MDR vs. Agentic AI SOC Analyst: Complementary or Replacement?

As a former security analyst and leader at top Managed Detection and Response (MDR) providers such as Mandiant, Expel, and Red Canary, I’ve seen the category evolve from its early days—when we’d manually pull and analyze forensic data on a monthly basis to check for active compromise—to today, where we process terabytes of telemetry in real time. The best MDRs deliver exceptional outcomes for customers, but they’re not a silver bullet.

At the same time, AI-driven SOC Analysts are the latest buzz in security operations, promising autonomous investigations, scalability, and real-time response. But where do they fall short?

Let’s break down where MDRs excel, where they struggle, and how Agentic AI SOC Analysts fit into the equation.

The core strength of MDRs: Detection

MDR providers specialize in detection. They build and maintain detection rule libraries that apply across their entire customer base, often going beyond vendor defaults. By leveraging security telemetry from EDR, SIEM, and other sources, MDRs deliver broad coverage and help identify known threats and attack patterns.

They’ve got teams of analysts writing these detections, and if a technique is listed in MITRE and your security tools can see it, a good MDR should catch it.

Detection coverage and response time are the top two things to evaluate when considering an MDR. And it makes sense—MDRs are designed to escalate threats as early as possible.

The challenge? They don’t always go deep on investigations and often lack context to make accurate determinations.

If an MDR is managing hundreds of customers, its analysts may not have the time or context to fully investigate every alert. In the worst cases, security teams end up answering a stream of follow-up questions from outsourced analysts who don’t have enough information to resolve alerts independently.

Instead of saving time, teams end up spending even more of it.

Where MDRs face challenges

Great MDRs provide strong detection coverage, but they need to solve for the masses at scale. That means they aren’t built for every use case, especially for organizations with complex environments or mature security programs that rely on custom detections.

Here’s where MDRs struggle:

• Limited Support for Custom Detections – MDRs prioritize scalable, repeatable detections that work across multiple customers. If you’ve built custom detections for your environment, most MDRs won’t handle them—leaving a major gap in coverage.
• Lack of Organizational Context – MDR analysts don’t have deep knowledge of your internal processes, infrastructure, or risk tolerance. That can lead to generic recommendations, false positives, and inaccurate investigative conclusions that require manual intervention.
• Investigation Gaps – MDRs excel at detecting threats, but full investigations are often left to the customer. Many escalations contain only basic triage data, leaving your team to correlate logs, determine root causes, and assess impact.

These challenges open the door for more automated, context-aware security operations.

The role of an Agentic AI SOC Analyst

Agentic AI SOC Analysts are designed to fill these gaps by autonomously investigating alerts, applying contextual knowledge, and scaling security operations beyond human limits. Here’s how they help:

• Continuous, parallel investigations – Unlike human analysts, AI SOC Analysts don’t experience fatigue and can handle an unlimited number of investigations at once. Your alert starts being investigated immediately—in seconds, not minutes or hours.
• Adaptability to custom detections – AI SOC Analysts can interpret and investigate alerts from custom detections, eliminating the scalability issues that MDRs face. They use your tools like your team would, learning from feedback to refine future investigations.
• Deeper investigations in real time – Instead of escalating an alert with limited triage data, AI SOC Analysts correlate logs, identify root causes, and map out attack paths—all within minutes. Mean Time to Investigate? Under 10 minutes, end-to-end.
• Remediation and containment – AI SOC Analysts don’t just investigate—they can take action. Whether isolating a compromised host, resetting credentials, or containing threats based on policy, remediation can be automated or require manual approval.
• Learning and improvement – Most security alerts turn out to be false positives, but that data isn’t worthless. AI SOC Analysts analyze closed cases, recommend tuning adjustments, and suggest posture improvements to prevent similar alerts in the future.

Can MDRs and Agentic AI SOC Analyst work together?

For organizations using an MDR, an AI SOC Analyst can amplify the impact, handling deep investigations, reducing the time spent on triage, and enabling faster response. This allows MDRs to focus on detection while AI-driven investigations add the missing context.

For organizations without an MDR, an AI SOC Analyst can serve as a replacement, delivering continuous monitoring, investigation, and response—without relying on an outsourced team.

The catch? AI SOC Analysts still need detections to work with. Whether from native security tools or a custom-built SIEM pipeline, they need a starting point.

Ultimately, whether you need both depends on:

• Your security maturity – Do you have strong detections in place already?
• Internal resources – Can your team handle investigations, or do you need automation?
• Response expectations – Are you getting fully investigated alerts from your MDR in under 20 minutes? If not, an AI SOC Analyst can dramatically speed up resolution times.

Conclusion

MDRs have played a vital role in modern security operations, but they aren’t without limitations. Agentic AI SOC Analysts take a different approach—focusing on scalability, investigation depth, and speed.

Whether as a complement or a replacement, AI-driven security operations are reshaping how threats are investigated and resolved. Organizations evaluating their security strategy should consider where MDRs and AI SOC Analysts fit in—either as standalone solutions or as an integrated approach—to maximize security effectiveness.