PRACTITIONER METHOD

Practical software assurance playbook

Validating AI-Enabled GxP Systems

A controlled path from context of use and human authority to evaluation evidence, release boundaries, monitoring, and stop conditions.

Professional interpretationEducational practitioner method · Quality review required for case-specific use

Validation process

Apply the lifecycle controls

  1. 01

    Intended Use

    Assessment
    Specify the users, population, data, AI task, output, decision influenced, environment, exclusions, and prohibited actions.
    Expected record
    Feature-level intended use with permitted and prohibited reliance.
  2. 02

    GxP Assessment

    Assessment
    Identify the regulated process, record, calculation, control, or decision affected by the AI-enabled use.
    Expected record
    Documented GxP applicability, scope, exclusions, and accountable owner.
  3. 03

    Part 11 and Records

    Assessment
    Determine electronic-record and electronic-signature reliance from the predicate-rule record and configured workflow.
    Expected record
    Record inventory, Part 11 rationale, retention, accurate-copy, signature, and audit-trail requirements.
  4. 04

    AI Role

    Assessment
    Determine whether the model retrieves, extracts, predicts, drafts, recommends, decides, or executes.
    Expected record
    Authority map showing deterministic, AI, and human responsibilities.
  5. 05

    Decision Authority

    Assessment
    State which outputs inform a person, change process state, create a record, or execute an action, and which decisions remain prohibited.
    Expected record
    Approved decision-authority matrix with confirmation, escalation, and stop controls.
  6. 06

    Supplier and Service Assessment

    Assessment
    Define the supplied model or service, release controls, available evidence, customer responsibilities, change notice, data terms, and known limitations.
    Expected record
    Supplier assessment with accepted evidence and customer-controlled gaps.
  7. 07

    Human Oversight

    Assessment
    Define reviewer competence, time, source visibility, independence, escalation, and the consequences of automation bias.
    Expected record
    Oversight procedure and representative-user challenge results.
  8. 08

    Failure Modes

    Assessment
    Trace omission, unsupported content, wrong source/version, subgroup failure, instability, prompt injection, overreliance, and action errors.
    Expected record
    failure scenarios linked to controls and critical acceptance criteria.
  9. 09

    Evaluation Dataset

    Assessment
    Represent the approved population, critical edge cases, realistic prevalence, source quality, subgroups, and prohibited contexts.
    Expected record
    Versioned dataset specification, provenance, exclusions, and leakage review.
  10. 10

    Expected Results and Acceptance Criteria

    Assessment
    Predefine correct behavior, permitted variation, unacceptable events, denominators, thresholds, confidence, reviewer recovery, and the action taken when criteria fail.
    Expected record
    Approved evaluation protocol with objective acceptance and stop rules.
  11. 11

    False Positives, False Negatives, and Critical Misses

    Assessment
    Measure error by issue type and consequence; examine every critical miss instead of relying on one aggregate accuracy score.
    Expected record
    Confusion matrix, precision, recall, critical-event review, subgroup results, disposition, and retest traceability.
  12. 12

    Source Verification and Data Integrity

    Assessment
    Verify source identity, version, provenance, completeness, transformation, retrieval, citation, retention, and reconstruction of inputs and outputs.
    Expected record
    Source-grounding tests, data-flow record, lineage, integrity controls, and accurate-copy evidence.
  13. 13

    Controls

    Assessment
    Constrain authority through source filters, citations, deterministic gates, permissions, confirmation, logging, and kill switches.
    Expected record
    AI use and control requirements with tested preventive and detective measures.
  14. 14

    Access, Audit Trail, and Recovery

    Assessment
    Restrict input, output, configuration, approval, and tool permissions; retain reconstructable activity and a tested safe fallback.
    Expected record
    Role challenge, audit-trail review, record reconstruction, failure handling, and recovery evidence.
  15. 15

    Release Decision

    Assessment
    State the supported use, open uncertainty, conditions, fallback, authorized approver, and restart criteria.
    Expected record
    Signed release narrative and reconstructable evidence package.
  16. 16

    Monitoring

    Assessment
    Detect changes in data, use, supplier model, prompts, retrieval, performance, user response, and critical-event rate.
    Expected record
    Monitoring plan with thresholds, owners, stop conditions, and reassessment criteria.
  17. 17

    Change Control and Revalidation

    Assessment
    Assess model, prompt, retrieval, data, interface, permission, supplier, and intended-use changes before continued use.
    Expected record
    Change-impact decision with regression, restriction, revalidation, rollback, or no-action rationale.
  18. 18

    Periodic Review and Retirement

    Assessment
    Confirm that use, controls, evidence, monitoring, access, supplier status, records, and assumptions remain current; plan controlled withdrawal when they do not.
    Expected record
    Periodic-review conclusion, open actions, reassessment criteria, and retirement or record-migration plan.

Release gate

Before the decision is defended

  • Critical errors are defined in operational terms and independently challenged.
  • Human review is designed and tested as a control rather than assumed.
  • The approved approved conditions of use and prohibited actions are explicit.
  • Monitoring can locate affected records and trigger suspension or reassessment.

Scope and limitations

What this playbook does not establish

  • A high aggregate accuracy score is not a release conclusion.
  • This playbook does not replace clinical, safety, privacy, security, or legal evaluation.
  • Model and supplier opacity may require narrower use, stronger controls, or a no-release decision.

Use applicable regulations, final guidance, organizational procedures, and subject-matter review for the actual system and jurisdiction.