The Future Of Human-Machine Teaming: Why AI Won't Replace Security Operators

Lydia Zhang, President and Co-founder of Ridge Security.

​Every time a new AI capability lands in security operations, someone asks how many analysts it lets us cut. It’s become almost reflexive. But it might be the wrong question, and an investigation into Meta handed us a pretty good real-world example of why.​

According to an August 2026 Reuters investigation, Meta had explored an “AI native” restructuring effort called Project OT, cutting some teams by as much as 60% and having a smaller group of employees supervise AI agents doing most of the routine work. Meta completed one round of layoffs in May (about 8,000 people), then quietly shelved the bigger second wave. Internally, code changes were up 220% year over year, but the share that turned into actual new or better features for users rose only 36%. Major technical and security incidents rose 40%.​ This means more activity, barely more progress and more things breaking.​

That’s not proof that AI agents don’t work. It suggests a job is rarely just a stack of tasks you hand off one by one, and security is a clear example of that.​

Why It Was Never A People Problem

Watching an alert queue and flagging what’s malicious is only part of a security operator’s job. A good analyst is constantly building context: What does this system do? Who depends on it? If it’s a real attack, what happens to the business if we shut it down? AI can help pull that context together fast. It doesn’t inherently know why any of it matters.​

The fear that AI replaces analysts also misreads what’s broken in most SOCs. It was never that there are too many people, but that there’s too much work. A typical team faces roughly 4,330 alerts a day, and only around 37% ever get a proper look. Nearly 90% of teams report meaningful skills gaps, and most tie a recent incident directly to one.​