Here's a situation everyone in this room has dealt with: you've got a legacy system with an ATO that's three years old. The evidence was collected once, the narratives were written once, and since then the system has drifted. New services got deployed, configurations changed, patches got applied (or didn't). The ATO package on file describes a system that doesn't exist anymore. But nobody wants to re-authorize because that's a 12-to-18-month nightmare.

The usual advice is "modernize the system and the ATO comes with it." That's fine if you have the budget and the three-year timeline. Most programs don't. They need their authorization current now, not when the rewrite ships in 2029.

This session is about a different approach that we've been working on: modernize the authorization without touching the system. Deploy AI-powered evidence collection into the existing environment, connect to whatever infrastructure is already there, and bring that paper ATO into continuous monitoring in two to three weeks. The system stays the same. The authorization becomes alive.

We'll walk through how this works in practice:

First, evidence discovery. You deploy into the existing VPC or hosting environment and connect to what's already running: cloud services, vulnerability scanners, config management, source repos. No new infrastructure. No modifications to the legacy system. You pull current-state evidence: actual configurations, actual scan results, the real security posture as it exists today.

Second, gap analysis. You compare what you collected against what the SSP says. Where the system matches, AI generates updated narratives grounded in real data. Where it's drifted, you know exactly where, you know how bad it is, and you get actionable remediation guidance. This replaces months of manual assessment with a clear picture in days.

Third, continuous monitoring. Once the package reflects reality, you keep it there. Scheduled re-collection, drift detection that catches changes before they become findings. The ATO stops being a document you dust off every three years and becomes something that's always current.

For teams that are actively rewriting legacy code, we'll also cover how AI-driven scanning catches STIG violations, IL5 gaps, and vulnerabilities during development rather than after. The goal is that by the time your modernized system is ready to deploy, the security work is already done. You don't hit the "security valley" where the system works but can't get authorized.

We'll talk honestly about where this approach works well and where it gets tricky: systems with minimal cloud footprint, air-gapped environments, integration with eMASS workflows, and what kinds of evidence adapters actually exist today versus what's coming.

The big picture we want to put in front of this audience: the DAF has thousands of systems with stale or expired ATOs. We don't have to rebuild all of them to fix the authorization problem. If we can use AI to bring them into continuous monitoring in weeks instead of years, that's a massive improvement in our actual security posture, not just our compliance paperwork.