Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Generative AI–and large language models in particular–reached mass consumer adoption beginning in late 2022 and early 2023, with ChatGPT reaching 100 million users faster than any consumer application in history. Since then, AI has advanced at a breakneck pace and now seems to be incorporated in every tool, app, and website–regardless of how useful it might actually be.

Your fraud detection agent scores 30,000 transactions per hour. Your KYC agent processes identity verifications against government watchlists. Your customer service chatbot resolves disputes and initiates balance transfers. Each agent runs on Kubernetes with inherited service account permissions that span payment APIs, customer databases, and compliance systems. Now imagine one of those agents is compromised through a prompt injection embedded in a customer support ticket.

Upgrading Microsoft enterprise licenses from E3 to E5 or from Entra ID Plan 1 to Plan 2? Whether your company is making the move or evaluating it, the key question is: How do you turn licensing changes into real security gains? Platformizing remains a major trend in 2025, and Microsoft often sits at the center of these efforts due to its broad security capabilities. But maximizing value from E3 and E5 licenses requires time, expertise, and contextual understanding of your environment.

Most organizations treat AI security as a finishing touch: A policy written after an incident or a product category evaluated after the core stack is already in place. That sequencing is the problem. AI has fundamentally changed how sensitive data moves inside an organization, through prompts, agents, summarization tools, and third-party models that operate entirely outside traditional security perimeters.

A new research report from Reach Security reveals that misconfigured security controls, configuration drift, and unused capabilities across an organization’s existing security technology stack are a primary driver of cybersecurity risk.

The agentic AI security standards your enterprise will adopt in the next 18 months are being written right now, inside working groups most CISOs have never heard of. The Coalition for Secure AI (CoSAI), an OASIS Open Project with more than 45 sponsor organizations, including Google, Microsoft, NVIDIA, IBM, and Meta, is producing the frameworks, reference architectures, and secure design patterns that will define how autonomous agents operate inside enterprise environments.

Security teams accept that standing up a real SOC requires days of configuration, credential wrangling, and infrastructure work before any actual security engineering begins. With LimaCharlie, actual setup time is closer to ten minutes. It gives valuable time back to SecOps teams by managing infrastructure and simplifying onboarding and operations with Claude Code. Using agentic AI to deploy SOC capabilities means your team spends less time on infrastructure and more on security work.

The human layer is not impacted by Anthropic's Mythos Preview announcement. If anything, it is reinforced, and for reasons that deserve to be spelled out clearly.

The AI security market is crowded. Vendors are racing to protect prompts, harden models, detect jailbreaks, and scan for data leakage at the LLM layer. The investment is real. The intent is good. And most of it is missing the point. Here is the problem: agents do not just think. They act. They call APIs. They trigger workflows. They write to databases, send emails, move money, and modify production systems.

Security maturity was the thread running through BSides MKE 2026, from clearer business language to role clarity, AI governance, and non-human identity risk.