6 Ways AI in Cybersecurity Can Help Strengthen Your Defences

As part of the study, we observed six potential use cases for AI in cybersecurity. In this blog, you’ll learn about the top use cases for meaningfully adopting AI into your security workflows.

While not all cyberattacks cause damage, there has been an increase in successful cyberattacks noted by the respondents to our survey. This signals a need for faster and earlier detection of cyberthreats.   

Key insights

• In 2023, 7 to 8 percent of all cyberattacks became cyberincidents; in the 2024 study, this increased to 9 to 10 percent across industries
• 61.3 percent of organizations said they use AI/ML for endpoint threat detection and response 
• 37.8 percent of organizations enhance their network monitoring and anomaly detection with AI

Modern AI applications can minimize the time it takes to detect a security incident after it has already begun. AI-powered detection tools can refer to a large historical dataset of cyberincidents, which lets them identify threats with greater accuracy and speed. 

This means security teams can catch threats before they cause damage and have more time to remediate the incident. It not only aims to reduce the likelihood of damage but also lower the number of successful cyberattacks.

“When it comes to dealing with a threat that’s already inside your IT environment, how fast you remediate makes a huge difference. AI-assisted detection significantly raises a security team’s potential of preventing long-term damage,” said Michael Traves, Principal Field Solution Architect for AI and DevOps at CDW.  

AI systems can be designed to respond to several types of threats autonomously with minimal human intervention. This could be quite beneficial in cases where early detection must be followed by a quick response to avoid significant downtime or extended data loss.

Such use cases are still limited, but as AI adoption grows, we expect more organizations to prioritize automated incident response. 

Key insights

• Smaller organizations reported a sharp increase in downtime due to DoS attacks at 18 days, compared with 12 days in the 2023 study
• 63.8 percent of organizations believe AI can help them accelerate incident response times
• 39 percent of organizations reportedly enhance their automated threat investigation and response with AI

Just like AI systems predict the presence of a threat, they can also come up with the right remediation measures. It could be something as simple as changing a firewall rule or removing network access once a bad actor is identified.

For instance, when dealing with repetitive DoS attacks that can bring business functions to a halt, automated response could play a crucial role. It could detect and divert the onset of a DoS attack in real time, to ensure minimal downtime. 

“In an age where customers expect instant access to information, downtimes can seriously affect brand loyalty and business. If your website goes down, customers jump to the next option, never to return,” said Ivo Wiens, Field CTO for Security Solutions Architecture at CDW Canada.

“Therefore, organizations can leverage advanced threat detection offered by AI systems to possibly keep the downtime caused by DoS and other cyberattacks to a bare minimum.”

The risk of internal threats, data loss and access manipulation attempts have led organizations to adopt the zero-trust model. But organizations may still face vulnerabilities in the absence of threat detection.

Behavioural analysis coupled with proactive threat detection and response can help organizations maximize the value of their zero-trust security strategy.

Key insights

• Less than one third of organizations have a policy that mandates security monitoring for threat detection
• 47.7 percent of organizations use AI for enhancing user behaviour analysis and insider threat detection
• 33.7 percent of organizations stated that AI helps them improve detection of insider threats

AI-powered behavioural analysis can check for when organizational users, whether external or internal, act in anomalous ways. For instance, a cyberattacker moving laterally in a system with compromised credentials may not be automatically perceived as a threat. But with AI analysis, this kind of behaviour has a higher likelihood of raising suspicion.

This helps security teams build access architectures that are resilient to threats. It could significantly improve the efficacy of zero-trust security and help achieve long-term security objectives.

“The majority of recent threats and attacks are being detected on the endpoint and whether they're taking advantage of vulnerabilities or unsuspecting users, a key area to detect these kinds of threats is on the endpoint,” Wiens remarked.

“The use of AI-led behaviour analysis and detection will be key in the AI arms race we’re entering with cyberattackers.”

As a matter of fact, endpoint threat detection has the highest share of security functions that AI is expected to enhance, as per the findings of the study.

Risk management is one of the top priorities for organizations as digital initiatives and cyberattacks give way to greater risk exposure. The study found increased investments for security frameworks to improve the assessment and management of cyber risk.

Key insights

• The adoption of the NIST cybersecurity framework jumped from 50.8 percent in 2023 to 62.7 percent in the 2024 study 
• 55 percent of organizations enhance their vulnerability assessment and management functions using AI
• 50.5 percent of organizations noted improved vulnerability, exposure assessment and remediation benefits with the help of AI

Security risk is an ever-evolving concern for organizations that is complex to manage and requires constant assessment and validation. Alongside adopting security frameworks, risk management practices can be further enhanced using the deep analysis capabilities of AI.

AI-enhanced risk management offers two major benefits:

1. AI systems can conduct more accurate risk scoring with qualitative and quantitative comparisons that
present a clearer picture of the risk landscape

2. AI-led automated incident summaries and responses can help cybersecurity administrators accelerate
investigation to keep risk levels in check

“A cybersecurity framework is not merely a set of guidelines; it is the foundation upon which the security posture of the entire organization is built. It’s good to think of these frameworks as potentially enabling the business and being a
competitive future advantage,” Wiens said.

“Adopting a cybersecurity framework and managing risk, aided with AI, can improve the long-term resilience of organizations, even if they don’t necessarily need to be compliant.”

While early threat detection can help mitigate damage, predictive capabilities can potentially improve an organization’s readiness to prevent threats. This proactive approach to cybersecurity may help defend against unforeseeable
attacks.

Key insights

• 49.5 percent of organizations believe the ability to detect novel attacks faster is an expected AI benefit
• 53.4 percent of organizations believe AI can potentially help them manage a security talent shortage through automation
• AI’s predictive capabilities help security teams to manage evolving threats within limited budgets

Predictive AI systems leverage a combination of historical data, real-time monitoring and pattern-matching capabilities to flag potential anomalies that may become threats. It’s like predicting a future threat based on previously encountered threats. These predictions can help security analysts get better insights into their security posture and fix loopholes that may go unnoticed.

“The use of behaviour analysis in cybersecurity isn’t new, yet we anticipate significant advances as AI capabilities expand. This includes developing AI-capable devices that enhance our ability to monitor and respond to threats more effectively,” Wiens said.

Therefore, organizations can stay one step ahead of cyberattackers by removing vulnerabilities that may become attack vectors. This capability, as reported in the study, also helps security teams get to the bottom of a cyberattack quickly when a novel attack surfaces by improving reaction speed and minimizing the impact of the attack. 

A cybersecurity false positive takes place when detection algorithms misfire due to outdated threat signatures or improper security settings. But as a security analyst, it might be hard to ignore flagged threats without checking if they’re really a false positive, which may lead to increased stress from overwork, or, conversely, to alert fatigue, in which many alerts get ignored or overlooked.

AI systems, thanks to their advanced analytical capabilities, can help eliminate false alarms. 

Key insights

• 66 percent of organizations find reduce false-positive security alerts as one of the top benefits of AI in cybersecurity 
• AI systems help teams improve the efficiency of security operations by focusing on real threats

Detection algorithms usually classify suspicious activities as threats based on a database of telltale signs, which may be limited or grow outdated with time. On the contrary, machine learning systems and large language models come with exhaustive datasets and enriched pattern-detecting capabilities that make them less prone to false positives.

“AI thrives on large datasets and fortunately, cybersecurity practices continue to amass vast amounts of data over the years. Leveraging these new technological capabilities to pinpoint the needle in a stack of needles offers a promising outlook,” Wiens commented.

As cyberattackers give rise to sophisticated attacks full of red herrings and deception techniques, AI systems can help organizations stay vigilant. With the use of AI-enhanced threat detection, security teams can be assured they go after the threats that really matter. 

As more Canadian organizations plan to adopt AI for cybersecurity functions, they’ll want to ensure smooth integration with legacy systems and resolve AI risks upfront. 

Our 2024 Canadian Cybersecurity Study speaks to Canada’s innovative landscape and captures prevailing trends. It offers statistical findings from Canadian organizations and our expert recommendations.

Leverage the full report to back your cybersecurity decision-making with the latest numbers and trends.