Artificial intelligence is transforming enterprise security in significant ways, delivering capabilities that were previously unattainable. As Sheetal Mehta, global head of cybersecurity at NTT DATA, outlines, we are witnessing a critical shift where AI systems, capable of learning and making decisions autonomously, are redefining how organizations manage cybersecurity.
The question for enterprises is whether they are fully leveraging AI's strengths in security operations. Here, we explore seven impactful applications of AI to bolster security resilience across organizations.
Enhancing Network and User Monitoring
One key function of AI is its ability to monitor network and user activities continuously, automating routine security tasks along the way. Leslie Daigle, CTO at the Global Cyber Alliance, emphasizes that employing behavioral analytics and machine learning models enables the identification of suspicious activity. “AI can flag critical threats, allowing security teams to concentrate on the most significant incidents,” she states.
AI's effectiveness stems from its integration within existing security infrastructures rather than operating as a standalone element. Daigle points out that crafting effective AI models requires collaboration among cybersecurity, IT, and AI teams to ensure alignment with an organization's specific context and threat landscape. It's also essential to regularly review and validate these models to respond to evolving threats adequately.
Providing Deeper Visibility into Security Posture
Security teams frequently find themselves overwhelmed by data but lacking clear insights into their security program's performance. Sivan Tehila, a professor at Yeshiva University’s Katz School and CEO of Onyxia Cyber, notes that AI can significantly enhance this visibility. Instead of laboriously sifting through information, security professionals can pose straightforward questions to AI—like “Which users are registered without MFA?”—to receive immediate, prioritized responses, drastically reducing analysis time.
This shift in approach not only streamlines the process but also transforms the perception of success from merely proving no breaches occurred to actively demonstrating consistent program improvements.
Streamlining the Security Operations Center (SOC)
The application of AI within Security Operations Centers (SOCs) has shown potential to vastly improve threat detection, alert triage, and response times. Marc Vael, director of global digital trust at Esko, stresses that with millions of security events arising daily, AI's ability to analyze and correlate data across different variables is invaluable. By prioritizing high-risk events, AI allows security analysts to focus on genuine threats without being overwhelmed by false positives.
Moreover, AI's rapid data processing capabilities equip teams to detect compromised accounts, insider threats, and evolving attack techniques that traditional methods may miss. The end result is reduced investigation times, as AI can automatically gather evidence and summarize findings, streamlining overall incident response.
Connecting the Dots on Ordinary Activities
While traditional cybersecurity measures often center around identifying suspicious activities, AI enables organizations to understand the context behind typical behaviors. Neil Sahota, chief AI officer at Consolidated Analytics, highlights that many successful attacks exploit seemingly benign actions, masking a breach until patterns of behavior are interconnected. Here, AI excels at recognizing these intricate relationships across various data points, such as identity systems and network telemetry.
As Sahota recommends, employing AI as a decision-making partner allows analysts to observe its recommendations and gradually shift to more autonomous functionalities based on trust and performance outcomes.
Reducing Data Loss and Improving Management Protection
AI proves to be more adept than humans in differentiating routine business operations from genuine risks by contextual analysis—considering a user's role, the intended data destination, and the timing of actions. Swathi Joshi, senior vice president of cyber defense at TransUnion, explains that AI establishes baselines for typical employee behavior and identifies deviations that may signal emerging threats. This capability helps reveal subtle patterns that might evade traditional, point-in-time controls.
Providing Relief to Security Teams
One of the most significant benefits AI offers security teams is the ability to process various logs and alerts swiftly, filtering through high volumes of data more efficiently than human analysts, according to Andrew Citro, CISO at Reltio. He suggests that organizations initially focus on one critical use case—such as phishing detection or alert triage—to validate AI's contributions before implementing broader automation.
Uniting Signals with Intelligence
AI can also serve as an intelligence layer that aggregates signals across an organization, providing context to help security teams make swift, informed decisions. Kuldeep Thakur, CISO at Incedo, asserts that integrating AI shifts security from merely generating alerts to continuous insight production. For years, heightened security spending has led to an abundance of sensors and alerts but left human analysts inundated with noise. AI now offers a way to transform alerts into coherent narratives within moments, allowing human oversight for judgments that truly require it.
By embracing these advanced AI applications, organizations can strengthen their overall security posture, reduce the incidence of breaches, and optimize resource deployment. This perspective not only sets the stage for proactive cybersecurity efforts but also significantly enhances operational efficiency amid an increasingly complex threat landscape.
