What is AI for security?

Artificial intelligence (AI) security describes the tools and strategies that leverage AI to identify, prevent, and respond to emerging cyber threats.

Artificial intelligence has long been a sort of ‘Holy Grail’. The ability to create intelligent programs capable of learning from previous activity and applying insights towards solving complex problems has the capacity to revolutionize nearly every aspect of modern business. And AI for cybersecurity is no different.

By applying new advances in machine learning and natural language processing, businesses have the opportunity to identify and respond to threats with greater speed and ability. AI is a capability that can enhance other products—it hones the focus of prevention, detection, and response products, and provides options for prediction. The result is faster threat response and improved remediation.

One key advantage of AI for security is that it requires less human management than many other security options. AI makes sense to embrace in support of other products for key use cases. As the models mature and users become more confident in the technology (just as with automation), one can start to knit together individual tasks in an orchestrated sequence.

Modern security solutions are most effective with specific use cases, such as in uncovering and neutralizing phishing, spam, or opportunistic malware on endpoints with a high degree of confidence. As it does so, AI must be able to learn from these encounters, gathering observations and applying logical conclusions to improve its capabilities over time.

Core AI capabilities include the following:


You train artificial intelligence by feeding it large numbers of data artifacts to consume, both structured and unstructured. AI improves its knowledge to understand cybersecurity and risks through machine learning and deep learning techniques. Unstructured data (such as facial recognition and analysis of video and audio) is a promising area where AI may exceed human capabilities, and provide better tools than have traditionally been available.


Artificial intelligence gains insights, then reasons to identify relationships between different attributes. For example, AI might connect the dots between malicious files, insiders, or IP addresses and enrich findings with behavioral and historical insights. These analyses allow for exponentially quicker decisions as the AI gains more experiences from which to draw insights.


Organizations have the potential to optimize their automation efforts by combining them with AI advances. Automated processes collect vital data, and then AI runs the models. The end result is improved analytical insights.

AI security represents the next evolution in cyber defense, but is it essential? This can be a difficult question to answer definitively. What is apparent is that ongoing advances in malicious programming and other threats are making traditional cybersecurity a much more difficult prospect. In fact, today approximately 60% of organizations believe that they would be unable to identify critical threats without artificial intelligence technologies (source: Capgemini). Consider the following factors:

AI helps reinforce gaps in the cybersecurity workforce

The pace of digital transformation is accelerating world wide. Unfortunately, the availability of trained, experienced cybersecurity professionals is not keeping pace. Artificial intelligence can fill a talent gap that sees millions of unfilled cybersecurity jobs. It is also a scalable solution to use AI for security tools, as they augment the workflows of employees. At the same time, AI frees up valuable resources by reducing time to identify and triage threats. This allows workers to focus on more complex tasks, leaving simpler, more repetitive chores to automation.

AI promotes faster threat identification

Hunting down threats takes a great deal of time—single alert investigations can take days to complete. AI powered security tools are capable of triaging events, cutting down on time that is needed for incident response.

AI allows businesses to counter threat escalation

While some organizations have been slow to adopt the newest advancements in digital security, it’s clear that threat actors are showing no such hesitancy. Microsoft reports that “threat actors have rapidly increased in sophistication over the past year, using techniques that make them harder to spot and that threaten even the savviest targets” (source: Microsoft). AI for security empowers organizations with the technology they need to outpace this trend.

Incident triage and analysis are necessities during the response process to eliminate false positives and determine how to contain and remediate incidents. Many companies use threat intelligence feeds as a part of their response process, and correlating the information automatically while leveraging enrichment from other tools can reduce the time spent on analysis. AI improves these processes by processing orders of magnitude more data in less time, and increasing the types of context, prediction, and historical insight that can be included.

AI is more than some nebulous, blanket solution to improve security stances across industries; it’s a solution that improves effectiveness within teams and departments. This includes the following:

Threat exposure

Threat actors remain viable by constantly improving and refining their tactics, techniques, and procedures. AI provides cybersecurity systems with up-to-date and relevant knowledge of industry-specific and global threats, which help teams make critical decisions about priorities based on what attack strategies may be used against a company.

Incident response

AI systems provide context for response and prioritization to security alerts, fast incident responses, and root-cause analysis to mitigate vulnerabilities while analyzing how to prevent a recurrence of such issues.

Breach risk prediction

AI systems predict how an organization is likely to be breached. This allows the organization to better plan for resource allocation, mitigating weaknesses in the process. Prescriptive insights taken from AI analysis help improve configuration and enhancement controls to more optimize cyber resilience.

39% of breach victims knew they were vulnerable before they were breached.

Controls effectiveness

Organizations should understand the various security processes and tools they have employed, and the subsequent impact of those processes and tools on their security posture. AI has the potential to improve evaluation of control-monitoring data, along with assisting with the analysis of strengths and gaps in tool and process coverage.

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