Industry-Specific AI Compliance
Regulated industries have extra rules for AI. This guide covers healthcare (HIPAA), finance (MAS, SEC, PCI-DSS), education (FERPA), legal, and government (FedRAMP). For each: what restrictions apply, what to look for in tools, and common pitfalls. Brief per industry; a starting point, not exhaustive.
Healthcare (HIPAA)
What applies — HIPAA governs protected health information (PHI). AI tools that receive PHI must be HIPAA-compliant. Business Associate Agreements (BAAs) required.
What to look for — Vendor offers BAA. Encryption. Access controls. No training on PHI without explicit agreement. Audit logs.
Pitfalls — Using consumer AI (ChatGPT, etc.) for PHI without BAA. Assuming cloud means compliant. Not all healthcare AI is HIPAA-ready.
Finance (MAS, SEC, PCI-DSS)
MAS (Singapore) — Monetary Authority of Singapore. Guidelines on AI in financial services. Fairness, governance, accountability.
SEC (US) — Securities regulation. AI in advice, trading, disclosure. Rules evolving. Consult counsel.
PCI-DSS — Cardholder data. AI tools that touch card data must not store or transmit card numbers insecurely. Often avoid sending card data to AI.
What to look for — Vendor compliance with relevant regulations. Data handling. Audit trails. No use of AI for regulated advice without proper oversight.
Pitfalls — Using AI for investment advice without proper registration. Sending card data to AI. Assuming general-purpose AI is finance-compliant.
Education (FERPA)
What applies — FERPA protects student education records. AI tools that receive student data must protect it. Consent and access controls.
What to look for — Vendor FERPA compliance. Data handling. No training on student data without consent. Consent mechanisms for minors.
Pitfalls — Using AI for grading or feedback without proper controls. Sharing student data with vendors that train on it. Not getting consent where required.
Legal
What applies — Privilege, confidentiality, conflict of interest. AI that receives client data must protect confidentiality. Some jurisdictions have rules on AI in practice.
What to look for — No training on your data. No sharing with third parties. Data residency. Confidentiality commitments. Some tools offer legal-specific deployments.
Pitfalls — Sending privileged material to consumer AI. Assuming vendor does not train. Using AI for advice without human oversight.
Government (FedRAMP)
What applies — FedRAMP for US federal cloud. AI tools used by government must meet FedRAMP requirements. State and local may have similar.
What to look for — FedRAMP authorization. Or FedRAMP-ready for deployment in government. Compliance documentation.
Pitfalls — Using non-FedRAMP tools for government data. Assuming commercial cloud is sufficient.
The Bottom Line
Regulated industries have extra rules. Map your sector. Check vendor compliance.
Healthcare: HIPAA, BAA. Finance: MAS, SEC, PCI-DSS. Education: FERPA. Legal: privilege, confidentiality. Government: FedRAMP. Common pitfall: using consumer AI for regulated data.