Agentic AI vs. Security Copilot: Which Approach Powers Your SOC?

AI is rapidly transforming how modern Security Operations Centers (SOCs) function. From analyst workflows to threat hunting and incident response, AI-driven tools promise faster, more accurate security outcomes. But not all AI is created equal. Two prominent approaches stand out: Agentic AI, a proactive and autonomous implementation that drives investigations and response independently, and Security Copilot, an assistive approach where the AI acts as an analyst’s sidekick. In this post, we’ll explore how these two paradigms differ, where they overlap, and how SOC teams can benefit from understanding both.

What is Agentic AI Security?

At its core, Agentic AI is about autonomy and proactivity. It’s not just about parsing logs or suggesting next steps—it’s about taking action. Think of Agentic AI as an investigation push to an analyst instead of an investigation pull from an analyst. Core competencies with agentic approaches include:

• Automate investigations. Given a suspicious alert, Agentic AI can automatically collect related telemetry, correlate logs, and analyze user behavior—all without waiting for a human to click a button. At its best, investigation planning is built dynamically and without hard-coded sequences or “playbooks”.
• Execute response actions. In many cases, the AI can isolate hosts, quarantine files, or escalate to an incident response team if it sees a high-confidence threat.
• Continuously learn and adapt. As it investigates and takes action, the system refines its investigative approach, effectively “learning from experience” based on user oversight into the system.

The benefit is obvious: less gruntwork for human analysts, faster time-to-fix, and fewer missed threats. That said, autonomy also brings risk. If an Agentic AI incorrectly identifies legitimate traffic as malicious, it could cause workflow interruptions or false positives. The key is balancing that autonomy with oversight mechanisms like keeping a human-in-the-loop for critical actions and ensuring that investigations are transparent and explainable for rapid analyst review.

Agentic approaches make the most sense for teams that:

1. Have limited analyst experience and struggle to ask the right questions to come to fast conclusions.
2. Are overwhelmed with alert volume and need an approach that can “take out the trash” with false positive alerts with minimal intervention

What is a Security Copilot?

A Security Copilot, in contrast, augments the analyst’s existing workflows. Think of it like having a dedicated AI research assistant who can:

• Pull in relevant intelligence with a quick query (“Which hosts are communicating with known malicious IPs from last week’s threat bulletin?”).
• Suggest remediation steps based on standard operating procedures, but leaves the final decision to the analyst.
• Contextualize alerts by summarizing suspicious patterns and pointing out possible next steps.

Security Copilots are essentially user-driven chatbots. They surface insights, but the human analyst is still at the wheel—initiating queries, interpreting results, and kicking off any major actions. This approach often feels more comfortable to SOC teams transitioning to AI, as it doesn’t overhaul their entire process or put potentially disruptive actions on autopilot. However, it also requires analysts to proactively prompt the AI and maintain a high level of engagement—so while it reduces some manual effort, there’s still significant human input involved.

Security copilots resonate most with teams that:

1. Have extremely strong security experts and limited alert volume. Copilots can go retrieve all the investigative data requested but require continuous prompting and active involvement from an operator.

Comparing Key Capabilities and Limitations

1. Automation & Proactivity
   
   • Agentic AI excels at proactively hunting threats and responding in real-time—ideal for high-volume, fast-moving attacks.
   • Security Copilot is less about autonomous response and more about assisting. It can help you identify what to do next, but you do the driving.
2. Decision-Making
   
   • Agentic AI can make decisions with minimal human intervention, speeding up response but increasing the potential impact of false positives.
   • Security Copilot keeps the decision-making in analysts’ hands, maintaining human oversight but requiring more time and human resources.
3. Workflows & Overhead
   
   • Agentic AI drastically cuts down on repetitive tasks and triage overhead, but demands robust guardrails, transparency, and contextual learning.
   • Security Copilot doesn’t fully offload gruntwork—analysts still need to interact frequently with the system.

Can They Work Together?

The short answer: Yes. There’s no rule stating a SOC can’t deploy both solutions in tandem. For instance:

• Agentic AI handles investigations autonomously, rapidly detailing the investigative process and supporting remediation workflows when relevant.
• Security Copilot allows users to follow-up in completed investigations with additional questions and dig deeper into evidence. They also complement Agentic AI security by enabling natural-language-based threat hunting for hidden threats that go undetected by existing alerts. 

By balancing the strengths of both, you can minimize alert fatigue, accelerate investigations, and empower operators to get to answers quickly without always needing to be in the driver’s seat.

Conclusion

Choosing between Agentic AI Security and a Security Copilot model isn’t an either/or proposition—it’s about aligning the right tool with the right problem:

• Agentic AI is proactive—it performs investigations and initiates responses without waiting for constant analyst input. This can drastically reduce your Alert Latency, Mean Time to Investigate, and Mean Time to Respond (MTTR). But with that autonomy comes greater need for robust guardrails and oversight.
• Security Copilot is reactive—it excels at responding to analyst queries, retrieving data, and suggesting next steps. This makes it ideal for teams that already have strong security expertise and want an AI “assistant” to streamline investigative efforts without replacing human decision-making.

At the end of the day, the best security strategy is the one that fits your team, your environment, and the threats you face on a daily basis. Whether you lean into Agentic AI, Security Copilot, or a combination of both, make sure you have the right processes and oversight in place to get the most out of your investment—without compromising on accuracy, control, or investigation quality.

Finding the right balance between automation and analyst control is key. Prophet Security’s Agentic AI bridges this gap by autonomously investigating alerts, reducing manual workload, and accelerating response times—without sacrificing oversight. To see how Prophet AI transforms security operations, request a demo today.

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