An AI-centric SOC is a security operations center where AI does most of the investigation work, and people own the judgment calls. "AI-centric SOC" is the term we use for our own 24/7 SOC.

Here's how that plays out day to day: AI agents pull telemetry, correlate activity, and flag suspicious behavior. When a threat is confirmed and clears a confidence threshold that people set, the AI acts on it. When a signal is ambiguous or new, it goes to a SOC analyst.

SOC analysts write the playbooks, set the thresholds, and can override the AI at any time. The word that matters is central: the AI carries the weight, and people hold the controls.

A fully autonomous AI SOC is a security operations model where AI investigates, decides, and responds to threats end to end, with no human review required.

The AI closes the case, including the ones it decides are benign. People still tune the system, audit it, and handle exceptions, but they aren't reviewing each verdict before it becomes final.

Vendors use different labels for this, so ask questions about validation. The test is simple: can the AI close an investigation without a person looking at it?

Plenty of SOCs have AI in them, and they don't all work the same way. Here's how the three common models stack up, with the AI-centric column showing how we run ours.

These three sit on a spectrum, and the spectrum is defined by where a person sits in the decision.

It's tempting to compare these models by speed or by how much AI is under the hood. The better comparison is who owns the verdict.

A SOC makes two kinds of calls: "this is a confirmed threat, act now" and "this is nothing, close it." The second one carries more risk. A false positive costs you time. A false negative, a malicious case wrongly closed, leaves an attacker in your environment.

So the closure decision is the one to watch. In an AI-centric SOC, AI moves fast on confirmed threats, and a SOC analyst reviews the benign closure. In a fully autonomous SOC, the AI makes that call too.

Here's what an AI-centric model looks like when it's written down as rules.

Athena is Huntress' agentic investigation system, made up of over 40 specialized AI agents. It works inside our 24/7 SOC alongside SOC analysts, and the guardrails around it are specific.

What Athena can do

• Investigate, act, and report on confirmed threats automatically when human-defined confidence thresholds are met
• Pull telemetry, correlate signals, and speed up investigations that SOC analysts lead
• Draft incident reports once a threat is confirmed

What Athena can't do

• Close an investigation as benign without a SOC analyst reviewing it
• Make the final call on a case that goes to an analyst for review. When an investigation goes to an analyst, the analyst decides

What happens when Athena isn't sure

• A signal that's ambiguous or below the confidence threshold routes automatically to a Huntress SOC analyst for review and finalization
• SOC analysts can review, revise, or override any Athena output

Athena outcomes, by the numbers

Athena moves at full speed on confirmed, high-confidence threats. On the decision with the most downside—closing something as harmless—a person signs off.

SOC analysts own the playbooks and the thresholds. They adjust them as threats evolve, and they review the cases where Athena isn't confident. That's the practical difference between AI-centric and autonomous: who has the last word.

A common worry is that keeping people in the loop slows everything down. In an AI-centric SOC, it mostly doesn't, because AI acts on its own where confidence is high. Our guide on automated threat remediation shows how Managed Response contains confirmed threats in seconds.

People earn their place on the cases that don't fit a playbook. New tradecraft, odd edge cases, and signals that could go either way need a SOC analyst's judgment and context. Our guide on incident response automation and why human SOC review still matters goes deeper on that.

Attackers move at machine speed, so AI belongs at the center of the SOC. The question is which decisions you hand it.

Use these when you're evaluating a managed SOC, ours or anyone else's. They work whether a vendor says "AI-centric," "agentic," or "fully autonomous."

1. Who decides when an alert is dismissed? Get a straight answer. If it's "the AI," ask what safeguards sit behind that decision.

2. Can the AI close a case as benign on its own? This question separates the models. A yes means the AI owns closure, and a no means a person reviews it first.

3. Who sets and adjusts the confidence thresholds? Thresholds decide what the AI acts on and what it hands off. Find out whether experienced SOC analysts own them and how often they change.

4. What happens to ambiguous or novel signals? Does the AI make its best guess, or does it route the signal to a person? Ask what "below threshold" means in practice.

5. Can analysts override the AI, and can you see what it did? Look for human override and a clear report on every automated action. If you can't see what happened and why, you can't trust it.

If you can't get a plain answer to all five, keep looking.

The Huntress Agentic Security Platform is backed by a 24/7 AI-centric SOC where AI handles the legwork and a SOC analyst owns the hard calls. It's built for businesses of all sizes, and you don't need a security team of your own to use it.

Faster threats get handled, and a person stays accountable for the decisions that matter. That's the deal.

See how the Huntress 24/7 AI-centric SOC works