Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

DevOps moves fast by design. Continuous integration, automated deployments, and infrastructure-as-code let development teams ship features in hours rather than weeks. Security teams have a real opportunity here: when they build workflows that integrate directly into the development process, they gain coverage and response speed that manual, disconnected approaches leave on the table.

Security teams have always had to justify their budgets, and the bar for that justification keeps rising. Boards and CFOs want proof that security spending delivers measurable business value: reduced risk translated into financial language. That pressure has made cybersecurity ROI calculators a standard part of the security leader’s toolkit, a way to convert threat prevention, automation efficiency, and incident response improvements into the numbers executives understand.

Yaniv Zimmer is an AI researcher at Torq, focusing on cybersecurity research at the crossroads of artificial intelligence, deep learning, and defensive operations. Drawing on extensive experience within Unit 8200 alongside industry and academic AI research roles, his work centers on advancing SOC AI architectures and threat detection capabilities Like a lot of people, we were excited when Jev launched. The premise is genuinely useful in production: an intelligent language model built for classification.

Over the course of this series, I’ve laid out the case for a fundamentally different security operating model — one built around Outcome, Judgment, and Execution layers, where AI handles the execution at machine speed, and humans focus on the decisions that actually need them. I’ve argued that the CISO’s role is changing, that human-centric security no longer scales, and that the org chart needs to reflect where AI fits on the team.

John White is the Field CISO for EMEA at Torq. A respected security executive with more than 20 years of leadership experience, John previously served as CISO at Virgin Atlantic, where he led a multi-year transformation deploying the Torq AI SOC Platform to modernize cyber operations. Prior to that, he built and transformed security functions for global organizations, including ASOS, Liberty Global, AEG Europe, and KPMG.

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.