IVIS

Sample · illustrative

What a Mini AI Risk Map looks like.

A simplified, illustrative example for a fictional support automation. Your real map is specific to your system — this shows the shape of the deliverable.

One-page executive summary

“SupportCopilot” is an internal automation that drafts replies to customer tickets using an LLM over your help-center content. It touches customer data, your orders API, and Slack. The biggest risks are an over-broad API credential and unredacted PII reaching the model. None are blockers to launch, but two High items should be fixed first. Recommended next step: remediate the two High findings, then a focused re-check.

Touchpoint inventory

Users

Support team (12), 2 external contractors

Data

Customer tickets, order history, partial PII

Integrations

Zendesk, internal orders API, Slack

AI

LLM + RAG over a help-center index

Credentials

Shared API key, broad read scope

Prioritized risks

High

Over-broad API credential

The automation uses one shared key with read access well beyond what the workflow needs. Scope it down and rotate.

High

PII can reach the model context

Customer records flow into the prompt with no redaction. Add field-level filtering before retrieval.

Medium

No human approval on outbound actions

The agent can post to Slack and update tickets without review. Add an approval step for state-changing actions.

Low

Limited logging

Prompts and tool calls aren't logged, making incidents hard to reconstruct. Add structured logging.

Recommended next step: fix the two High findings (scope the credential, redact PII before retrieval), then a focused re-check. No full audit needed yet.

Get a real map for your system.

A $1,499 Mini AI Risk Map gives you this clarity for one real app, workflow, or automation.