TL;DR: Most teams asking this question already own SOAR and keep reading that it died. It did not. The category got absorbed into bigger platforms, and it still handles repeatable work better than anything else you can buy. What agents add is judgment on the cases nobody wrote a play for. So the call comes down to how much authority you are willing to delegate, and what evidence you expect back when you do.
The difference fits in one sentence
SOAR carries out a decision a human already made. An AI agent makes the decision in the moment and explains how it got there.
Every other difference comes off that one split. Hold onto it and the rest of the market noise gets much easier to sort.
What SOAR was built to do
SOAR started with a boring problem. Analysts were clicking across six consoles to answer the same question forty times a day.
So SOAR wired the consoles together. You write a playbook once, and the platform runs those steps every time a matching alert arrives. Enrich the IP. Open the ticket. Page the on-call engineer. Close the loop.
That works. It still works. The catch is that a playbook only fires on a case somebody already predicted.
Gartner put a stake in the ground in 2024. Its Hype Cycle for Security Operations labeled SOAR “obsolete before plateau” and dropped its benefit rating from high to moderate. The reason was not that orchestration stopped working. It was that other products swallowed it. Automation turned into a feature every platform ships instead of a market you shop for on its own. A Gartner analyst later clarified that the label was aimed at vendors selling standalone automation platforms, not at automation as a practice.
So read the “SOAR is dead” headlines carefully. Absorbed is not the same as gone. The capability is probably already sitting in your stack.
No: back to the queue
What an AI agent does differently
An agent does not wait for a matching rule. It treats the alert as a question and goes looking for the answer.
It decides while the alert is live
A playbook asks “which script matches this?” An agent asks “what is actually happening here?”
That means it pulls context, tests what the evidence suggests, drops the lines that go nowhere, and follows the one that does. Two alerts with identical signatures can end in two different verdicts, because the surrounding facts were different.
This is the part teams underestimate. You are not buying faster scripts. You are buying judgment, which also means you now have to audit judgment.
Coverage is not capped by your playbook count
A SOAR deployment can only cover the alert types you built for. Every new detection, new tool, or new attack pattern is a ticket for somebody to go write another play.
An agent starts from zero rules and reasons over whatever shows up. Nobody has to predict the case first.
That removes the maintenance ceiling. It does not remove the need for boundaries, which is where most pilots go sideways.
Where AI agents actually break
This part gets skipped in most vendor comparisons, so here it is plainly.
Agents are new. Gartner’s 2026 edition of that same hype cycle moved AI SOC agents up to the peak of inflated expectations, rated them embryonic, and put market penetration between 1% and 5%. Climbing that curve measures attention, not maturity.
The forecast is blunt about the gap. Gartner expects 70% of large SOCs to pilot AI agents for Tier 1 and Tier 2 work by 2028, but only 15% to show measurable improvement without a structured way to evaluate them.
Practitioners report the same thing from the other side. In the SANS 2026 AI Survey of 536 security and IT practitioners, only 27% called their AI deployment mature production. In the same study, 63% reported significant shortcomings in AI’s ability to detect or respond to threats, up from 45% a year earlier.
And the governance work is lagging the buying. 76% of those practitioners said they hold a governance role for enterprise AI, yet more than half said no formal audit framework exists to support it.
None of this says do not buy. It says the agent that cannot show you its reasoning is the one that will fail your pilot.
The real question is who holds the decision rights
Once an agent can decide, the interesting question stops being accuracy and starts being authority.
Teams running agents today answer that question conservatively. One 2026 practitioner survey on agent evaluation found 44% let the agent recommend while a human executes, 30% allow it to run low-risk actions on its own, and 13% extend that to medium-risk actions. Another 13% keep it on read-only triage. Not one team in that sample granted full autonomy with no oversight. Treat the figures as directional given the single source, but the shape is consistent with what teams say out loud.
The same survey found 57% require a person to review every agent decision before an alert is allowed to close.
That is the design answer, not a trust problem to be outgrown. An approval gate is what lets you widen the agent’s scope later without arguing about who signed off on what. It is the same logic behind human approval gates in compliance work.
Write the permission model down before the pilot:
- Advisory: which actions the agent can only recommend
- Signature required: which actions need a named human to approve
- Within policy: which actions can run on their own inside limits you set
Teams that skip this step end up negotiating it during an incident, which is the worst possible time.
When to choose which
Stay with SOAR for work you can fully describe
If the task has a fixed input, a fixed output, and no judgment in the middle, a playbook beats an agent on cost and predictability. Password resets, ticket routing, scheduled enrichment, and evidence pulls all qualify.
Deterministic work deserves a deterministic tool.
Reach for an agent where the work needs a verdict
Alert triage, phishing review, suspicious login investigation, and anything where the answer depends on context are a poor fit for fixed steps. These are the queues where building and maintaining SOAR playbooks never quite catches up to the alert volume.
If your backlog is full of cases that need a human to look before anyone can act, that is agent work.
Run both when you already own SOAR
This is the common case and the one most comparisons miss. Your SOAR platform is good at doing things. An agent is good at deciding what should be done.
Let the agent reach a verdict, then hand execution to the playbooks and integrations you already built and already trust. You keep the investment and skip the rewrite.
| SOAR vs AI agents at a glance | SOAR | AI agent |
|---|---|---|
| Who decides | A human, in advance, in the playbook | The agent, at runtime |
| Coverage | Only the alert types someone built a play for | Any alert, no play required |
| Best at | Fixed, repeatable response steps | Triage and investigation that need a verdict |
| Main risk | Playbook maintenance never catches up | Unverifiable reasoning and unclear authority |
| What to audit | The playbook logic | Every query, result, and decision the agent made |
Do AI agents replace SOAR playbooks?
Mostly no, and the ones they do replace are the ones you should want gone.
Agents make triage playbooks redundant, because reasoning at runtime beats a decision tree someone wrote last quarter. Response playbooks are different. The steps to isolate a host or revoke a token are supposed to be fixed, because consistency is the point.
So the honest answer is that agents replace the deciding, not the doing. If a vendor tells you to turn off your SOAR entirely, ask which specific playbooks they mean, and watch whether they can name any.
How Secure.com helps
Secure.com puts governed AI Teammates above the stack you already own, so nothing gets ripped out. The SOC Teammate decides, your team keeps the authority, and every step leaves a trail.
- Works with your stack: sits above your SIEM, EDR, and SOAR instead of replacing them, so existing playbooks and integrations keep running
- Coverage without playbook sprawl: reasons through alerts at runtime, so coverage is not limited by how many playbooks your team can keep current
- Approval gates you define: pauses where you decide, with read, recommend, execute, and remediate permissions kept separate
- A full audit trail: logs the recommendation, the approval, the action, and the outcome, so you can defend any decision to an auditor or a board
- Start small: begins as one teammate on one function, so you can prove the value before expanding
FAQs
Are AI agents replacing SOAR platforms?
Not as a category swap. SOAR got absorbed into broader platforms after Gartner marked it obsolete before plateau in 2024, and the orchestration layer is still doing useful work inside most stacks. Agents are taking over the decision step that sat in front of those playbooks.
Do AI SOC agents replace SOAR playbooks?
They replace triage playbooks, where a fixed decision tree was always a weak substitute for judgment. They generally do not replace response playbooks, where fixed, repeatable steps are exactly what you want.
Can SOAR and AI agents run together?
Yes, and for most teams that already own SOAR this is the practical setup. The agent investigates and reaches a verdict. The SOAR platform then carries out the approved action through connections your team already trusts.
What should I check before trusting an agent to act?
Ask to see the reasoning behind a verdict, not the verdict alone. You want every query the agent ran, the results it got back, and the ability to rerun those queries in the source tool yourself. If you cannot reproduce its work, you cannot audit it.
Is SOAR still worth buying in 2026?
As a standalone purchase it is a harder case, since most SIEM, XDR, and security platforms now ship orchestration natively. As a capability it is still worth having, and if you already run it, keeping it alongside an agent is usually cheaper than a migration.