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The artificial intelligence in security market size is forecast to increase by USD 25.47 billion at a CAGR of 34.73% between 2023 and 2028.
The artificial intelligence in security industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD billion" for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.
Artificial Intelligence (AI) is revolutionizing the security market, particularly in areas such as Network Security, Application Security, Cloud Security, and Threat Detection. AI-powered systems are increasingly being used to mitigate malicious activities, including cyberattacks, breaches, and vulnerabilities. AI is also transforming industries like Healthcare, Manufacturing, and the Automotive and Transportation sectors, securing electronic health records, medical imaging data, wearable device data, and cloud-based services. AI solutions provide advanced analytics, neural networks, and continuous monitoring to strengthen cybersecurity posture and protect against cyber dangers.

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The on-premise segment was valued at USD 2.75 billion in 2018 and showed a gradual increase 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 AI in security market in North America is experiencing significant growth due to the increasing number of cyberattacks and the subsequent demand for advanced security solutions. Key industries, including retail, BFSI, manufacturing, and healthcare, are major contributors to this market in North America, particularly In the US, Canada, and Mexico. The rise of technological advances and the Internet of Things (IoT) has resulted in an influx of security-related data. AI-powered systems are increasingly being adopted to analyze this data, detect threats, and enhance cybersecurity posture. Threats, such as malicious activities, breaches, and vulnerabilities, pose significant risks to connected enterprises.
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 advantage.
Rapid increase in the use of mobile and other connected devices is the key driver of the market.
Increasing demand for cloud-based applications is the upcoming market trend.
Technical difficulties in developing AI technologies is a key challenge affecting the industry growth.
The artificial intelligence in security 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 artificial intelligence in security market report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their market growth analysis strategies.
Customer Landscape
Companies are implementing various strategies, such as strategic alliances, artificial intelligence in security market forecast, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the industry.
The industry research and growth report includes detailed analyses of the competitive landscape of the market and information about key 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 industry 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.
Artificial Intelligence (AI) is revolutionizing the security market by enhancing threat detection and response capabilities for various sectors. Network security, application security, and cloud security are among the areas experiencing significant advancements due to AI's ability to analyze vast amounts of data and identify patterns indicative of malicious activities. AI-powered systems are increasingly being adopted by both professional and managed security services to strengthen cybersecurity postures. These systems employ machine learning algorithms to analyze data from networks, applications, and cloud services in real-time. They can detect anomalies and vulnerabilities that might go unnoticed by traditional security tools, enabling proactive threat mitigation.
In addition, the integration of AI in security solutions is crucial for connected enterprises in industries such as government and defense, manufacturing, healthcare, automotive and transportation, and others. AI's threat detection capabilities are essential in mitigating cyber dangers, including data breaches, phishing attempts, ransomware related activities, and insider attacks. The healthcare sector, in particular, benefits significantly from AI's capabilities in securing electronic health records, medical imaging data, and wearable device data. AI can analyze these data types to identify anomalous behavior and potential threats, ensuring the protection of sensitive patient information. Cloud-based services are increasingly becoming the target of cybercriminals, necessitating strong cybersecurity measures.
Furthermore, AI's role in cloud security is vital in threat intelligence, online transactions, and NEFT/mobile commerce In the banking sector. AI-powered systems can analyze patterns in large datasets to identify potential threats, enabling quick response times and minimizing manual errors. Advanced security solutions employing AI and machine learning are becoming the norm as digital transformation initiatives continue to disrupt traditional business models. These solutions offer intelligent security systems that can learn from threats and adapt to new vulnerabilities. They also enable collaborative threat intelligence, automated incident response, and compliance management, ensuring customer data protection and continuous monitoring. The adoption of AI in security is a response to the increasing sophistication of cyber threats.
In addition, cybercriminals employ various tactics, including political rivalry, monetary gain, reputational harm, and radical religious organizations, to exploit vulnerabilities. AI's ability to analyze data and learn from threats makes it an essential component of any organization's cybersecurity strategy. Its ability to analyze vast amounts of data and identify patterns indicative of malicious activities makes it an essential component of any organization's cybersecurity strategy. The integration of AI in security solutions is a response to the increasing sophistication of cyber threats and the need for proactive threat mitigation.
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Market Scope |
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Report Coverage |
Details |
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Page number |
144 |
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Base year |
2023 |
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Historic period |
2018-2022 |
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Forecast period |
2024-2028 |
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Growth momentum & CAGR |
Accelerate at a CAGR of 34.73% |
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Market growth 2024-2028 |
USD 25.47 billion |
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Market structure |
Fragmented |
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YoY growth 2023-2024(%) |
25.9 |
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Key countries |
US, China, UK, Germany, and Japan |
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Competitive landscape |
Leading Companies, market growth and forecasting, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
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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 Deployment
7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Opportunity/Restraints
10 Competitive Landscape
11 Competitive Analysis
12 Appendix
Research Framework
Technavio presents a detailed picture of the market by way of study, synthesis, and summation of data from multiple sources. The analysts have presented the various facets of the market with a particular focus on identifying the key industry influencers. The data thus presented is comprehensive, reliable, and the result of extensive research, both primary and secondary.
INFORMATION SOURCES
Primary sources
Secondary sources
DATA ANALYSIS
Data Synthesis
Data Validation
REPORT WRITING
Qualitative
Quantitative
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