10.7Building a Compliance Test Suite

Step 1: Classify Your AI Features

Map each AI feature to a risk level:

Feature	Risk Classification	Regulation	Required Tests
Customer chatbot	Limited (EU AI Act)	Transparency	Disclosure test
Credit scoring model	High (EU AI Act)	Full compliance	Bias, explainability, logging, human oversight
Product recommendations	Minimal / Algorithm-specific (China)	Varies	Transparency in China
Resume screening	High (EU AI Act)	Full compliance	Bias, fairness, human override

Step 2: Map Requirements to Tests

For each regulatory requirement, create an automated test:

Requirement	Test	Automation Level
Transparency disclosure	Check for AI disclosure text on UI	Fully automated
Human oversight	Verify override mechanism exists	Fully automated
Bias assessment	Run model on diverse demographic test set	Fully automated
Audit trail	Verify log contains required fields	Fully automated
Accuracy monitoring	Run model on labeled test dataset	Fully automated
Risk assessment	Document review	Semi-automated (AI-assisted)
Conformity assessment	Third-party audit	Manual

Step 3: Integrate into CI

# .github/workflows/compliance.yml
name: AI Compliance Checks
on:
  push:
    paths:
      - 'models/**'
      - 'src/ai/**'
      - 'prompts/**'

jobs:
  compliance-tests:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - run: pip install -r requirements-test.txt
      - name: Run compliance test suite
        run: pytest tests/compliance/ -v --junitxml=compliance-results.xml
      - name: Upload compliance report
        uses: actions/upload-artifact@v4
        with:
          name: compliance-report
          path: compliance-results.xml