AI can do what now?! Agentic AI is the autonomous future coming to security operations

Agentic AI in cybersecurity promises to transform workflows as we know them, enabling a new level of personalization, automation, efficiency, and innovation.
It’s already being deployed by security teams for use cases like autonomous threat detection and response, advanced threat hunting, automated incident investigation, real-time fraud protection, and more.
So, how is agentic AI working overtime to help security analysts build a more resilient security posture? In this most recent episode of AI can do what now?!, Anas Khatri, security solutions architect at Elastic, explains how agentic AI can address skills shortages, ease alert fatigue management, and enhance existing AI security tools.
Agentic AI in SOC operations
AI agents in SOC operations are designed to address the most persistent cybersecurity challenges. “We have been trying to address these challenges for quite some time now, but it looks like agentic AI can really push that boundary and get us across,” Khatri says.
Rather than relying on static playbooks, AI agents can autonomously analyze threats, gather contextual information, and adapt their behavior based on findings.
Agentic AI security tools fundamentally shift security operations by combining multiple key components:
Large language models (LLMs): An LLM (one or several) provides the reasoning and generative capabilities.
Automated workflows: Once an LLM generates incident response results, security analysts need a workflow to help decide which actions to take. Security platforms like Elastic use open agentic frameworks to build purposeful, automated workflows.
APIs: AI agents need a connection to existing security tools.
Retrieval augmented generation (RAG): One of the most important pieces of the puzzle, RAG provides the right context for every AI answer, ensuring its accuracy.
AI agents are great at alert triage, automatically enriching data with threat intelligence, and continuously optimizing detection rules based on observed patterns. They interpret context, select optimal enrichment sources, and iteratively refine conclusions, mimicking the work of security analysts.
How to integrate AI in SOC: Preparing for the future of agentic AI
“There’s no reason for security analysts to feel insecure about agentic AI replacing them,” Khatri notes. “An AI agent is just another smart analyst that is always available. Reducing the number of human analysts or replacing them is not the right approach to this tool.”
Instead, Khatri explains, agentic AI augments security analysts in SOC operations. By automating mundane or time-consuming tasks, AI agents free human analysts to focus on complex investigations and strategic security decisions. For management, getting more value out of people and technology makes operations more efficient.
Agentic doesn’t just augment the work security analysts do. It can support each and every existing security tool, streamlining your toolkit and your workflows. While it’s too early to completely replace every tool with an AI agent, it’s in your best cybersecurity interests to start adopting this technology.
“If you're not doing it, attackers are already using agentic AI and LLMs to attack you faster,” Khatri says. “It's not an option; it's a necessity to use the right agentic AI with your existing SOC tools. Otherwise, you’re going to be left behind.”
Ultimately, cybersecurity teams should consider agentic AI as another smart colleague that you can consult for answers and optimization. Agentic AI tooling will support your security analysts, not replace them. By using AI agents to augment your tools, you can bolster your security posture and stay ahead of potential attackers.
Check out the AI Can Do What Now?! - Agentic AI episode to learn why now is the time to start preparing for the future of security operations and how agentic AI should be used today.
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