AI Use Policy
Last Updated: May 2025
We leverage artificial intelligence (AI) technologies to enhance our services while maintaining ethical standards and legal compliance. This policy outlines our approach to AI development and deployment.
1. Principles of AI Use
We adhere to these core principles when developing or implementing AI solutions:
- Human Oversight: AI systems augment but never replace human judgment
- Fairness: Proactive measures to prevent algorithmic bias
- Transparency: Clear disclosure of AI use where appropriate
- Accountability: Designated responsibility for AI system outcomes
- Privacy Protection: Compliance with data protection regulations
2. Types of AI We Use
Generative AI
For content creation support with human review:
- Drafting assistance (emails, reports)
- Code generation with developer validation
- Data analysis visualization
Predictive Analytics
For service improvement:
- Workflow optimization
- Resource allocation forecasting
- Anomaly detection in system operations
Human-in-the-Loop Requirement
All AI-generated outputs undergo human review before implementation in client-facing materials or decision-making processes. We maintain audit trails of significant AI-assisted work products.
3. Data Handling
When using AI systems, we:
- Never input sensitive client data without explicit consent
- Use anonymized datasets for model training where possible
- Review third-party AI providers' data policies (e.g., OpenAI, Anthropic)
- Maintain records of data sources for audit purposes
4. Third-Party AI Tools
We carefully evaluate external AI services for:
- Compliance with our privacy standards (Privacy Policy)
- Data retention and deletion policies
- Security certifications (SOC 2, ISO 27001)
- Geographic data processing locations
Current tools we use include [List tools with brief purpose, e.g., "OpenAI API for text processing"].
5. Quality Assurance
Our AI quality framework includes:
- Regular accuracy testing against control benchmarks
- Bias detection protocols for demographic fairness
- Version control for all production AI models
- Clear documentation of system limitations
6. Staff Training
We provide ongoing AI training covering:
- Appropriate use cases and limitations
- Prompt engineering best practices
- Identification of hallucinations/fabrications
- Escalation procedures for uncertain outputs
7. Policy Updates
This policy will be reviewed biannually to reflect:
- Technological advancements
- Regulatory changes (e.g., EU AI Act)
- Internal process improvements