{"id":5575,"date":"2025-10-29T07:00:00","date_gmt":"2025-10-29T07:00:00","guid":{"rendered":"https:\/\/cybersecurityinfocus.com\/?p=5575"},"modified":"2025-10-29T07:00:00","modified_gmt":"2025-10-29T07:00:00","slug":"top-7-agentic-ai-use-cases-for-cybersecurity","status":"publish","type":"post","link":"https:\/\/cybersecurityinfocus.com\/?p=5575","title":{"rendered":"Top 7 agentic AI use cases for cybersecurity"},"content":{"rendered":"
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Agentic AI promises to revolutionize a wide range of IT operations and services, including cybersecurity. While the technology, which accomplishes specific tasks with no human supervision, may seem intimidating to some CISOs, a growing number of cybersecurity leaders are discovering that agentic AI is less complex and easier to deploy than they initially believed.<\/p>\n

\u201cAs agentic AI becomes more mature, its potential in cybersecurity is particularly compelling,\u201d says Sandra McLeod<\/a>, CISO at Zoom, noting that many cybersecurity use cases are a strong fit for AI because they take advantage of the technology\u2019s ability to operate at a scale and speed human teams can\u2019t match.<\/p>\n

AI can process massive volumes of data continuously without experiencing fatigue, making it ideal for monitoring environments where human attention would eventually taper off, McLeod explains. \u201cIt\u2019s especially useful for addressing problems that are either too large in scope or too low in priority for already-stretched security teams,\u201d she says.<\/p>\n

Additionally, AI\u2019s ability to respond in real-time means it can act much faster than humans, helping to reduce the blast radius of an attack or minimize the time a threat remains undetected. \u201cBy handling high-volume or time-sensitive tasks, AI allows humans to focus on more strategic, higher-value work,\u201d McLeod adds.<\/p>\n

Is your organization ready to add agentic AI<\/a> to its cybersecurity arsenal? Here are seven top use cases for your consideration.<\/p>\n

1. Autonomous threat detection and response<\/h2>\n

A standout use case for agentic AI in cybersecurity is autonomous threat detection and response, which offers the ability to detect, protect, contain and recover from threats at unprecedented speed and scale, says John Scimone<\/a>, president and CSO at Dell Technologies.<\/p>\n

\u201cThis includes spotting and disrupting intrusion attempts autonomously in real-time by making security and IT changes to mitigate risks,\u201d he explains. \u201cEssentially, agentic AI can operate as a real-time, autonomous cyber defense agent.\u201d<\/p>\n

Cyberattacks are increasingly executed by autonomous agents<\/a> operating at the speed of light, far outpacing human response capabilities, Scimone says. The primary value of autonomous threat detection lies in speed and scale \u2014 two critical factors where traditional methods fall short. \u201cAgentic AI will level the playing field by enabling defenders to respond with equal speed and expansive breadth,\u201d he says.<\/p>\n

2. Security operations center support<\/h2>\n

Security operations centers (SOCs)<\/a> are a great use case for agentic AI because they serve as the frontline for detecting and responding to threats, says Naresh Persaud<\/a>, principal, cyber risk services, at Deloitte.<\/p>\n

With thousands of incidents to triage daily, SOCs are experiencing mounting alert fatigue<\/a>. \u201cAnalysts can spend an average of 21 minutes or longer per ticket to remediate,\u201d says Persaud, noting that documenting cases and collecting forensic data is a time-consuming task, while tracking vulnerabilities and user access anomalies can be a complex process. \u201cWhat\u2019s more, the volume of incidents is expected to rise as attackers increasingly employ AI to launch attacks on a broader scale.\u201d<\/p>\n

Persaud believes that adding agentic AI to SOCs<\/a> makes sense given that agents can be trained to handle detection, utilize natural language processing (NLP)<\/a> to produce case documentation, integrate with identity systems to correlate anomalous access<\/a>, and perform automated remediation. \u201cMore important, agentic AI SOC analysts can allow SOCs to scale geometrically as work volume fluctuates.\u201d<\/p>\n

3. Automated triage and enriched of security event logs<\/h2>\n

Pascal Geenens<\/a>, director of threat research for cybersecurity services firm Radware, says that automated triage, combined with enriched security event logs, form a strong AI agentic use case.<\/p>\n

\u201cImagine an AI agent that autonomously collects indicators of compromise [IOCs] from multiple threat feeds, correlates them with internal telemetry, enriches the data with context from OSINT and CTI [cyber threat intelligence] repositories, and then drafts a structured alert for an analyst.\u201d Instead of waiting for a SOC team to pivot manually across different platforms, the agent executes the pivoting automatically, flags anomalies, and prepares a recommended response playbook.<\/p>\n

Geenens believes his suggested approach, like many agentic AI use cases presented here, addresses two major cybersecurity pain points: scale and speed. \u201cAnalysts are drowning in alerts and lack the time to connect dots across multiple sources,\u201d he says. Agentic AI can effectively supplant repetitive, high-volume correlation tasks. More important, it closes the gap between detection and mitigation, enabling analysts to focus on validation and strategy rather than operations. \u201cIn practice, this doesn\u2019t replace humans, but amplifies expertise while cutting through noise.\u201d<\/p>\n

4. Augmenting security talent<\/h2>\n

Another big problem in cybersecurity doesn\u2019t involved technology \u2014 it\u2019s the current talent gap, and AI agents provide that most practical answer<\/a>, says Rahul Ramachandran<\/a>, generative AI product management director at Palo Alto Networks.<\/p>\n

\u201cAI agents can act as force multiplier for your swamped security teams, automating the endless maintenance needed to keep your security posture solid and troubleshooting complex issues across your many different security tools,\u201d he explains. \u201cThis frees up your best people to focus on critical threats instead of manual, repetitive work.\u201d<\/p>\n

The cybersecurity talent gap isn\u2019t a temporary trend \u2014 it\u2019s a persistent reality<\/a> we\u2019ll be facing for years, Ramachandran warns. \u201cYou simply can\u2019t hire your way out of this problem,\u201d he adds. \u201cUsing AI agents is a strategic decision to invest in your existing team, making them more productive, more effective and, ultimately, happier.\u201d<\/p>\n

5. Protecting brands against fraud<\/h2>\n

Fake domains have always been a headache, says \u0160ar\u016bnas Bru\u017eas<\/a>, CEO of office equipment services provider Deskronic. \u201cAn AI agent can scan for new domain registrations that appear similar to your company, grab screenshots, perform WHOIS checks, and even draft takedown requests.\u201d<\/p>\n

Bru\u017eas reports that an AI agent recently helped him catch a phishing site in less than 20 minutes from launch. \u201cThat would have normally taken days, during which time customers could have lost data and money,\u201d he says.<\/p>\n

Another strong use case is detecting scam ads on social media. \u201cScammers run Facebook or Instagram ads that impersonate your brand, and an AI agent can alert you immediately so you can have them taken down before too many customers click,\u201d he adds<\/p>\n

Such incidents happen quickly, and a manual team can\u2019t keep up with the volume, Bru\u017eas says. Every hour a phishing site or scam ad is up increases the risk for fraud while damaging customer trust. \u201cWith agents always scanning for fake sites and ads, it will take less time to detect scams, and the human team is then free to focus on review instead of routine monitoring,\u201d he notes. \u201cIn the end, this will make work smoother, limit the time attackers have to strike, and keep customers safer.\u201d<\/p>\n

6. Help desk support<\/h2>\n

AI agents can be used to automate common and repetitive help desk tasks, such as provisioning access to applications or troubleshooting authentication issues, freeing team members to respond quickly to requests that may not be as straightforward, says Ed Dunnahoe<\/a>, vice president of innovation at cybersecurity services firm GuidePoint Security.<\/p>\n

\u201cIn the context of infrastructure, agents may also be able to speed-up the process of performing root cause analysis by parsing system logs more quickly, correlating results across data sources, and giving human engineers a major head start on their investigation,\u201d he adds.<\/p>\n

7. Autonomous real-time zero-trust policy enforcement<\/h2>\n

Every end user has a unique profile, reflecting specific behaviors, privileges, and risk scores, says Stephen Manley<\/a>, CTO at cyber resilience platform provider Druva.<\/p>\n

\u201cAgents can monitor those users and, if there\u2019s a deviation, can push changes to what that user can access, force a re-authentication, or even temporarily sandbox that user,\u201d he says. This becomes even more important, he adds, for organizations that are striving for zero trust<\/a>, \u201cbecause you can have agents monitor non-human actors, such as other AI agents.\u201d<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"

Agentic AI promises to revolutionize a wide range of IT operations and services, including cybersecurity. While the technology, which accomplishes specific tasks with no human supervision, may seem intimidating to some CISOs, a growing number of cybersecurity leaders are discovering that agentic AI is less complex and easier to deploy than they initially believed. \u201cAs […]<\/p>\n","protected":false},"author":0,"featured_media":5576,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-5575","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-education"],"_links":{"self":[{"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=\/wp\/v2\/posts\/5575"}],"collection":[{"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5575"}],"version-history":[{"count":0,"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=\/wp\/v2\/posts\/5575\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=\/wp\/v2\/media\/5576"}],"wp:attachment":[{"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5575"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5575"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cybersecurityinfocus.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5575"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}