Assessment · template · CSVtoCSA editorial

AI Use Assessment Template

Version 2.0 · Updated 2026-09-21 · Assessment

Define and evaluate an AI-enabled GxP use, its decision authority, failure scenarios, human review, evidence, monitoring, and revalidation criteria.

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

When to use it

Before pilot or production use of machine learning, generative AI, retrieval-augmented generation, or agentic functions in a regulated process.

Information needed before starting

  • Defined AI task, users, authority and excluded uses
  • Source data, reference cases and model/configuration identifiers
  • Acceptance basis, human-review design and supplier responsibilities

Field instructions

  • Intended use and AI function: Describe the specific task, users, outputs and decisions supported. Identify the assessed environment and limits of reliance.
  • Decision authority and prohibited uses: State what is outside the assessed use or evidence. Explain the consequence and any restriction; do not treat missing information as a pass.
  • Data, population, and reference dataset: Describe dataset provenance, representativeness, independent expected results and exclusions. Keep evaluation material separate from development where appropriate.
  • Failure scenarios and critical misses: Describe a credible incorrect, missing or delayed result and trace it to the affected process, record or decision. Distinguish severity from how often it could occur.
  • Human review design: Define the reviewer’s independent checks, source access, competence and escalation route. Reference evidence that the review detects important errors.
  • Performance measures and acceptance criteria: Define the measures, denominators and risk-based acceptance criteria before execution. Report critical misses separately and explain dataset limitations.
  • Source verification and data integrity: Identify the authoritative source/version for each relied-on output and the checks preserving provenance, completeness and record meaning.
  • Access, audit trail, and supplier responsibilities: Identify the account or role, permitted actions and business justification. Check authorization, inappropriate combinations, inactive accounts and evidence of removal or correction.
  • Testing and release conditions: Identify the assessed configuration, representative data, selected activities and expected results. Include abnormal and recovery paths and explain remaining coverage gaps.
  • Monitoring, stop, and revalidation criteria: Define changes or events that reopen this assessment, the responsible role and the required response or review date.

Define the AI task and prohibited actions at feature level.

Identify decision authority and realistic failures, including critical misses.

Specify reference data, metrics, acceptance criteria, and human-review effectiveness.

Control model, prompt, retrieval, data, tools, access, monitoring, and change.

Completed fictional example

Fictional teaching example; this is not an executed or approved validation record.

FieldCompleted example
Intended use and AI functionDraft nonauthoritative validation-protocol review comments from permitted documents
Decision authority and prohibited usesQualified reviewer disposes findings; AI cannot approve, reject, sign, or release a document
Data, population, and reference datasetApproved English-language protocol types with independently established reference findings
Failure scenarios and critical missesMissed approval, false traceability gap, wrong source version, unsupported compliance claim
Human review designReviewer sees source passage, requirement, and rationale and can accept, reject, or request clarification
Performance measures and acceptance criteriaCritical-finding recall, false findings, citation correctness, performance by issue type, and reviewer detection
Source verification and data integrityImmutable source version and page/section reference retained with the potential finding
Access, audit trail, and supplier responsibilitiesRole-restricted use; input, version, output, disposition, and change recorded
Testing and release conditionsRepresentative challenge set and human-workflow study; scanned handwritten records excluded
Monitoring, stop, and revalidation criteriaStop on critical-miss threshold, source failure, unauthorized action, or material model/prompt/parser change

Blank template

System / record ID: ____________________

Prepared by / date: ____________________

Required review / approval under local procedure: ____________________

FieldYour entry
Intended use and AI function____________________
Decision authority and prohibited uses____________________
Data, population, and reference dataset____________________
Failure scenarios and critical misses____________________
Human review design____________________
Performance measures and acceptance criteria____________________
Source verification and data integrity____________________
Access, audit trail, and supplier responsibilities____________________
Testing and release conditions____________________
Monitoring, stop, and revalidation criteria____________________
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 →
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