AI governance record

AI Inventory Generator

Create a practical AI system inventory before compliance work turns into scattered notes. Add each AI system, classify data and decision impact, identify missing evidence, and export a CSV or printable report.

Add an AI system

The inventory is saved only in this browser. It is useful for intake, launch review, renewal review, and preparing evidence before legal, security, or compliance review.

Data handled by the AI system
Evidence already available

Inventory table

First record

Know what AI exists

Start with the systems, vendors, owners, data, lifecycle, and decision impact that matter most.

Evidence

Find missing proof

The tool highlights gaps like missing owner, logging, vendor review, disclosure, and EU role notes.

Next steps

Connect to review

Use the inventory to decide which systems need risk classification, disclosure, vendor review, or training.

Disclaimer: AI Compliance Kit provides initial self-assessment tools and educational content. It does not provide legal advice, certification, or a guarantee of compliance.

practical AI compliance self-assessment

Practical notes for AI Inventory Generator

AI Inventory Generator | AI Compliance Kit is maintained for founders, product managers, compliance owners, agencies, and small teams building AI workflows who need AI governance workflow. The goal is to help visitors complete a real task and leave with an AI inventory, risk note, disclosure draft, vendor question set, policy outline, or review workflow report, not only read a generic summary.

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Define the system

Start by naming the AI feature, users, decision impact, data categories, vendors, and the team member responsible for maintaining the review record.

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Separate triage from advice

Use the generated output as first-pass operational triage. Legal, medical, hiring, credit, education, biometric, and public-sector uses still need specialist review.

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Keep evidence

Save the output, assumptions, date, source links, and reviewer notes so the team can explain why a risk level, disclosure, or vendor question set was chosen.

Before relying on this page

  • Review high-impact use cases manually.
  • Keep policies and disclosures aligned with the real product behavior.
  • Re-run the workflow when vendors, data, or user impact changes.

Review record

How to use AI Inventory Generator in an AI compliance file

A compliance tool is useful when it leaves a traceable record. The output should name the AI system, explain the assumptions, and show what the team still needs to verify with product, legal, security, or vendor owners.

Describe the real system

Record the feature name, user group, decision impact, data sources, vendor dependencies, and the human owner. A generic "chatbot" label is rarely enough. A hiring assistant, support summarizer, medical triage bot, and product recommender can have very different risk profiles even if they all use language models.

Separate signal from conclusion

Treat this page as first-pass triage. It can flag high-risk areas, transparency duties, missing evidence, and questions to ask a vendor. It should not be treated as legal approval, clinical advice, hiring approval, credit approval, or permission to launch without human review.

Save evidence and changes

Save the generated result with the date, reviewer, source links, and unresolved questions. Update the record when the model, data, users, product flow, vendor, or region changes. This keeps the site useful for actual operators rather than only being a static explanation page.

Evidence checklist

  • Document what the AI system does and what it does not do.
  • Record whether the system influences employment, education, credit, public benefits, healthcare, biometric identification, safety, or other high-impact outcomes.
  • Keep vendor documentation, model notes, data descriptions, user notices, human oversight notes, and monitoring plans together.
  • Re-run the review when the product behavior changes, not only when the law changes.
  • Use specialist review for high-impact or regulated workflows before relying on any generated text.