Agentic AI (AI that makes decisions) is revolutionizing the IT world. But its biggest benefit may lie in making cybersecurity more robust.
Agentic AI promises to transform many areas of IT operations and services, including cybersecurity.
As agentic AI matures, its potential in cybersecurity is particularly compelling. This is because many cybersecurity applications are well-suited to AI. The technology can take advantage of the scale and speed at which human teams can perform tasks.
AI can continuously analyze large amounts of data without fatigue. This makes it ideal for monitoring environments where human attention spans eventually diminish.
This is especially useful for solving very broad or low-priority problems (for security teams that are currently understaffed).
In addition, AI’s real-time responsiveness means it can act much faster than humans. This helps reduce the impact of an attack or the time it takes for a threat to be detected.
By letting AI handle high-volume or real-time tasks, humans can focus on more strategic, high-value tasks.
Is your organization ready to add Agentic AI to your cybersecurity arsenal? Here are seven top use cases to consider.
1. Autonomous Threat Detection and Response
A unique use case for Agentic AI in cybersecurity is Autonomous Threat Detection and Response. This approach enables unprecedented speed and scale to prevent, contain, and remediate threats.
This includes autonomously detecting and blocking intrusion attempts in real time, while making security and IT changes to mitigate risks. In short, Agentic AI can act as a real-time, autonomous cyber defense agent.
Cyber attacks will increasingly be carried out by autonomous agents operating at the speed of light, far exceeding the ability of humans to respond.
The key value of autonomous threat detection lies in its speed and scale, two key aspects that traditional methods fail to achieve. Agentic AI will balance the playing field by allowing defenders to react with equal speed and breadth.
2. Security Operations Center (SOC) Support
Security Operations Centers (SOCs) are a great use case for Agentic AI because they are the frontline in detecting and responding to threats.
With thousands of incidents being prioritized every day, SOCs are experiencing alert fatigue. Investigators can spend an average of 21 minutes or more resolving an issue.
This is because documenting incidents and collecting evidence is time-consuming, and tracking vulnerabilities and unusual user access can be a complex process. Worse, the number of incidents is expected to increase as attackers use AI to carry out attacks on a wider scale.
It makes sense to deploy Agentic AI in SOCs. This is because AI agents can handle detection tasks, generate logs using natural language processing (NLP), It can be trained to integrate with Identity systems to correlate unusual accesses and perform automated remediation.
More importantly, Agentic AI SOC Analysts enable SOCs to scale geometrically when workloads fluctuate.
3. Automated Triage and Enrichment of Security Logs
Automated Triage, when combined with Enriched Security Event Logs, is a strong area where Agentic AI can be used.
Imagine an AI Agent: It automatically collects IOCs from various threat sources, correlates them with internal data, enriches the data with background information from OSINT (Open-Source Intelligence) and CTI (Cyber Threat Intelligence), and then generates a customized alert for the analyst.
Instead of waiting for the SOC team to manually change and scan various platforms one by one, the Agent can automatically scan for changes, flag anomalies, and prepare a recommended response plan.
This use of Agentic AI addresses two of the major challenges in cybersecurity: scale and speed. Analysts are overwhelmed by alerts and don’t have enough time to connect information from disparate sources. Agentic AI can effectively replace repetitive, high-volume correlation tasks.
More importantly, it bridges the gap between detection and resolution. So analysts can focus on validation and strategy rather than operations.
In practice, it doesn’t replace humans, but rather enhances expertise while removing unnecessary noise.
4. Empowering Security Staff
Another big problem facing cybersecurity isn’t technology—it’s the current staffing gap, and AI agents offer a practical solution.
AI agents can act as a force multiplier for your overworked security teams. They can help you automate the endless maintenance tasks needed to keep your security posture strong and solve complex problems across multiple security tools.
This frees up your best people to focus on critical threats instead of manual, repetitive tasks.
The cybersecurity staffing gap isn’t a temporary trend—it’s a long-term reality that we’ll face for years. It’s simply not something you can solve by hiring new employees.
Using AI agents is a strategic decision to invest in your existing organization, making them more productive, more efficient, and more effective. Ultimately, it will make you happier.
5. Protecting Brands from Fraud
Fake Domains have always been a problem. An AI Agent can scan for new domain registrations that look like your company, take screenshots, perform WHOIS checks, and even draft takedown requests.
An AI Agent recently caught a phishing site less than 20 minutes after it was launched. This would normally take days, during which time users could lose data and money.
Another great area of use is detecting fraudulent ads on social media. When fraudsters impersonate your brand and run Facebook or Instagram ads, the AI Agent can immediately alert you. So you can take them down before too many users click on them.
These incidents happen quickly, and it’s difficult for a human team to keep up with the volume. Every hour that a phishing site or fraudulent ad is up increases the risk of fraud and undermines user trust.
Since agents are constantly scanning for fraudulent websites and ads, they will have less time to detect fraud. And the human team will be free to focus on re-verification instead of regular monitoring. Ultimately, this will streamline the work, limit the time attackers have to attack, and keep users safer.
6. Help Desk Support
AI agents can be used to automate routine and repetitive help desk tasks, such as granting access to applications or resolving authentication issues. This gives team members the freedom to respond quickly to requests that may not be clear.
In the infrastructure context, AI agents can accelerate root cause analysis by examining system logs more quickly and correlating results across data sources. This gives human engineers a major lead in their investigations.
7. Self-governing, real-time Zero-Trust Policy Enforcement
Each user has a unique profile that reflects their unique behaviors, privileges, and risk scores.
AI agents can monitor these users. If they detect any deviation from the user’s normal behavior, agents can change what the user can access, require re-authentication, or temporarily isolate the user (sandbox).
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This is especially important for organizations that are trying to implement a Zero Trust security system. This is because agents can monitor non-human objects, like other AI agents.
