AEGIS · AEGIS Policy Core
Artifact 1.3
AI Risk Register
The live inventory of AI risks, quantified, owned, and reviewed. Risks that are not on this register cannot be addressed; risks on this register cannot be ignored.
- Client
- [CLIENT NAME]
- Engagement
- [ENGAGEMENT ID]
- Version
- v1.0
- Issued
- 2026-09-22
Delivered by TechFides under the AEGIS Governance Operating Services engagement. This document is proprietary to the client named above. Redistribution beyond the engagement steering committee requires written consent.
Purpose
Intent. A risk register is a living document, not a deliverable. Its value is in what it forces the organization to do, name risks, assign owners, quantify exposure, and return to the decisions quarterly.
This register is the system of record for AI risks at [CLIENT NAME]. It is owned by the AI Governance Lead, ratified by the Council, and reviewed in full every quarter. Any risk discussed outside the register, in a meeting, an email, or an incident debrief, must be recorded here within five business days or it does not exist for governance purposes.
Risk Categories
Intent. Six buckets covering the territory. Every risk in the register is tagged to one primary category; secondary categories are noted in the detail row.
Data & Security
- Regulated data (PHI, PII, PCI) sent to an AI tool without a BAA or DPA.
- Model provider retains prompts and outputs despite enterprise settings, exposing trade secrets.
- Vector database used for RAG contains restricted content that bypasses access controls.
Legal & Regulatory
- EU AI Act obligations apply to a deployed system and no conformity evidence exists.
- AI-generated communication with customers creates an implied contract or regulatory disclosure duty.
- Copyright or IP exposure from model training data or generated output that mirrors a protected work.
Operational
- Production workflow depends on a model that can silently change version without notice.
- Shadow AI creates parallel processes that bypass SOP review steps.
- Critical business knowledge concentrated in a prompt library with no backup or version control.
Financial & Vendor
- AI spend growing 40%+ YoY with no cost owner or utilization data.
- Vendor lock-in on a model or tool with no defensible switching plan.
- License-per-seat spend on tools used by a small fraction of the license holders.
Reputational & Ethical
- Hiring or performance decisions made with AI screening that has not been bias-audited.
- Customer-facing chat feature produces harmful, discriminatory, or defamatory output.
- Undisclosed AI use in professional services creates a trust breach when discovered.
Personnel & Change
- Key employees quietly use unsanctioned AI, resigning with institutional knowledge embedded in external tools.
- Policy fatigue: staff stop reading updates and miss a material change.
- Training completion high but retention low, assessment scores drop in spot-checks.
Scoring Method
Intent. Quantified exposure, not adjectives. Every risk gets a likelihood, an impact, and a dollar band.
Likelihood scale (1 to 5)
- 1: Rare. Would require an unlikely combination of failures; no realistic scenario in the next 12 months.
- 2: Unlikely. Could occur but no evidence it has or is trending up.
- 3: Possible. Has occurred at peers, or there is indirect evidence inside the organization.
- 4: Likely. Near-misses already observed; the condition for occurrence is present.
- 5: Near certain. Expected to occur in the next 12 months without intervention.
Impact scale (1 to 5)
- 1: Negligible. Cost or disruption absorbed without material effect.
- 2: Minor. Addressable within a function; no board or regulator attention.
- 3: Moderate. Cross-functional response required; may trigger client notification.
- 4: Major. Executive attention; material financial cost; reputational exposure.
- 5: Severe. Board-level incident; regulatory action plausible; existential for a product or line of business.
Severity = Likelihood × Impact
A risk's severity is the product. Score ≥20 is P0 and is reviewed at every Council meeting. 12 to 19 is P1 and is reviewed quarterly. 6 to 11 is P2, reviewed annually. Below 6 is tracked but not actively managed unless re-scored.
Dollar exposure
Every scored risk carries a dollar band (range, with stated assumptions). Dollar bands are the currency of board conversations and force a discipline that adjective-based risk assessments do not. Bands can be wide, but they cannot be absent.
Active Register
Intent. The live inventory. Populated from the diagnostic and maintained continuously. The rows below are illustrative starting risks that appear in most engagements.
| ID | Risk | Cat | L | I | Sev | Exposure | Owner | Treatment | Due |
|---|---|---|---|---|---|---|---|---|---|
| R-001 | Shadow AI use of consumer tools on client material | DS | 4 | 5 | 20 | $250 to $800K | CISO | Mitigate | Week 8 |
| R-002 | Model provider retention settings not verified in writing | DS | 3 | 4 | 12 | $100 to $400K | CISO | Mitigate | Week 5 |
| R-003 | AI coding assistant produces insecure authentication flow | OP | 3 | 5 | 15 | $200 to $1.2M | CTO | Mitigate | Ongoing |
| R-004 | Customer-facing AI ships without disclosure notice | LG | 2 | 5 | 10 | $100 to $500K | General Counsel | Avoid | Pre-launch gate |
| R-005 | AI spend grows untracked across function budgets | FN | 5 | 3 | 15 | $50 to $200K / yr | CFO | Mitigate | Week 8 |
| R-006 | Resume-screening AI lacks bias audit | RP | 3 | 4 | 12 | $150 to $2M | CHRO | Mitigate | Week 10 |
| R-007 | Vendor subprocessor change unnoticed | DS | 3 | 4 | 12 | $75 to $300K | CISO | Mitigate | Ongoing |
| R-008 | Prompt library contains P1 data pasted into templates | DS | 4 | 3 | 12 | $50 to $200K | Knowledge Ops | Mitigate | Week 10 |
Risk Detail Template
Intent. The format every entry in §4 expands to. One page per risk when the row is clicked through, or on a standalone sheet for P0 risks.
[R-XXX]
[RISK TITLE]
- Condition
- [THE STATE OR PATTERN THAT MAKES THE RISK POSSIBLE]
- Consequence
- [WHAT HAPPENS IF THE RISK LANDS, STATED CONCRETELY]
- Likelihood · Impact · Severity
- [L=X, I=Y, SEV=XY]
- Exposure
- [$ LOW: $ HIGH · WITH STATED ASSUMPTIONS]
- Owner · Backup
- [NAME + TITLE · BACKUP NAME]
- Treatment
- [MITIGATE / ACCEPT / TRANSFER / AVOID]
- Treatment Plan
- [CONCRETE ACTIONS, WITH DATES, THAT WILL CHANGE L OR I]
- Review cadence
- [NEXT REVIEW DATE]
- Related artifacts
- [VRA #, INCIDENT #, POLICY SECTION, ETC.]
Treatment Decisions
Intent. Four paths, chosen explicitly. The register is not a to-do list, it is a record of decisions made about exposure.
Mitigate
Reduce likelihood, impact, or both through controls, process changes, or engineering. Default treatment for risks at P0/P1. A mitigate decision comes with a treatment plan and a due date.
Accept
Choose to carry the risk at its current level because treatment is disproportionate to exposure. Acceptance requires an accountable decision-maker named in the register and a scheduled re-review date.
Transfer
Shift the exposure to a third party, insurance, a vendor contract, or a client assumption. Transfer is never total; the residual risk stays on the register.
Avoid
Change the activity so the risk condition no longer applies. Avoid is the strongest treatment but is not always available, use it when the risk is intolerable and the activity is optional.
Review Cadence & Governance
Intent. The operating rhythm. Without cadence the register rots; with cadence it becomes the heartbeat of the program.
At every Council meeting (bi-weekly)
- Every P0 risk reviewed with owner present.
- New risks added in the preceding two weeks ratified.
- Closed risks removed with a closure statement on file.
Quarterly
- Full register reviewed; P1 risks re-scored.
- Exposure totals rolled up and reported to the Executive Sponsor.
- Materiality threshold re-confirmed.
Annually
- Categories reviewed; new categories added as needed.
- Scoring scales recalibrated against incident history and peer benchmarks.
- Register reported to the board with rollup and trend.