The research provides a global and regional analysis and valuation of the Artificial Intelligence-Based Security market. The study provides an in-depth analysis of the industry’s competitive landscape, constraints, sales forecasts, opportunities, present and developing trends, and industry-validated market data. The research includes historical data from 2016 to 2019 and a forecast for the period 2020 to 2026. (USD Billion).
The global Artificial Intelligence-Based Security market, which was valued at approximately 5.1 (USD Billion) in 2019 and is expected to generate revenues of 14.2 (USD Billion) by 2026, is expected to grow at a nearly 17.91 percent compound annual growth rate between 2020 and 2026.
How Artificial intelligence Described ?
Artificial intelligence is described as the ability for machines to perform “clever” or “intelligent” tasks without the need for human intervention. As a result, AI security entails using AI to detect and eliminate cyber threats with less human intervention than is normally expected or required with traditional security approaches.
When comparing the behaviour of entities throughout an environment to those in a comparable environment, Artificial intelligence based security solutions are frequently used to classify “good” against “bad.” This procedure allows the system to detect and flag changes automatically. Unsupervised learning, often known as “pattern of life” learning, produces a huge number of false positives and negatives. More advanced AI security solutions can go beyond merely identifying good or bad behaviour by analysing large volumes of data and assisting in the piecing together of connected activities that may suggest suspicious behaviour. In this approach, AI security works in the same way as the greatest and most talented human analyst.

AI Security Aids in the Saving of Time Spent Hunting for Threats
Aside from the rising talent gap, it’s apparent that current security analysts are having a hard time finding the time they need to discover new risks. In a recent SANS Institute SOC survey, respondents admitted to using time- and resource-intensive approaches for threat hunting, which can lead to alert fatigue. The ramifications of which can be disastrous:
- A single alarm inquiry can take hours or even days, according to 73% of respondents.
- To get to the bottom of an investigation, 53% indicated they employ three or more data sources.
- Critical notifications are claimed to go completely uninvestigated by 54% of respondents.
- 30 % of their prioritised warnings are never explored.
This is due in part to the fact that the majority of event correlation in SIEM and big data products is still done manually. In contrast, AI security technologies are capable of automatically correlating and triaging events, reducing the time required for incident response and cleanup.
According to the Capgemini Research Institute’s recent cybersecurity with AI paper, AI decreases the cost of detecting and responding to breaches by up to 12 percent and reduces the overall time taken to detect threats and breaches by up to 64 percent.
The Awake Advantage
The initial wave of approaches to AI security behavioural analytics focused on baselines to construct a “pattern of life.” By relying solely on unsupervised learning to detect abnormal activity, these outdated systems create a large number of warnings, the most of which are false positives, while also ignoring dangers. Awake, on the other hand, was ranked first in terms of time to value because to its frictionless approach that offers answers rather than notifications.
Artificial Intelligence Based Security Market Outlook 2020-2026
Artificial intelligence can perform tasks such as speech recognition, language translation, visual perception, and decision making that are similar to those performed by human intelligence. The convergence of cybersecurity, artificial intelligence, and physical security has sparked interest, resulting in new security tools. As a result, there is a greater demand for smart security solutions, boosting the appeal of AI-based security systems in a variety of industries. With the Internet of Things (IoT) becoming more common, the market for artificial intelligence-based security is expected to grow in the future years.
Growth Dynamics for Artificial Intelligence Based Security Market
Over the projection period, an increase in the number of connected devices will drive the growth of the artificial intelligence-based security business. Furthermore, the use of artificial intelligence in security systems is expected to improve system accuracy and the ability to detect potential threats to any security system. As a result, the employment of AI tools in security systems will become more widespread, as it will strengthen security. Over the assessment period, the growing threat of cyber security threats and hacking, which result in massive data losses as well as financial losses for businesses, will generate profitable growth avenues for the artificial intelligence-based security industry. Furthermore, the necessity to improve the security of banking services and financial institutions would expand the size of the artificial intelligence-based security industry over the forecasted timeframe.
Furthermore, the requirement to provide robust security to eCommerce websites in order to ensure secure transactions is expected to drive massive growth in the artificial intelligence-based security market over the projection period. The need to protect defence systems from external attacks as well as malware attacks – a core domain and important area of concern for national security – will aid the market in traversing and charting a new route of growth over the next few years. Fintech companies use blockchain technology, which necessitates a high level of security, and AI is the best viable alternative for these companies. Over the projection timeframe, it appears that the rise in identity and data thefts, as well as the requirement for strong security solutions for conducting business and other financial operations, will result in massive business growth.