersecurity Market face during the growth?

The high cost of deployment is a key challenge affecting the market growth.

• The global market for artificial intelligence (AI) in cybersecurity is confronted with significant expenses associated with implementing and maintaining cybersecurity solutions for individuals, enterprises, and governments. The total investment required includes software licensing fees, system design and customization, implementation, employee training, and ongoing maintenance. Hiring IT personnel to oversee the implementation and managing in-house IT administration staff for on-premises cybersecurity solutions adds to the financial burden.
• Moreover, there are hidden costs involved in gaining a comprehensive understanding of the AI cybersecurity solution's functionality through knowledge acquisition, experience, and skill development. The escalating number of cyberattacks, including ransomware attacks like WannaCry, and the potential financial losses, reputational damage, and political rivalry resulting from these attacks, necessitate the deployment of advanced cybersecurity solutions. However, the high implementation costs remain a significant barrier to entry for many organizations.

Exclusive Customer Landscape

The market forecasting report includes the adoption lifecycle of the market, covering from the innovator's stage to the laggard's stage. It focuses on adoption rates in different regions based on penetration. Furthermore, the report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their market growth analysis strategies.

Customer Landscape

Key Companies & Market Insights

Companies are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.

Check Point Software Technologies Ltd. - The key offerings of the company include artificial intelligence-based cybersecurity.

The market research and growth report includes detailed analyses of the competitive landscape of the market and information about key companies, including:

• Amazon.com Inc.
• AO Kaspersky Lab
• BlackBerry Ltd.
• Broadcom Inc.
• Cisco Systems Inc.
• CrowdStrike Inc.
• Dell Technologies Inc.
• Fortinet Inc.
• Hewlett Packard Enterprise Co.
• Intel Corp.
• International Business Machines Corp.
• Juniper Networks Inc.
• LogRhythm Inc.
• Mahindra and Mahindra Ltd.
• Micron Technology Inc.
• NVIDIA Corp.
• S.C. BITDEFENDER S.R.L.
• Securonix Inc.
• Vectra AI Inc.

Qualitative and quantitative analysis of companies has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key market players. Data is qualitatively analyzed to categorize companies as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize companies as dominant, leading, strong, tentative, and weak.

Research Analyst Overview

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing the cybersecurity landscape, with Cyber AI emerging as a key area of focus. Behavioral biometrics, ML algorithms, and deep learning (DL) technology are at the heart of this revolution, providing advanced capabilities for detecting and responding to cyber threats. The financial sector is a major adopter of these advanced technologies, with cloud security and zero-trust architecture being key areas of investment. The network security segment and endpoint security are also seeing significant growth, as organizations seek to protect their IT systems and digital assets from evolving cyber threats. The services segment is also witnessing a in demand for AI-driven security solutions, as organizations look to automate their security operations and improve their cybersecurity processes.

Moreover, ML technology is being used to analyze vast amounts of data in real-time, enabling organizations to respond quickly and effectively to security incidents. Advanced technologies such as AI, ML, and DL are being used to detect and respond to a range of cyber threats, including ransomware, phishing attempts, malicious browser ads, crypto mining, and insider threats. Cyberattacks, driven by political rivalry and financial gain, continue to pose a significant risk to individuals, enterprises, and governments, resulting in substantial financial losses and damaging reputations. The use of AI in cybersecurity is not just about threat detection and response, but also about smart data utilization, fraud detection, risk management, secure user authentication, and compliance management.

With the increasing digital transformation initiatives, real-time security solutions are becoming increasingly important for customer data protection and advanced encryption. Anomaly detection, continuous monitoring, data loss prevention, and predictive analysis are some of the advanced capabilities that AI is bringing to the cybersecurity table. With the increasing use of IoT and IT systems, endpoint solutions are also becoming crucial for securing data communication and data interchange protocols such as MTConnect, EtherCAT, and MDIS. In conclusion, AI and ML are transforming the cybersecurity landscape, providing advanced capabilities for detecting and responding to cyber threats. The financial sector is a major adopter of these technologies, with cloud solutions and endpoint security being key areas of investment.

Furthermore, organizations are looking to automate their security operations and improve their cybersecurity processes, and AI is providing the advanced capabilities needed to meet these challenges. The use of AI in cybersecurity is not just about threat detection and response, but also about smart data utilization, fraud detection, risk management, and compliance management. With the increasing digital transformation initiatives, real-time security solutions are becoming increasingly important for customer data protection and advanced encryption. The evolving cyber threats require continuous monitoring and advanced algorithms, behavioral analysis, and predictive analysis to stay ahead of the curve.

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What are the Key Data Covered in this Market Research and Growth Report?

• CAGR of the market during the forecast period
• Detailed information on factors that will drive the market growth and forecasting between 2024 and 2028
• Precise estimation of the size of the market and its contribution of the market in focus to the parent market
• Accurate predictions about upcoming market growth and trends and changes in consumer behaviour
• Growth of the market across APAC, North America, Europe, South America, and Middle East and Africa
• Thorough analysis of the market's competitive landscape and detailed information about companies
• Comprehensive analysis of factors that will challenge the growth of market companies

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