u/DryEggplant6678

Leadership wants ChatGPT (and similar tools) available because the productivity gains are real, but security wants controls. Blocking felt like the easy option a year ago, but now it just pushes people to personal devices or browser workarounds, which is worse for visibility.

The workaround problem is what worries me most. Once someone starts pasting work content into a personal ChatGPT account on their phone, you've lost all visibility, and any DLP investment stops mattering for that data flow.

So, for the sysadmins who've dealt with this: what's your actual setup? DLP integration, browser-level controls, enterprise ChatGPT accounts with admin controls, or some combination?

Also wondering how much of this comes down to technical enforcement vs. policy and trust. At what point did leadership stop asking for a full block?

im Looking at this from the transport side rather than the security side.

basically....AI traffic has a different profile than the web traffic our current design was built around:..long-lived connections, streamed responses, bursty token throughput, and a small number of destination endpoints concentrated in a handful of US and EU regions. Add inline inspection on top and you are doing decrypt, inspect, and re-encrypt on sessions that stay open for minutes.

What that surfaces: PoP density matters less than PoP placement relative to model endpoints; inspection adds compute at the edge, which not every PoP footprint is provisioned for; our sites in South America and Southeast Asia are already the outliers on RTT, so adding an inspection hop there is the thing I am worried about; and peering to the major cloud and AI providers varies a lot by vendor and nobody publishes it clearly.

Questions for anyone who has measured rather than trusted the marketing map: what is your real added latency for an inspected AI session from a secondary-market site; does the vendor do inspection at every PoP or only at a subset of "full-stack" locations, since several are quietly the latter; and has anyone hit throughput ceilings on inspection during peak?

Doing an audit before we commit budget to this, and the current state is embarrassing. SAST, SCA, a separate cloud posture tool, a container scanner, and a CSPM bolted on top, each with its own dashboard, its own alerting, and its own definition of "high severity." Nobody on the team has a single view of actual risk, just five browser tabs of noise, and ownership tracing across all of this is a nightmare since a finding in the SCA tool doesn't know which team owns the repo.

Before we sink a quarter into this, what should I actually be watching out for? Has anyone gone from 5+ tools down to something unified and seen it stick, or are there hidden gotchas nobody warns you about going in?

We have gone from one agent to five in about six months, and each one is wired into different internal tools.

Every agent has its own custom setup for policy and permissions, and logging is still handled separately by each team. Nothing is centralised. Adding a sixth agent means rebuilding the same stack again.

What I keep wanting is something like an AI control plane, one place that defines policy and applies it consistently across every agent instead of each team rebuilding enforcement from scratch. I have not found much written about what that actually looks like in practice, as opposed to the term just being used as a marketing label.

For teams managing more than a couple of agents, is centralised policy across agents actually achievable today, or is everyone still running point solutions per agent and calling it a control plane afterwards?