AI Business Maturity Model

Depot Leaders Training

10 Lessons · Levels 1 – 3

AI for Depot Leaders

Click any lesson to jump in, or run the walkthrough start-to-finish. Scenarios run in the GenAI.mil simulator or ChatGPT.

Start walkthrough
Level 1AI Drifter

What is incidental exposure?

Every query you type into a public search engine leaves your device — landing in search logs, autocomplete systems, and ad-profiling databases. Nothing felt classified. But the detail is gone. Click any example below to see exactly what a browser search looks like from the other side.

The Level 1 hazard: There is no malicious actor, no breach, no classified query — just normal browsing behavior. The fix is structure: move to Level 2 prompting with approved tools and the right data classification.

Level 2Prompted Operator

Which tool for which data?

Public / Non-CUIAny tool (ChatGPT, Claude, Gemini)
CUI / PIIGenAI.mil (IL5) only, or depersonalize first
ClassifiedNo current IL5 AI tool. SCIF only.
Level 3Agent Builder

RapidDashboard — AIBMM-certified tool for NALCOMIS / SAMS-E plain-language dashboards.

Open ↗

Training Data Files — 3 Notional Depot Spreadsheets

Download, then upload to GenAI.mil (CUI) or any LLM (notional/non-CUI).

View in Data Lab →

Deep Research Projects — ChatGPT / Claude

Download the three training spreadsheets above, attach them to ChatGPT or Claude, enable Deep Research or web browsing, then paste a prompt below and let it run. Each project synthesizes the data with open-source research to produce actionable depot analysis.

AIBMM — structured five-level path from AI experiments to strategic advantage.

Talk Track — Beyond Level 3