AI Intake Without Security Boundaries Is a Liability

Start with purpose and consequence

Name the question the workflow supports, the user of its output, and the action that may follow. Distinguish an internal draft from a recommendation relied on in a consequential decision. This context determines which records and review steps need attention.

Map the information route

Identify the sender, source category, collection field, provider, tool, storage location, access owner, and intended recipient. Ask where prompts, uploads, outputs, and logs may persist. A statement that a tool is “AI-enabled” does not establish permission to process a particular record.

Separate public contact from record transfer

ARE Global’s public intake is a local draft helper for a non-sensitive summary. It does not call an AI model or upload supporting files. Sending source material for an accepted assignment requires a separate agreement on authority, purpose, tools, and handling.

Illustrative boundary failure

Hypothetical example: a public form asks a visitor to paste a complete customer file so a workflow can be described. The record transfer occurs before anyone has decided whether those details are needed or permitted. A short description of the workflow and information categories would support the first discussion with less disclosure.

Define the human decision

Identify who can pause the workflow, reject an output, request a source check, and authorize release. Record the version and review basis. A useful intake design includes a permitted route for uncertainty rather than forcing every submission into an automated result.

Reference

NIST AI RMF Core. The AI RMF organizes risk-management activities through Govern, Map, Measure, and Manage. The intake review described here is ARE Global’s scoped application of risk-management principles.

This is public advisory analysis. Hypothetical examples are not client results. Service boundaries and information-handling requirements remain applicable.