AIRUM demo

Explore AI risks, applicable controls, and audit procedure guidance

This reduced interactive page shows how AIRUM can be used first as a risk-universe explorer, then as a deterministic pre-discovery selection aid, and finally as a starting point for applicable-control audit procedure planning.

Reduced AIRUM Public Demo: v3.2.1

Assurance Boundary

This reduced public demo shows selected AIRUM risks, representative controls, and summarized source references only. It is not the full AIRUM method or evidence base. AIRUM is a pre-discovery preparation aid and does not provide legal advice, does not provide audit assurance, source-perfect validation, or final workpapers.

Part 1 - AI Risk Universe

Explore the reduced AI risk universe

AIRUM starts as a curated universe of AI risks. This public version intentionally shows a reduced subset: selected risks, representative controls, and summarized source references only.

0 demo risks shown
reducedsource-backed subset
0applicable controls included

Honeycomb view

The original AIRUM idea is a risk universe: many AI risks arranged as a reviewable landscape, not a linear checklist. This reduced demo uses a sanitized honeycomb to show that concept without publishing the full risk universe.

source-backed AIRUM risk color = risk family
Original-style honeycomb reference

This is the original AIRUM honeycomb reference visual: a full risk landscape with risk titles inside the cells. The reduced demo below uses the same title-in-cell idea for the visible source-backed subset.

Open reference image Original AIRUM honeycomb reference with color-coded AI risk titles inside hexagons

Browse risk examples

The 10 visible risks use reduced AIRUM risk text plus the mapped applicable controls, control objectives, control source labels, and dedicated audit procedure detail links.

0visible

Part 2 - Risk Scoping

Frame a demo audit context

Risk Scoping uses the 10 source-backed demo risks below. It creates candidate discussion topics, not final audit-scope decisions. In the full AIRUM solution, this step would combine a richer audit context with the complete AI Risk Universe, group selected risks by audit use, and prepare a reviewable discovery pack for the audit team.

Full implementation reference

This screenshot-style reference shows the shape of the full AIRUM workflow without publishing internal rules, data mappings, or non-public risk content.

Open reference image AIRUM full implementation workflow reference showing risk universe, scoping inputs, candidate topics, and export pack
Open example export

What the full solution would usually do here

The public controls above only re-rank the reduced demo risks into candidate discovery-preparation topics. In the full AIRUM solution, this step would normally collect more audit context, apply the complete risk universe and internal selection logic, separate baseline governance checks from direct process risks and specialist dependencies, and produce an exportable discovery working paper.

The reduced public example shows the intended output shape: selected AI Risks, why each appears, applicable controls, control-level audit procedure guidance, discovery questions, and evidence to request.

Open the reduced discovery working paper

Challenge this output

For each candidate topic, ask: why did this risk appear; which assumption caused it; what evidence would remove it; what evidence would escalate it; what specialist or legal/compliance review is needed; and which disclosure-safe source family supports the expected control?

Candidate discovery-preparation topics

The demo pack now mirrors the newer AIRUM planning shape more closely: prioritized candidate topics, why they were selected, discovery focus, applicable controls, control-level audit procedure links, lifecycle context, and disclosure-safe source labels. It remains a reduced demo, not the full AIRUM method.

What the demo is not