Here we have a breakdown of the core differences we need to apply with our UK vs our USA policies.
| Area | Description |
|---|---|
| Human in the loop | AI is a co-pilot. Employees are responsible for outputs and decisions. |
| Transparency | AI use must be disclosed, especially when outputs affect people. |
| Security-first | Only approved tools may be used. Tools must meet company and regulatory standards. |
| Bias awareness | All employees must be alert to bias in AI-generated content or recommendations. |
| Training required | All users must complete AI awareness training before using tools. |
| Prohibited actions | Entering personal/sensitive data into public AI tools, generating false/misleading content, or relying blindly on outputs is not allowed. |
| Topic | UK Policy 🇬🇧 | USA Policy 🇺🇸 |
|---|---|---|
| Regulatory Anchor | Anchored in UK GDPR, ICO guidance, and principles of fairness. | Anchored in state-specific laws (e.g. CCPA, CPRA, HIPAA), federal law where applicable. |
| Data Protection Impact Assessment (DPIA) | Mandatory for tools processing personal or sensitive data. Must be completed before adoption. | Not legally required, but a Tool Risk Review form is recommended. Data privacy is assessed during approval. |
| Decision-making automation | Explicitly prohibited to use AI for employment decisions (hiring, promotion) without DPIA + human review. | Same principle applies, but framed as a business risk rather than legal requirement. |
| Language style | More compliance-oriented tone, reflecting UK’s data protection culture. | More risk-oriented and flexible, with emphasis on innovation balanced by oversight. |
| Use of PII | Very strict: No personal or confidential data allowed in AI tools unless assessed via DPIA. | Similar restriction, but framed in terms of specific data types (PII, PHI, etc.) under US law. |
| Governance group | Referred to as the “AI Working Group” and includes HR, Legal, IT, DPO. | Called the “AI Governance Committee.” Structure is less prescriptive. |
| Tool approval criteria | Explicit mention of opt-outs for model training and storage transparency. | Focus on enterprise readiness, opt-out for model learning, and vendor terms. |
| Cultural context | Focus on legal compliance, fairness, and worker protections. | Focus on innovation, security, and avoiding legal risk. Emphasis on exploration with guardrails. |
| Element | UK Policy | US Policy |
|---|---|---|
| Tone | Compliance-driven, cautious, duty-of-care language | Exploration-friendly, with clear boundaries |
| Employee framing | “Here’s how to stay compliant and protect people” | “Here’s how to explore responsibly and avoid risk” |
| Enforcement cues | References to ICO expectations, lawful processing, data minimisation | Emphasis on internal approvals, practical guardrails, ethical norms |
Want to extend your policy? Here’s how you could break guidance down further:
| Role | Additional Guidance |
|---|---|
| Managers | Encourage ethical experimentation, ensure team compliance, flag risks |
| HR | Guide use in hiring/L&D/engagement; assess risks in people-related applications |
| IT/Security | Maintain tool list, assess vendor risk, approve integrations |
| Employees | Use tools for productivity, not decision-making; never enter sensitive data |