Testing · worksheet · CSVtoCSA editorial

AI performance evaluation

Version 2.0 · Updated 2026-09-21 · Testing

Record issue-level results and retain a traceable basis for metrics and the decision.

Adapt this template to your intended use, applicable requirements, and approved procedures.

When to use it

Use when you need to record issue-level results and retain a traceable basis for metrics and the decision.

Information needed before starting

  • Defined AI use, authority limits and assessed configuration
  • Controlled sources and independent reference results relevant to this worksheet
  • Applicable risk assessment, acceptance basis and responsible reviewers

Field instructions

  • Requirement or risk reference: Link the requirement and failure being evaluated.
  • Test category: State normal, negative, boundary, source, repeatability or other defined category.
  • Reference result: Record the independently established expected finding and its source.
  • AI result: Record the actual finding or omission and execution/configuration identifiers.
  • Severity: Use the predefined local rubric and keep critical results separate.
  • Outcome: Record correct, false, missed or unresolved, with adjudication rationale.
  • Deviation reference: Link failed criteria and required actions; do not hide failures from totals.
  • Conclusion: Explain permitted reliance, exclusions and unresolved uncertainty.
  • Units and design: Record distinct documents, reference issues and repeated runs separately; identify dependencies.

Completed fictional example

Synthetic T-01 includes 12 documents and 40 reference issues: 10 critical and 30 major. The AI reports 38 findings: 32 correct and six false. Eight issues are missed, including two critical. Precision 84.2%; recall 80%; critical recall 80%. The rows below are illustrative extracts, not the entire 40-issue register.

Requirement / riskTest categoryReference resultAI resultSeverityOutcomeDeviationConclusion
REQ-01 / R-01Critical omissionProtocol must challenge specified alarm conditionNo candidate findingCriticalMissedDEV-01Expanded reliance unsupported
REQ-02 / R-02Unsupported statementNo approved source requires screenshot for every testClaims every test needs screenshotMajorFalseDEV-03Reject unsupported claim
REQ-01 / R-01Requirement mismatchAcceptance criterion differs from approved requirementIdentifies mismatch with correct sourceMajorCorrectNoneEvidence for this case only

Blank template

System / record ID: ____________________

Prepared by / date: ____________________

Required review / approval under local procedure: ____________________

FieldYour entry
Requirement or risk reference____________________
Test category____________________
Reference result____________________
AI result____________________
Severity____________________
Outcome____________________
Deviation reference____________________
Conclusion____________________
Units and design____________________

Blank results or assessment rows

Requirement / riskTest categoryReference resultAI resultSeverityOutcomeDeviationConclusion
________________________________________________________________________________________________________________________________________________________________
________________________________________________________________________________________________________________________________________________________________
________________________________________________________________________________________________________________________________________________________________
Relevant regulations and guidance

These sources apply within their stated scope. The suggested worksheet fields, test designs and fictional decisions are practitioner recommendations, unless a source requirement is expressly identified. Completing a template does not establish compliance.

Computer Software Assurance for Production and Quality Management System Software ↗

Regulatory guidance / GMP guideline · United States · February 2026

Scope: Medical-device manufacturers assuring software used in production or their quality management system.

Relevance: For medical-device production or QMS software, supports selecting assurance activities from intended use, risk and available evidence. It is nonbinding guidance and does not determine other sectors’ obligations.

Status: Final / published · Checked 2026-09-21

Publication identity, scope and status checked against the linked official source. This is not an independent audit of every retained guide statement.

Read source details and applicability →

EudraLex Volume 4, Annex 11 — Computerised Systems ↗

Regulatory guidance / GMP guideline · European Union · January 2011 revision

Scope: Computerised systems supporting activities in the applicable EU pharmaceutical GMP context.

Relevance: For computerised systems used in EU GMP activities, informs lifecycle, supplier and record controls. Confirm applicability to the actual activity; the example does not establish it.

Status: Final / published · Checked 2026-09-21

The Commission index confirms the January 2011 operative revision. The linked PDF could not be retrieved in this check; retained detailed section mappings need review against an authorized copy.

Read source details and applicability →

Artificial Intelligence Risk Management Framework (AI RMF 1.0) and NIST AI 600-1 ↗

Industry guidance / framework · United States · AI RMF 1.0 (2023); GenAI Profile (2024)

Scope: Cross-sector AI governance and risk management, including generative AI.

Relevance: A voluntary framework for describing AI risks, evaluation and ongoing management. Its suggested practices are not regulatory requirements.

Status: Final / published · Checked 2026-09-21

Publication identity, scope and status checked against the linked official source. This is not an independent audit of every retained guide statement.

Read source details and applicability →
Was this useful? Leave feedback

Was this resource useful?

Was this template clear and useful? Tell us which instruction or field could be improved.

Loading contribution options…

Questions and moderated discussion

Questions and discussion

Ask a question or share a perspective. Contributions are reviewed before publication.

Loading contribution options…

Suggest a correction

Sent privately to the editorial moderation queue. Your account email and correction are not published as a comment. Do not include confidential or personal information.

Resource: AI performance evaluation

Loading sign-in status…

Correction details