AI risk assessment template Excel
Last reviewed: June 15, 2026 by Grant Holloway.
Free AI Risk Assessment Template (Excel)
Get an editable Excel template for AI inventory, initial risk scoring, stakeholder review, evidence gaps, and remediation ownership.
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Email me the free Excel workbook
Editable .xlsx with example AI use cases, 0-5 risk scoring, evidence gaps, remediation tracking, and SR 26-2 evidence prompts.
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Built for community banks, credit unions, and fintech teams preparing AI governance evidence for compliance, audit, board, and examiner review.
Practitioner reviewed
Grant Holloway
Founder & CEO, AegisAI Compliance
Grant has 18+ years of model risk, regulatory compliance, and AI/ML oversight experience, including model risk and AI governance leadership for a Tier-1 European bank.
Review founder credentialsMapped to SR 26-2 and FFIEC AI governance expectations for banks and credit unions.
The free workbook is a practical starter template. The paid Starter Kit contains the broader AI governance operating package: policy, vendor questionnaire, evidence tracker, board reporting, control mapping, and implementation templates.
Why use Excel for AI risk assessment?
Many banks, credit unions, and fintechs need a practical starting point before they have a dedicated AI governance platform. An Excel workbook gives risk teams a familiar way to inventory AI use cases, collect vendor and model evidence, score gaps, and assign remediation owners.
The goal is not to make the spreadsheet the control environment. The goal is to make AI risk visible enough that teams can decide what needs policy review, vendor due diligence, model risk review, board reporting, or evidence collection.
This page includes a free editable starter workbook for building an AI risk assessment in Excel. The paid Starter Kit adds the broader governance package: policy, vendor diligence, evidence tracking, board reporting, control mapping, and implementation templates.
What the workbook should cover
An AI risk assessment workbook should connect AI use cases to the controls that matter most for regulated institutions: ownership, approval, vendor review, model risk governance, data practices, privacy, security, consumer impact, monitoring, reporting, and remediation.
For vendor AI, the workbook should capture due diligence responses, evidence gaps, contract issues, monitoring requirements, and risk-tiering decisions. For internal or model-driven AI, it should capture intended use, validation status, data sources, performance monitoring, limitations, change history, and issue tracking.
- AI use case inventory
- Vendor and third-party AI review
- Model risk and validation status
- Data, privacy, and security evidence
- Risk scoring and gap prioritization
- Remediation owner and due-date tracking
Regulatory context
The fields in an AI risk assessment workbook should map to the way regulated institutions already organize risk: model governance, third-party oversight, information security, data controls, consumer impact, monitoring, reporting, and remediation evidence.
Model risk fields should be framed around current interagency model risk management guidance, including SR 26-2, which superseded SR 11-7 in April 2026. Vendor review fields should reflect the Interagency Guidance on Third-Party Relationships: Risk Management. Security and operations fields should connect back to FFIEC IT Examination Handbook expectations where AI tools rely on institutional data, infrastructure, or critical third parties.
How to use the template
Start by listing AI-enabled tools, vendor products, pilots, automated decisioning systems, analytics models, fraud tools, customer service systems, and employee productivity tools. Include systems where AI is embedded inside a vendor platform.
Next, classify each item by risk. Customer-impacting, credit, fraud, AML, cybersecurity, compliance monitoring, regulatory reporting, and critical operations use cases should receive deeper review than low-risk drafting or internal productivity uses.
Finally, convert missing or partial answers into remediation work. A good workbook should make it clear who owns the gap, what evidence is required, when the item is due, and where it will be reported.
AI risk assessment template preview
These workbook sections are the core tabs and fields most teams need when turning AI risk into a documented assessment file.
- 1Inventory each AI use case, vendor tool, pilot, and embedded AI feature.
- 2Assign a business owner and a risk or control owner for each AI item.
- 3Classify whether the AI supports customer decisions, controls, reporting, or critical operations.
- 4Identify whether the AI is internally developed, vendor-provided, or embedded in a third-party platform.
- 5Document intended use, limitations, prohibited uses, and approval status.
- 6Record data inputs, sensitive data exposure, retention, and vendor data-use restrictions.
- 7Capture model documentation, validation evidence, monitoring metrics, and change-management status.
- 8Score vendor, model, data, security, consumer-impact, and evidence gaps.
- 9Prioritize high-risk gaps for management, committee, or board reporting.
- 10Track remediation owners, due dates, status, and supporting evidence links.
FAQ
What should an AI risk assessment template in Excel include?
It should include an AI use case inventory, risk tiering fields, vendor and model risk questions, response scoring, evidence prompts, remediation owners, due dates, and status tracking.
Is an Excel AI risk assessment template enough for compliance?
No. A spreadsheet can organize evidence and support internal review, but it does not determine compliance or replace legal, audit, supervisory, privacy, security, or model validation review.
Who should complete the assessment?
The assessment usually requires input from business owners, compliance, risk, vendor management, information security, privacy, model risk, legal, and internal audit depending on the use case.
How often should the template be refreshed?
Refresh it during onboarding, annual or periodic review, material vendor changes, model updates, new data sources, expanded use cases, and before board, audit, or examiner review.
Start with the free workbook, then expand when governance gets real.
Use the emailed Excel workbook to inventory AI use cases, score initial risk, and document evidence gaps. Keep the free workbook as the primary first step; use the Starter Kit when you need the broader operating package for policy, vendor diligence, evidence tracking, board reporting, and control mapping.
Need more than the free Excel template?
The paid Starter Kit adds editable workbooks for AI risk scoring, vendor diligence, control mapping, evidence tracking, board reporting, and remediation ownership.
Related AI governance resources
AI vendor risk assessment template
Review the vendor-specific AI due diligence structure after the main assessment flow.
AI governance readiness calculator
Score your current AI governance program and identify the highest-priority gaps.
SR 26-2 model risk guide
Map workbook evidence fields to current model risk language and SR 11-7 continuity.
AI governance checklist for small banks
Review the 30-question checklist behind the AegisAI readiness framework.
AI governance evidence tracker
Turn gaps into owners, due dates, evidence requirements, and board-ready status.
Important limitation
Free AI Risk Assessment Template (Excel) is for informational and educational purposes only. It does not constitute legal, regulatory, audit, supervisory, model validation, privacy, security, or compliance advice. Institutions should consult qualified counsel and risk, compliance, audit, privacy, security, and model risk professionals regarding their specific obligations.
- Use spreadsheet fields for repeatable review.
- Keep scoring separate from final approval decisions.
- Document evidence for each material gap.
- Refresh the workbook after material AI changes.