Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Odysseus left Troy with a fleet and reached Ithaca with nothing, having lost every ship to the sea. While the war was won by force, the journey home was won by wits, and ultimately the fleet barely mattered. Most security operations centers are still running their SecOps voyage the way Odysseus ran the war: more tools, more force, more signal. It is the wrong instinct, because the SOC bottleneck was never how much you can see. It is how fast you can decide.

Most agentic triage solutions hand you a verdict and stop right there. Maybe you get an alert ranking, maybe a severity score, maybe some light investigation, but you, as the analyst, still have to do the cleanup manually. There is still a mountain of evidence that needs to be gathered by hand, and a mountain of cases to dig through on your own.

Software Analyst Cyber Research (SACR) just published its 2026 AI SOC Market Report, offering an independent assessment of vendors competing in what has rapidly become the most consequential category in enterprise security. Torq features prominently, and the report’s framing is worth unpacking because it illuminates what makes the AI SOC category hard to evaluate and why Torq’s approach is consequential.

Back in June, I wrote a blog making the case that agentic triage alone isn’t an AI SOC. The way I see it, that’s like saying triage is the only responsibility of a SOC team. But as we know, the SOC’s responsibilities extend far beyond that, and these triage-only solutions don’t investigate threats, contain them, or close cases. That work is still left to the SOC team; the bottleneck is just shifting.

Every conversation our team has with security leaders begins the same way. Nobody is backing off on AI in the SOC. The direction of the lean is what’s shifting. Torq’s 2026 AI SOC Leadership Report surveyed more than 450 CISOs and SOC leaders. The data confirms what those conversations were already telling me. We’ve left the adoption phase. The market is now in the architecture phase and the implications for how teams plan, buy, and build are significant.

Most “AI SOC” demos out there can look great. The polished dashboard, the confident verdict, the slide that says “autonomous.” A demo is built to show the platform at its best, on clean data, in a controlled environment, answering a question the vendor already knew was coming. The differences only show up after you’ve signed, when the platform meets your real stack, alert volume, and compliance requirements.

A year ago, a handful of vendors called themselves an “AI SOC.” Today, more than 100 do. The label now means whatever the person selling it needs it to mean, leaving security teams to buy very different products under the same two words. So let’s sort the market. Beneath the “agentic” branding, most AI SOC vendors fall into one of four categories, and none of them clears the bar. Each can look capable in a demo.

The rules of offensive security just changed. Here's what every SecOps leader needs to do about it.

AI SOC memory is the difference between an investigation that starts from your team’s history and one that starts from zero. In most security operations centers, there is none: context disappears the moment a case closes. When a new alert fires, the investigation effectively starts from zero.

See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster. Request a Demo The first half of 2026 is coming to a close. And unless you live under a rock, there is only one takeaway: The AI SOC revolution is here, and Torq is winning.