A structured AI risk register and assessment worksheet for ranking AI use cases by data exposure, impact, human review, vendor dependency, and control strength.
Rank AI use cases instead of treating all AI activity the same
Identify where sensitive data, automated decisions, or weak review creates risk
Give management a clearer view of the AI risks that need action
Proof points
Focuses on practical risk signals: data sensitivity, decision impact, user scope, vendor dependency, and human review.
Creates a record that can support policy review, management reporting, and future compliance work.
Helps small teams avoid overbuilding while still documenting real AI risks.
Asset proof
DOCX implementation guideRedacted render from the editable DOCX implementation document included after purchase.Open redacted previewXLSX operating trackerRedacted render from the structured XLSX tracker included after purchase.Open redacted preview
Buyer confidence
Real editable filesEach paid product includes a Markdown delivery document plus editable DOCX and XLSX assets where the product calls for documents, registers, trackers, or checklists.Redacted asset previewsProduct pages show redacted renders from the delivered DOCX/XLSX files so buyers can inspect structure without exposing the paid content publicly.Verified digital deliveryOrder pages and downloads require server-side Stripe payment verification before files are unlocked.Internal-use licenseTemplates may be adapted for internal commercial use inside one buyer organization unless a product states a narrower rule.
Quality standard
Implementation-oriented language with owners, decisions, review cadence, and escalation paths.
Editable DOCX documents for policy, rollout, review, and operating guidance.
Structured XLSX trackers or registers with example rows, status fields, owners, dates, and evidence prompts.
Public samples and redacted file previews before checkout.
Buyer-fit and not-a-fit guidance so teams understand when professional review is still needed.
Preview
Risk fields: use case, owner, system, users, data category, output use, decision impact, human review, vendor, controls, residual risk.
High-risk signal: AI output affects employment, credit, health, access, legal rights, pricing, eligibility, or customer-impacting decisions.
