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Businesses should start AI compliance by listing the systems they use or provide, what each system is intended to do, where it is offered or used, and the organization’s role in its supply chain. Those facts—not simply whether a tool is called “AI”—help determine which legal duties may apply. The EU AI Act is one important example, but it does not create a single checklist for every business or replace privacy law. NIST’s AI Risk Management Framework can support governance, but it is voluntary guidance, not a regulation.
What does AI regulation mean for your business?
AI regulation is a set of legal obligations that can depend on the market involved, the system’s purpose and risk category, and what the organization does in relation to that system. A company that develops or supplies an AI system may have different responsibilities from one that deploys a system in its operations. A business can also have obligations under privacy or sector-specific laws even when a particular AI-specific rule does not apply.
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Begin with an inventory rather than a general policy statement. Record systems developed in-house, purchased, embedded in other products, or accessed through a service. Include pilots and systems used by employees, not only tools formally approved by IT. For each entry, document the following:
- System and provider: product or model name, vendor, version if known, and whether the organization built or materially changed it.
- Intended purpose and actual use: what the system is designed to do and the decisions, recommendations, or content it supports in practice.
- Markets and locations: where the system is offered, deployed, or used, and which entities in the organization are involved.
- Organizational role: whether the organization acts as provider, deployer, or another kind of actor under the relevant law.
- Data and decisions: what information enters the system, whether it includes personal or sensitive data, and who may be affected by its output.
- Controls and ownership: accountable business owner, review and approval records, human oversight, monitoring, and incident-handling arrangements.
This inventory gives legal, privacy, security, and business teams a common basis for deciding what to assess next. A vendor’s description of a tool is useful evidence, but it does not by itself establish how the organization uses it or settle the organization’s legal role.
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Does the EU AI Act apply to your company?
The EU AI Act sets harmonized rules for AI systems and general-purpose AI models placed on the EU market. It prohibits certain practices, establishes requirements and operator obligations for high-risk systems, and sets transparency rules. The Act is risk- and role-based: applicability and duties depend on the system, its intended purpose, and the organization’s role. It should not be read as imposing identical requirements on every company or every use of AI.
Use the following questions to decide which issues need a closer legal assessment. They are an initial screen, not a substitute for checking the Act’s definitions, exceptions, and current implementation rules.
| Question | What to establish |
|---|---|
| Where is the system offered or used? | Identify the relevant markets and deployments. The Act’s rules concern systems and models placed on the EU market; assess the facts against the Act’s scope rather than relying only on the company’s headquarters. |
| What is the intended purpose? | Describe the function and decisions the system supports. Check whether that purpose could bring it within a defined high-risk category or a prohibited practice. |
| What is your role? | Establish whether the organization provides, deploys, or otherwise participates in the system’s value chain. Different roles can carry different obligations. |
| What information is processed? | Identify personal and sensitive data, data flows, and affected people. Assess privacy duties alongside AI-specific rules. |
| When does the relevant duty apply? | Check the provision, any transition rule, and amendments in force for the specific system and actor. The Act’s obligations do not all share one application date. |
| What governance is in place? | Check whether risk review, documentation, accountability, human oversight, ongoing monitoring, and incident processes match the system and role. |
If a system may fall into a prohibited or high-risk category, or if the organization supplies a model or system to others, obtain a role-specific assessment before relying on a broad internal classification. Legal applicability cannot be inferred just from a tool’s marketing label or from an organization-wide “low risk” designation.
How does AI regulation affect privacy?
The EU AI Act does not displace EU personal-data, privacy, or communications-confidentiality law for data processed in connection with the Act. AI compliance therefore does not answer the separate question of whether collecting, sharing, retaining, or using particular data is permitted under applicable privacy rules.
For each use case, map what data is sent to the AI system, why it is processed, who can access it, and whether it is retained or used for further purposes. Consider the applicable privacy requirements for the relevant jurisdictions and the organization’s role in processing. A system can raise privacy concerns even if it is not classified as high-risk under the AI Act; conversely, satisfying a privacy review does not establish compliance with AI-specific duties.
What do the general-purpose AI rules require, and when?
General-purpose AI model provider obligations are a distinct part of the EU AI Act. They should not be treated as duties that automatically apply to every business employee using an AI service. The European Commission says the relevant provider obligations entered into application on 2 August 2025. Its summary identifies technical documentation, a copyright policy, and a public summary of training content among the requirements for covered providers.
Providers of models with systemic risk have additional duties identified by the Commission, including risk assessment and mitigation, incident reporting, and cybersecurity measures. Whether a company is a covered provider, and whether a model meets the applicable systemic-risk criteria, must be assessed under the Act and current guidance.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsThe Commission says its enforcement powers for general-purpose AI provider obligations apply from 2 August 2026. Its broader overview also reports that the AI Omnibus entered into force on 27 July 2026. These dates describe different milestones; an entry-into-force date is not, by itself, the application date for every amended or existing obligation. High-risk-system and transparency requirements have their own application timing and transition rules. Check the current consolidated legal text and Commission implementation material for the precise provision and date relevant to a system before making a compliance decision.
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Can NIST’s AI Risk Management Framework help?
Yes—as a governance aid, not as a substitute for law. NIST describes AI RMF 1.0 as voluntary guidance intended to help organizations incorporate trustworthiness considerations into the design, development, use, and evaluation of AI products, services, and systems. NIST also says the framework is being revised, so organizations should check its current status when adopting it.
NIST’s listed trustworthiness dimensions can help teams organize reviews across an AI system’s lifecycle:
- Reliability: whether the system performs consistently for its intended use.
- Safety and security: whether foreseeable harms and security weaknesses are addressed.
- Accountability and transparency: whether responsibilities, system behavior, and important limitations are made clear to relevant people.
- Explainability: whether outputs can be understood to a degree appropriate to the use and its consequences.
- Privacy enhancement: whether privacy risks are considered in system design and operation.
- Fairness: whether harmful bias is identified and managed.
These dimensions can inform internal reviews, procurement questions, documentation, and monitoring. They do not determine whether an AI Act requirement applies, nor do they make a voluntary framework legally binding.
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What should businesses do to manage AI risk?
- Inventory systems and uses. Assign an owner to each system and record its purpose, provider, data inputs, users, affected people, and deployment markets.
- Map roles and jurisdictions. For each use, identify the organization’s role and assess relevant laws in every market involved. Do not assume that one entity’s assessment covers every affiliate or deployment.
- Screen purpose and risk. Check for prohibited practices, defined high-risk categories, transparency duties, and any rules specific to general-purpose AI providers.
- Review privacy and data flows. Bring privacy specialists into the assessment to examine the data collected, disclosed, retained, and used by the system, alongside AI-specific requirements.
- Set controls that match the use. Document approvals and responsibilities, establish human oversight where appropriate, and define monitoring, complaint, and incident-escalation routes.
- Track dates and changes. Record which obligation applies to which system and role, its relevant application date, and any transition provision. Revisit the assessment when the system, purpose, provider, deployment market, or law changes.
Because the rules differ by jurisdiction and can change, use this framework to identify the questions that need answers—not to declare a system compliant. The EU AI Act and NIST AI RMF do not provide a complete account of US federal, state, or sector-specific rules, or of laws in every other country. Have qualified counsel or compliance specialists verify the requirements for the organization’s specific markets and uses.
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