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The artificial intelligence-based cybersecurity market size is estimated to grow by USD 58.23 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. Furthermore, the increasing demand for cloud-based applications underscores the need for AI-driven cybersecurity solutions to safeguard cloud environments against sophisticated cyberattacks. This market trends and analysis report includes an in-depth analysis of drivers, trends, and challenges. Furthermore, the market forecasting report includes historic market data from 2018 to 2022.
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Artificial Intelligence (AI) and Machine Learning (ML), two pivotal technologies, are revolutionizing the Cybersecurity sector. The market is witnessing significant growth with the integration of AI and ML. The Machin Learning algorithms enable Cybersecurity solutions to learn from past threats and identify new ones, thereby enhancing security measures. The use of AI in Cybersecurity is not limited to threat detection but also extends to Behavioral Biometrics for user authentication and Secure Access. The Cloud Security sector is also leveraging AI for real-time threat detection and response. Fintech companies are adopting AI Cybersecurity to secure their financial transactions and customer data. The Cybersecurity market size is expected to grow significantly in the coming years, driven by the increasing number of cyber-attacks and the need for advanced security solutions. The deployment of AI and ML in Cybersecurity is a game-changer, offering Secure and Finetech companies a competitive edge. The future of Cybersecurity lies in the integration of AI and ML, offering proactive and intelligent security solutions.
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.
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 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.
The high cost of deployment is a major challenge impeding market growth. One of the major challenges for the global market is the high deployment cost of cybersecurity solutions. The total installation cost includes the cost of software licensing, system designing and customization, implementation, training, and maintenance for an individual organization. Furthermore, an organization must recruit specialized staff, for proper implementation of the cyber security software, which incurs additional costs.
Furthermore, the maintenance of on-premises cyber security solutions requires in-house IT administration staff to manage and control issues, which would result in high implementation costs. Moreover, these solutions contain additional costs, such as costs involved in providing knowledge, experience, and skill development of the solution to understand its functionality. Thus, the high cost of deployment will impede the growth of the market in focus during the forecast period.
The market growth analysis 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 market research and growth report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their growth strategies.
Customer Landscape
The BFSI and fintech sectors, handling sensitive financial data, prioritize maintaining confidentiality amidst the wave in online transactions and resulting cybersecurity threats. AI and Machine Learning (ML) technologies, specifically Cyber AI, are increasingly adopted for advanced threat detection. Behavioral biometrics and ML algorithms identify anomalous patterns, enhancing security operations. Regulations like the Sarbanes Oxley Act drive this trend. The Media & Entertainment industry and Network security segment also leverage AI for cloud security and zero-trust architecture. Endpoint security in the Services segment benefits from ML technology and Deep Learning. Advanced technologies, automation, and smart data utilization are key to real-time security solutions. Alarming statistics reveal cyberattacks causing significant financial losses for individuals, enterprises, and governments, emphasizing the need for vital cybersecurity processes. Technological advancements and digital transformation initiatives underscore the importance of AI and ML in cybersecurity solutions, providing real-time protection against cyber threats driven by political rivalry or financial gain, damaging reputations.
The market share growth by the BFSI segment will be significant during the forecast period. The BFSI sector deals with the financial information of customers. The advent of new technologies has led to an increase in the number of online transactions, thus making data vulnerable to cyberattacks. Thus, it is important to maintain the confidentiality of this data.
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The BFSI segment was valued at USD 3.16 billion in 2018. The BFSI sector is investing heavily in AI-based cybersecurity solutions to identify and detect the sources of threats. Several regulations are also compelling financial organizations to adopt cybersecurity solutions to prevent data theft. Furthermore, with the increased use of mobile devices, the adoption of mobile banking is rising among end-users. This is also increasing the need for cybersecurity solutions. The primary drivers that contribute to the large market share and high growth of this segment include the increasing adoption of AI-enabled technology for operational efficiency and the generation of data due to digitalization. Moreover, the financial sector is expected to focus on the improvement of customer services and superior workflow automation of core and allied activities, such as deposits, lending, leasing, and regulatory compliance. This will also likely lead to an increase in the deployment of AI-based security solutions across the segment. Therefore, the abovementioned factors will drive segment growth during the forecast period.
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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. The Artificial Intelligence (AI) and Machine Learning (ML) driven Cyber AI market in APAC is experiencing significant growth, particularly in China, Japan, and South Korea. This expansion is attributed to the IT sector's rapid advancement, including the BFSI and fintech sectors, which utilize AI-based cybersecurity solutions like behavioral biometrics and ML algorithms. 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.
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 growth and forecasting report also includes detailed analyses of the competitive landscape of the market and information about 15 market companies, including:
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.
The market forecast report provides comprehensive data (region wise segment analysis), with forecasts and estimates in "USD Billion" for the period 2024 to 2028, as well as historical data from 2018 to 2022 for the following segments
Artificial Intelligence (AI) is revolutionizing the cybersecurity landscape by providing advanced threat detection and response capabilities. The market is experiencing significant growth due to the increasing number of cyber threats and the need for more effective security solutions. Machine Learning (ML) and Deep Learning (DL) algorithms are being used to analyze large data sets and identify patterns, enabling the detection of previously unknown threats. Cybersecurity companies like (AI), (ML), and (CLoud Security) are leveraging AI to offer predictive threat analysis, automate security processes, and enhance network security. Behavioural analytics is another area where AI is making a difference, helping to detect anomalous user activity and prevent insider threats. The future of cybersecurity lies in the integration of AI, ML, and DL to create intelligent security systems that can adapt to evolving threats and protect against advanced attacks.
The market is witnessing exponential growth, driven by advancements in technologies like Natural Language Processing (NLP) and the increasing sophistication of Fintech sector operations. The market landscape depends on the advanced encryption, anomaly detection, continuous monitoring, data loss prevention, advanced algorithms, behavioural analysis, predictive analysis, DLP solutions, sensitive information, security incidents, evolving cyber threats, overall data protection measures. As cyber threats evolve, the demand for solutions capable of combating Distributed Denial of Service (DDoS) attacks is on the rise, leading to the development of innovative defenses powered by Artificial Neural Networks (ANN). Organizations, guided by reports from institutions like the Center for Strategic and International Studies (CSIS), are investing in Fraud detection/anti-fraud segment solutions and Unified Threat Management (UTM) platforms to bolster their cybersecurity posture. Additionally, the adoption of cloud solutions is offering scalable and cost-effective options for safeguarding digital assets against emerging threats.
Market Scope |
|
Report Coverage |
Details |
Page number |
185 |
Base year |
2023 |
Historic period |
2018 - 2022 |
Forecast period |
2024-2028 |
Growth momentum & CAGR |
Accelerate at a CAGR of 31.89% |
Market Growth 2024-2028 |
USD 58.23 billion |
Market structure |
Fragmented |
YoY growth 2023-2024(%) |
22.19 |
Regional analysis |
APAC, North America, Europe, South America, and Middle East and Africa |
Performing market contribution |
APAC at 47% |
Key countries |
US, China, UK, Japan, and Germany |
Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
Key companies profiled |
Amazon.com Inc., AO Kaspersky Lab, BlackBerry Ltd., Broadcom Inc., Check Point Software Technologies Ltd., 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., and Vectra AI Inc. |
Market dynamics |
Parent market analysis, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and recovery analysis and future consumer dynamics, Market condition analysis for forecast period |
Customization purview |
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1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation by End-user
7 Market Segmentation by Deployment
8 Customer Landscape
9 Geographic Landscape
10 Drivers, Challenges, and Opportunity/Restraints
11 Competitive Landscape
12 Competitive Analysis
13 Appendix
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