# Validation of AI-enabled GxP systems
Validating an AI-enabled system means showing, with documented evidence, that each AI function is fit for its intended use and stays that way. QLogix follows GAMP 5 (Second Edition) and computer software assurance principles: effort is scaled to the risk of the function, and the evidence is written for an inspector to follow.
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## What gets defined for every AI function
- Intended use: what the function does, for whom, and what it must never do
- Risk level: what happens if the output is wrong, and who would catch it
- The human control: who reviews and approves the output before it becomes a record
- Acceptance criteria: what good enough looks like, in measurable terms

## What the evidence looks like
- A risk assessment that drives how much testing each function gets
- Documented testing against the acceptance criteria, on representative cases
- Checks that outputs are sourced, labelled as AI-generated and traceable
- Audit trail and access control verification
- A validation report that states what was tested, what was found and what is monitored

## Keeping the validated state
An AI function changes when its model, its prompt or its data sources change. Each of those goes through change control with an impact assessment and regression testing in proportion to risk. Performance is monitored in use and reviewed periodically against the baseline.
EU GMP Annex 22 on artificial intelligence is a consultation draft at the time of writing. We design to its direction and update as final text is published.

## Your qualified people decide
- Your quality unit approves the intended use, the risk assessment and the validation report.
- A function is released for use by a person, not by passing its tests.

## Frameworks this work is built to
- GAMP 5 (2nd ed.)
- FDA CSA guidance
- 21 CFR Part 11
- EU GMP Annex 11
- EU GMP Annex 22 (draft)
- ICH Q9(R1)

## Included
- Intended use
- Risk assessment
- Test evidence
- CSA

## Questions about validation of AI-enabled systems

### How do you validate something that does not give the same answer twice?

By validating the function in its context of use. A drafting function with mandatory human review is tested for whether its outputs are sourced, complete enough to be useful and correctly labelled, across representative cases and against acceptance criteria, instead of for identical output on every run.

### What is the difference between CSV and CSA?

Computerized system validation (CSV) has often been practiced as scripted testing of everything. Computer software assurance (CSA) is FDA's risk-based approach: put the most rigorous assurance where a failure would affect product quality or patient safety, and use lighter, unscripted testing where it would not.

### What happens when the AI model is updated?

The update is handled as a change: impact assessment, regression testing against the acceptance criteria in proportion to risk, approval, and a record of the model version in use for each output.

### Can you validate an AI function we already use?

Yes. The starting point is the same: write down its intended use and risk, find out what evidence already exists, and close the gaps.

## Related services
- QMS digitizationConfigured on the platform that fits your size and product type.
- AI-assisted investigationsThe AI drafts. Your investigators and QA decide.
- Connected quality dataYour QMS linked to plant and lab systems for trending, recurrence detection and earlier signals.
- Agentic workflow automationOrchestrated agents that take on routine quality work across your systems: gathering, checking, drafting and chasing. Each one works inside defined guardrails and hands decisions to your people.

## Talk it through with someone who has run a plant
Bring your backlog, your systems map or one investigation that keeps coming back. We will tell you plainly what we would do and what we would leave alone.
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In the first meeting we cover
- Your current QMS and how it connects to MES, LIMS and ERP
- Where deviations, CAPAs and change controls slow down
- Whether a readiness assessment makes sense, and what it would cover

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Source: https://qlogix.ai/services/validation-of-ai-enabled-systems
QLogix · contact@qlogix.ai · +17146639012