HIPAA, COPPA, GDPR, GLBA, FCRA, ECOA, Title VII, WARN
The one-paragraph answer
Sector rules AI compliance is the set of pre-existing federal statutes and regulations that now govern how AI can be used in specific regulated sectors. HIPAA covers healthcare AI. COPPA covers children's AI. GDPR covers EU personal data AI. GLBA covers financial-institution AI. FCRA covers consumer-report AI. ECOA covers lending AI. Title VII covers employment AI. The WARN Act covers layoff AI. None of these laws mention AI directly. All of them apply to it.
Executives were told AI is unregulated. They believed it. Then they discovered that HIPAA, COPPA, GDPR, GLBA, FCRA, ECOA, Title VII, and WARN all apply to how they use AI, even though none of these statutes mention AI. The pain is that AI does not create a new regulatory island. It sits inside every existing sector rule. If your industry has federal regulation, that regulation applies to your AI. If your data category has federal regulation, that regulation applies to how you use it in AI. The compliance job doubled without doubling the compliance budget.
Eight major statutes and regulations shape how AI can be used in regulated contexts. Each is covered in detail on its own page (linked below), but the common thread is: existing law applies. AI does not exempt you from HIPAA if your AI touches PHI. AI does not exempt you from ECOA if your AI decides credit. AI does not exempt you from Title VII if your AI screens candidates. Every existing rule stands, and AI amplifies both the compliance burden and the enforcement risk.
Click into each rule below for detailed compliance guidance.
Because the pattern of AI enforcement in the United States is: agencies enforce existing law against AI first, then Congress or states may add AI-specific requirements later. If you comply only with new AI laws, you have missed most of the actual enforcement landscape. Sector rules are where most AI cases are being brought, most investigations are being opened, and most settlements are being paid.
The academic literature on sector rules is ahead of most corporate practice, and it is unusually blunt. Two findings are worth putting in front of any executive who thinks this is a compliance formality.
“all those who are involved in the research, development and maintenance of AI systems have social and ethical responsibilities”
That is the gap between having AI and governing it. The second finding is the one that tends to change the room.
“Algorithmic biases can result in discriminatory outcomes, reinforcing societal inequalities and reputational risks for businesses.”
Neither of these is a fringe position. Both come from peer-reviewed work, and both describe the condition most organisations are actually in when the question about sector rules arrives from the board, the buyer, or the regulator.
This is the sequence that works, and it is not the sequence most organisations choose. They start with the framework and work backwards toward reality. Start with reality.
Done in this order, sector rules becomes tractable. Done out of order, it becomes a document nobody uses and a control nobody exercises.
By industry, data category, and function. Healthcare organizations face HIPAA. Financial institutions face GLBA and often FCRA/ECOA. Consumer-facing businesses handling children's data face COPPA. Employers face Title VII, ADEA, ADA, GINA, and WARN. Any organization touching EU users faces GDPR.
Yes. Vendors that process regulated data on behalf of a covered entity typically face flow-through obligations through business associate agreements (HIPAA), data processing agreements (GDPR), or vendor management requirements (banking).
Volume III of The Operating Discipline for AI Library™ includes sector-specific addendums for healthcare, financial services, employment, and children's data. The AI Business Enablement Audit™ identifies which sector rules apply to your specific operations.
The detail pages below each take one component of sector rules and answer the same four questions: what it actually is, what it requires of you, why it matters commercially and legally, and what a defensible position looks like. Read the one that maps to your exposure first. The others become relevant as your AI footprint widens.
Executives ask, reasonably, where to start. The sequence that works is the same one every time, and it is not the sequence most organisations choose. Start with an inventory: you cannot govern AI you cannot list, and almost every organisation we assess is using more AI than its leadership believes. Then rank by consequence, not by volume, because the tool that makes one high-stakes decision a week carries more exposure than the one that drafts a thousand emails.
Only then assign an owner. Not a committee, an owner, named, with the authority to stop a deployment. Governance without a person who can say no is documentation, not control. With those three steps done, the specific requirements of sector rules become tractable, because you now know what you have, what matters, and who answers for it.
The organisations that struggle are the ones that begin with the framework and work backwards toward reality. The frameworks are the map. The inventory is the territory. Start with the territory.
The authoritative texts and agency pages behind this summary. We keep this page current, but where a compliance decision turns on exact wording, read the source. Anything concerning sector rules that carries legal consequence should be confirmed against the enrolled text or the issuing body, not against a secondary summary, including this one.
The AI Business Enablement Audit™ measures your organization against every framework in this library, including Sector Rules, and delivers a defensible governance dossier. Start or finish your audit below.
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