AI Risk Register Worksheet for ERP Projects
A risk register is the document that keeps AI project risks visible after the kickoff meeting. This editable worksheet scores each risk on likelihood and impact, rates it high, medium or low, and tracks the owner, mitigation and next review date. Export it to Excel for your PMO.
| ID | Risk description | Category | Likelihood (1-5) | Impact (1-5) | Score | Rating | Owner (role) | Mitigation | Status | Next review | |
|---|---|---|---|---|---|---|---|---|---|---|---|
15 | 3 | ||||||||||
9 | 2 | ||||||||||
8 | 2 | ||||||||||
12 | 2 | ||||||||||
6 | 1 | ||||||||||
6 | 1 |
Scores are judgement calls. Agree the 1-5 scales with your risk team (for example, impact 5 means regulatory breach or plant stoppage) and keep them consistent across projects. Replace the example rows with your own.
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How to use the worksheet
Replace the example rows with risks from your own project. Score likelihood and impact from 1 to 5, and the worksheet multiplies them to give a score out of 25. Scores of 15 or more rate high, 8 to 14 medium, and below 8 low. Assign an owner by role, write a specific mitigation, and set a review date. Sort or filter the exported Excel file by rating before steering committee meetings and focus the discussion on the high rows.
Risk categories that matter for ERP AI
ERP-connected AI mixes traditional integration risks with model-specific ones. Use the categories to make sure the register is not only about technology.
- Data: permissions, stale extracts, poor master data quality
- Security: prompt injection, data leakage, credential handling
- Accuracy: wrong numbers, invented part numbers, outdated documents
- Compliance: export control, privacy law, audit trail gaps
- Operations: duplicate or unintended ERP transactions by agents
- People and vendor: adoption, skills, model or provider changes
Reading the scores
The score is a prioritisation aid, not a precise measure. Two risks with the same score can need different responses: a likely low-impact annoyance may be accepted, while a rare high-impact event may need a hard control. The exposure index shows the average score as a share of the 25-point maximum, which is useful for trend tracking month to month. If the index is not falling after mitigations are marked done, the controls are not working or the risks are being rescored too optimistically.
Common mistakes
Registers fail when risks are vague, owners are teams rather than roles, or mitigations say monitor. Write the risk as cause, event and consequence. Keep accepted risks in the register with an explicit acceptance by the right person. Review the register on a fixed rhythm, such as every steering committee, and close risks only with evidence that the control exists and works.
Frequently Asked Questions
What scale should we use for likelihood and impact?
A 1 to 5 scale is common. Define each level in words, for example impact 5 as regulatory breach or plant stoppage. Using your company's existing enterprise risk scales makes the AI register easier to roll up into corporate reporting.
How many risks should a register have?
For a single AI project, 15 to 30 well-written risks is typical. A longer list tends to hide the important ones. Merge near-duplicates and keep only risks with an owner and a plausible mitigation.
Does this replace a formal AI impact assessment?
No. It is the ongoing tracking tool. A formal assessment, where required by regulation or policy, feeds the register with its findings, and the register tracks mitigation through to closure.
Can I import it into our PMO tool?
Export to Excel or CSV and import it into your project tool. Keep the column names so the next export maps cleanly, and keep dates in a standard year-month-day format.
If you want help stress-testing the high-rated rows, such as permission leakage or agent write-back, Netray can run a short review of your ERP AI design.
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