Government contractors can use AI productively today — but the constraints (data handling, auditability, human accountability, FedRAMP-aligned infrastructure) must be design inputs from day one, not retrofits. Start with low-sensitivity, high-volume workflows and a documented human review path.
Start with posture, not the model
In a regulated environment the first questions are not about the model. They are: what data can this touch, where can it run, who is accountable for the output, and can we prove what happened? Answer those and the technical choices narrow themselves.
Where to start
The best first AI workflows in gov-con are high-volume, low-sensitivity, and human-reviewed: drafting from approved content, summarizing for an analyst who verifies, surfacing relevant prior work. Save the high-stakes automation for after the posture and the trust are established.
- Data boundaries drawn before any build — what is in scope, what is never in scope.
- Auditability on every step — prompt, sources, output, the human who approved it.
- FedRAMP-aligned infrastructure so the path to ATO is the path you are already on.
- Human accountability named and documented for every consequential output.
In regulated work, "the AI decided" is never an acceptable sentence. A named person decided, with the AI's help, and there is a record of it. Design for that from the first line of code.
On CMMC specifically
CMMC readiness is its own discipline. We deliver it through A3PO, our partnership with Alpha Team Solutions — an AI-assisted readiness workflow with human expert review at its center. It exists precisely because compliance work is too consequential for un-reviewed automation.