Around 2017, every SOC leader heard the same pitch: take your best analyst’s phishing workflow, encode it as a playbook, and let software run it a thousand times a day without coffee breaks. Extract the URL, detonate the attachment, check the sender’s history, quarantine matching messages, close the ticket. For that class of work, the pitch was honest. SOAR platforms really did give security teams their first taste of response at machine speed.
Then teams discovered what the pitch left out: someone has to build every playbook, maintain every integration, and anticipate every branch in advance. A decade later, SOAR occupies a strange position, genuinely useful, widely deployed, and no longer where the industry’s ambitions live. Understanding why requires understanding what SOAR is, where it came from, and what changed around it.
What Is SOAR in Cybersecurity?
SOAR (Security Orchestration, Automation and Response) is a category of security technology that connects an organization’s security tools through API integrations, automates repetitive security tasks through predefined playbooks, and manages incident cases and response actions from a single workspace. The name spells out its three pillars: orchestration is the plumbing between tools, automation is the playbook engine that executes multi-step workflows, and response is the case management layer where analysts track incidents to closure.
The unit of work in SOAR is the playbook: a flowchart of actions and decision points, built in advance, triggered by an alert or a human. A phishing playbook might extract indicators, query threat intelligence, check whether anyone clicked the link, and quarantine the email across every mailbox, with an approval gate before any destructive step. The logic is deterministic. Given the same inputs, the playbook does the same thing every time, which is both its greatest strength and its defining limit.
SOAR is downstream of detection. It doesn’t find threats; it acts on what other systems, most often a SIEM, have already flagged. That position in the pipeline matters, because SOAR can only be as smart as the alert it receives and the branches its author anticipated.
Where SOAR Came From, and Where the Category Went
A Gartner Acronym, Twice Over
Gartner coined SOAR in 2015, and the original expansion wasn’t what it means today: it stood for Security Operations, Analytics and Reporting. In 2017 the firm redefined it as Security Orchestration, Automation and Response, describing the convergence of three tool types, orchestration platforms, incident response case management, and threat intelligence platforms, into one product. The redefinition stuck because it matched what startups like Phantom, Demisto, and Swimlane were actually building.
The category validated fast. Splunk acquired Phantom in 2018, Palo Alto Networks acquired Demisto in 2019 (rebranding it as Cortex XSOAR), and within a few years nearly every major security platform vendor had bought or built a SOAR capability. That consolidation wave was a compliment, and also a warning sign for the standalone market.
From Category to Feature
By the mid-2020s, analysts had largely stopped treating SOAR as a market of its own. Playbook automation became a bundled feature of SIEM platforms, XDR suites, and managed service offerings rather than a product you bought separately. The capability didn’t die, far from it, but the era of the standalone SOAR purchase mostly ended. What replaced the standalone conversation is the one this article closes with: whether predefined playbooks are still the right abstraction for automating security decisions at all.
Two forces drove the absorption. Buyers were tired of paying separately for automation that logically belonged inside the tools producing the alerts, and platform vendors needed a workflow layer to make their consolidation stories credible. By the time low-code workflow builders arrived with friendlier pricing, the standalone pioneers had already been folded into bigger portfolios, and the acronym had quietly become a feature checkbox.
What Playbooks Do Well, and Where They Hit a Ceiling
The Sweet Spot: Deterministic, High-Volume Work
SOAR shines when a task is repetitive, well-defined, and consequential to get wrong by hand. Indicator enrichment, ticket creation and routing, IP blocking, account disabling with approval gates, evidence collection at the moment an alert fires. These tasks don’t need judgment; they need consistency and speed. A well-built playbook executes them in seconds, identically, with a full action log, and frees analysts from work that was never a good use of a human.
The gains show up directly in response metrics. Enrichment that took ten minutes per alert happens before a human ever opens the case, and containment steps that once waited for someone to log into three consoles fire in seconds. For high-volume SOCs, this was the first automation win the industry could actually measure, and it’s why the pitch worked as well as it did.
Teams that got real value from SOAR tended to share a trait: they automated narrow, boring workflows first and resisted the urge to encode entire investigations. The tool rewards modesty.
The Maintenance Tax
Every playbook is software, and software rots. Vendors change APIs, log formats drift, a SaaS tool gets replaced, and the playbook that ran cleanly for eight months starts failing silently on step four. Organizations that deployed SOAR aggressively often found they’d hired for security engineering and ended up staffing an internal automation dev team instead. Walk into a long-running SOAR deployment and ask which playbooks still run in production; the gap between “built” and “running” is usually the first honest metric you’ll hear.
And the tax scales with ambition. Ten playbooks are manageable. A hundred playbooks, spanning three tool migrations and two team reorgs, are a legacy codebase.
The Judgment Gap
The deeper limit isn’t maintenance. It’s that branching logic is not reasoning. A playbook can ask “is the asset tagged critical?” because its author anticipated that question. It can’t ask “is this login weird for this specific user, given what I know about their role, their travel, and the incident we closed last week?” unless every one of those considerations was wired in ahead of time. Real incidents are combinatorial; playbooks are enumerative. The gap between those two words is where Tier 1 analysts have always lived, doing the alert triage and investigation work that no flowchart could absorb.
That’s not a flaw in any particular SOAR product. It’s a property of the abstraction. Which is why the next wave of SOC automation didn’t try to write better flowcharts.
SOAR in the AI SOC Era: Playbooks Versus Reasoning Agents
The clearest way to see what changed is to compare how each approach handles an alert neither has seen before. A SOAR playbook checks its trigger conditions, finds no match (or worse, a partial match), and either does nothing or does the wrong predetermined thing. An agentic AI system starts from a goal, “determine whether this alert is a real threat,” and works out the steps itself: what context to pull, which systems to query, what hypotheses to test, when the evidence is sufficient to reach a verdict. Playbooks encode answers. Agents encode the method for finding answers.
That difference compounds across the alert queue. Playbook-based SOC automation covers the scenarios someone bothered to build, which in most deployments is a thin slice of the queue. An AI SOC platform investigates the whole queue, including the odd, low-severity, doesn’t-fit-any-playbook alerts that historically got closed on a glance because nobody had time. The full four-way breakdown of who does what is worth reading separately in this SIEM vs SOAR vs XDR vs AI SOC agents comparison.
None of this makes SOAR obsolete as an execution layer. The integrations SOAR platforms spent a decade building, the connectors that disable an account or quarantine a mailbox, are exactly the hands an AI agent needs once it reaches a verdict. A realistic 2026 architecture pairs the two: AI SOC agents do the investigation and decide what should happen, and playbook-grade automation carries out the mechanical action, with human approval gating anything irreversible. The reasoning moved; the plumbing stayed.
Managed service providers illustrate the hybrid better than anyone. A provider running dozens of customer environments can’t hand-build and maintain a playbook library for each tenant, the maintenance tax multiplies by customer count, but they can run reasoning agents across every tenant and reuse each customer’s existing connectors as the action layer. The economics that made playbook sprawl painful are the same economics now pushing reasoning to the front of the pipeline.
To be fair to the flowchart: where a process genuinely never varies, a playbook is still the cheaper, more predictable tool, and mature teams will keep a set of them running for years. The mistake was ever expecting playbooks to carry judgment.
Conifers CognitiveSOC is built on the reasoning side of that architecture. Its agents run investigations end to end, gathering evidence across connected tools and documenting each step, with an average investigation taking around 2.5 minutes, and autonomy bounded by explicit guardrails so that consequential actions stay under human control. Teams weighing playbooks against reasoning agents can see the difference concretely at a live demo.
Frequently Asked Questions About SOAR
What is the difference between SIEM and SOAR?
The SIEM is the detection layer: it collects telemetry, correlates it, and raises alerts. SOAR is the action layer: it takes those alerts and runs workflows around them, enrichment, ticketing, containment steps, notifications. A SIEM without SOAR gives you findings and no hands; SOAR without a SIEM gives you hands and nothing to act on. Most enterprises run them as a pipeline, and most SIEM vendors now sell the two as one platform.
A practical test when evaluating either: trace one alert end to end. The SIEM’s job ends when the alert is raised with the right context attached. SOAR’s job ends when every follow-on action is executed and documented. Everything between those two points, deciding what the alert actually means, is a third job entirely, and it’s the one neither acronym ever covered.
Is SOAR dead?
As a standalone product category, mostly yes; as a capability, no. Playbook automation is now a feature inside SIEM, XDR, and managed service platforms rather than a separate purchase, and analyst firms stopped covering SOAR as its own market. But the connectors and workflow engines those products built remain in daily production use, increasingly as the execution layer beneath AI-driven investigation. What died is the idea that a library of hand-built flowcharts could automate security operations by itself.
If you already own a SOAR, the practical takeaway isn’t to rip it out. It’s to stop expanding the playbook library into judgment territory and let the platform do what it was always best at: reliable, audited execution of the steps somebody, or something, has already decided on.
What is the difference between SOAR and an AI SOC agent?
Determinism. A SOAR playbook follows branches a human authored in advance; it cannot handle a situation its author didn’t foresee. An AI SOC agent reasons about the specific alert in front of it, decides what evidence to gather, and adapts its investigation as findings come in, closer to how an analyst works than how a script runs. The practical consequence: SOAR automates the scenarios you predicted, while agents cover the queue you actually have, including the alerts that fit no template.
When is a static playbook still the better choice?
Whenever the process truly doesn’t vary and the cost of deviation is high. Regulated notification sequences, evidence preservation steps, offboarding a terminated employee’s access, these should run the same way every single time, and a deterministic playbook is the right tool precisely because it can’t improvise. It depends on the work: if you’d fire an analyst for being creative with the task, script it; if you’d fire them for not being able to think, don’t expect a script to do it.