Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

With 96% of security teams now using AI, the question is no longer whether AI delivers real value to the SOC, but one of efficiency and reliability. The recent AI Adoption in the SOC report, conducted by Dimensional Research and sponsored by Elastic, surveyed more than 400 cybersecurity professionals responsible for security operations at companies with more than 500 employees.

The rules of cyber defense have shifted. Threat actors are increasingly using advanced automation to accelerate reconnaissance, evade static signatures, and orchestrate rapid intrusions across critical infrastructure, software supply chains, and insider pathways. This has created a critical velocity gap: when adversaries compress attack timelines from days to minutes and defenders rely on manual triage across fragmented legacy tools, the defense falls behind.

The future of policing depends on more than changing force structures or investing in AI. It depends on making data work across boundaries. Policing is being asked to change at pace.

As autonomous AI reshapes cyber risk, financial institutions need the visibility and context to detect unusual behavior and respond at machine speed. AI agents are changing more than just how financial services companies operate. They are also changing the speed and scale of cyber risk.

On August 20, 2026, the Cybersecurity and Infrastructure Security Agency (CISA) published its Logging Reference Architecture (LRA), the implementation guidance federal civilian executive branch (FCEB) agencies have been waiting for since the Office of Management and Budget's Memorandum M-26-14 reset the requirements for enterprise logging.

Elastic sits at the very top of this year’s AV-Comparatives' CyberRisk Quadrant within the 2026 Endpoint Prevention and Response (EPR) test with the only protection scores at 100%, combined with both the lowest modelled operational footprint of any tested product and zero false alerts.

How teams are leaving value on the table and what it costs when they do It's 3:00 a.m. Your on-call engineer gets paged that the central processing unit (CPU) is at 97% on payment-processor-01. They open their observability platform, look at the metric spike, reboot the host, and close the ticket.