Gartner declared SOAR "Obsolete Before Plateau" in 2024, and the industry has been arguing about whether SOAR is dead ever since. The vendors who built the category responded quickly, and now sell AI SOC platforms and agentic AI instead.
This article breaks down what actually died, why the work still piles up, and the blind spot the replacement platforms carried over.
SOAR stands for security orchestration, automation, and response. As a product category, it bundled three jobs. It connected security tools, executed repeatable response steps without a human doing the clicking, and carried out the containment action at the end. TechTarget's breakdown treats those as three separable functions.
The label caused enough confusion that Gartner customers flooded the firm with questions about what it meant, per Dark Reading. Gartner's own analyst narrowed the scope. Eric Ahlm clarified in the same reporting that the designation targets "the field of vendors who sell nothing but dedicated platforms for automation," a group he doubted had "a very lively future."
The strongest evidence that SOAR is dead as a purchasable category is the acquisition record. Dark Reading's reporting lists four deals between 2017 and 2024 that folded standalone SOAR products into larger security platforms. Three of the four were pure-play SOAR products. The fourth folded a SIEM suite with SOAR inside it into a larger platform.
Ahlm explains why. SOCs wanted a single hub for investigation and response. Extended detection and response (XDR) and SIEM platforms grew into that role, and a separate automation purchase no longer justified its own line item.
TechTarget's April 2026 report found former SOAR companies marketing themselves as "AI SOC," "agentic AI," or "intelligent workflows" vendors. Analysts and vendors now avoid the label, even though SOCs still depend on the functionality.
Demand kept rising through it all. The SANS 2024 SOC Survey recorded lack of automation and orchestration as the single most-cited barrier, named by 71 of 388 respondents. The two staffing answers, high staffing requirements and lack of skilled staff, together outnumber it.
Strike48's May 2026 survey of 100 security leaders points to the deeper problem:
Storage cost sets that ceiling, capping how much alert volume any automation layer can cover.
Much of the commentary declaring SOAR dead is published by the vendors selling its replacement. That commentary blames legacy SOAR's failure on rigid architecture, limited integrations, and a shortage of playbook engineers. The strongest part of that case holds up. Playbook maintenance is an engineering cost that never retires, and it grows with every integration and every upstream schema change.
Every one of those arguments assumes the alert stream underneath is complete. It usually is not. An agentic layer inherits whatever the alerts left out, and an unmonitored log source produces no signal for an agent to work with, no matter how good the model is. In Strike48's May 2026 survey, 65% of security leaders said an investigation has stalled because log data was trapped somewhere they could not query it.
The three positions differ on which layer they blame.
The first two rows argue about whose reasoning layer is better. The third asks what either layer can see in the first place.
Strike48's federated search architecture queries logs where they already live, so agents work across the full environment, including data that never made it into a SIEM. Search-in-place connectors reach S3, existing SIEM stores, and data lakes directly. Parse-at-query processing structures the data at read time, so nothing waits on an ingest pipeline.
Each micro agent runs with a fixed scope. A GraphRAG persona graph defines what each agent can retrieve, and Model Context Protocol (MCP) constraints control which tools it can call. Investigations run autonomously. A person approves anything with consequences.
Yes. A log source that never reached a queryable store cannot factor into the investigation at all, so an agent's conclusion depends on what it can retrieve.
With full coverage, endpoint, identity, and network signals from one intrusion correlate into a single case with patient zero identified. That is the work Strike48's SOC Level 1 and Level 2 agents do against shared indicators like IP addresses, user accounts, and process hashes. Under partial coverage, the same intrusion surfaces as separate alerts, each triaged from a separate angle and closed on its own thin evidence.
Complete visibility raises the ceiling on agent reliability. Agents still make things up, which is why scoped micro agents and human approval gates stay in the design.
Teams that understand their own workflows and tech stack still get real value from deterministic, rule-based automation. Gartner analyst Kevin Schmidt told TechTarget that SOAR's code-based nature makes it brittle once the people who built the integrations leave, and that teams succeeding with it should stay put. "You don't throw out your tool that is working just to go after the new splashy, shiny AI stuff," he said.
Phoenix Cyber reports a fivefold return for clients running SOAR successfully, and Omdia's read is that a standalone platform remains a reasonable approach for many companies.
The workflows that hold up best are compliance-driven, audit-heavy sequences where the same steps must execute the same way every time and leave a fixed evidence trail. Hybrid workflow design makes it a per-step choice within one workflow. Run the repeatable parts on fixed rules and save the agent's judgment for the steps that need it.
Strike48's Pre-Built Agent Packages run SOC investigation work as coordinated micro agents with a human sign-off on high-impact actions. Four mechanisms cover the jobs SOAR used to hold.
The branching logic engineers used to hard-code into playbooks is now decided at runtime, based on the evidence in front of the agent.
Tasks like field normalization, routing, and ticket creation follow fixed, deterministic rules. Tasks with more ambiguity like evidence synthesis and escalation calls go to an agent.
The agent assembles the case and names the recommended action. A person authorizes anything with real-world consequence.
The record shows which tool ran, on what data, and what the agent concluded. An Evidence Collection Agent organizes that record by control and framework requirement.
Search-in-place connectors query the existing stores, so Strike48 runs alongside the SIEM as a log intelligence layer. The existing SIEM keeps its job. Where centralizing a source is the faster path, Smart Collection covers roughly 80% of an organization's log sources in under a day. The deeper comparison of SOAR alternatives breaks down where each replacement category falls short.
The claim that SOAR is dead holds up, and the evidence is public. Four acquisitions closed between 2017 and 2024. By April 2026, the trade press found the surviving vendors had largely stopped using the word. And SOC teams still name a lack of automation as their most-cited barrier, the same problem SOAR was built to solve.
That leaves one question worth asking in every platform conversation: what share of the environment can the automation layer query?
Two follow-ups pin the answer down:
Strike48 starts from complete log visibility, because agents can only investigate what they can query. The Flexible Data Foundation handles that at petabyte scale.
Security orchestration, automation, and response. In practice, it describes a hub that connects security tools through integrations, executes predefined response sequences without an analyst driving each step, and takes the containment action at the end. Those three functions are separable, which is why other platforms could absorb them one at a time.
No. A SIEM collects log data and detects threats. That produces the alerts. SOAR coordinates and executes what happens after an alert fires. They converged because platform vendors bought or built both into a single product, and buyers stopped seeing them as separate purchases.
Finish the deterministic playbooks whose logic is already codified. That work keeps its value in any architecture. Then inventory which log sources your automation layer cannot query today and what reaching them would cost. That inventory feeds the next platform decision, and you don't have to rip anything out to produce it.
