With the AI Act's obligations coming into force in stages, many organisations have launched an "AI compliance" project. Some call it "AI governance". Others use the two terms interchangeably.
In practice, they don't mean the same thing. AI compliance is about meeting the legal obligations that apply to your AI systems. AI governance is the internal system that decides how your organisation uses AI, who is accountable, and which risks it is willing to take.
Mixing them up has consequences. An organisation can tick every box of an AI Act checklist and still have no real control over how AI is used across its teams. Another can have a well-designed governance framework and still miss a legal obligation that applies to one of its systems.
What is AI compliance?
AI compliance means meeting the legal and regulatory requirements that apply to AI systems. In the EU, that mainly means the AI Act, but also the GDPR whenever personal data is involved, as well as sector rules (finance, health, employment).
Compliance answers precise questions. For instance, if we're basing the reflexion on the EU AI Act, the type of questions would be:
- What is our role? Provider, deployer, importer or distributor under the AI Act.
- What is the risk level of each system? Prohibited, high-risk, subject to transparency obligations, or minimal risk.
- Which obligations follow? For example, AI literacy (Article 4), transparency towards users (Article 50), or, for high-risk systems, a quality management system (Article 17) and human oversight.
- Can we prove it? Documentation, logs, assessments, contracts.
The stakes are concrete. Under Article 99 of the AI Act, prohibited practices can lead to fines of up to €35 million or 7% of worldwide annual turnover. Breaches of most other obligations, including those for high-risk systems, can reach €15 million or 3%.
Compliance is driven from the outside: the law sets the requirements, and the organisation demonstrates that it meets them. It is measurable, and it has deadlines.
What is AI governance?
AI governance is the set of roles, rules and processes an organisation puts in place to steer its use of AI. It goes beyond what the law requires.
Governance answers different questions:
- What do we want to do with AI, and what do we refuse to do?
- Who decides whether a new tool can be deployed?
- Who owns the risk once it is live?
- What is our risk appetite, and does each use case fit within it?
- How do we stay in control as tools, suppliers and uses change?
Governance is driven from the inside. No regulator imposes a single model, and the AI Act does not create a dedicated function equivalent to the DPO. Each organisation designs the structure that fits its size, sector and culture.
AI compliance vs AI governance: the key differences
| AI compliance | AI governance | |
|---|---|---|
| Purpose | Meet legal obligations | Steer and control the use of AI |
| Driven by | Laws and regulators | The organisation’s strategy and values |
| Scope | Systems covered by the regulation | All AI use, including what the law does not cover |
| Key question | “Are we compliant?” | “Are we in control?” |
| Owned by | Legal, compliance, DPO | Cross-functional: management, business owners, legal, security, data |
| Flexibility | Low: requirements are set by law | High: adapted to size, sector and risk appetite |
| Typical outputs | Classification, documentation, contracts, notices | Policies, roles, decision processes, risk acceptance |
| How it is measured | Audits, documentation, conformity assessments | Coverage of the AI register, review cycles, tracked risk acceptance, training completed |
| Time frame | Legal deadlines & ongoing | Ongoing |
Why the confusion is risky
Compliance without governance has a one-shot approach. The register is filled in once, the assessments are done for the deadline, and six months later the inventory no longer reflects reality. New tools arrive through suppliers, AI features are switched on in existing software, and nobody is in charge of catching them.
Governance without compliance produces a blind spot. Roles and committees exist, but nobody has checked whether a recruitment tool falls under the high-risk category, or whether the contract with the supplier covers the obligations that apply.
There is a third risk, less visible. The AI Act focuses on certain uses. A tool can be minimal risk under the AI Act and still be critical to the business, for example if it is embedded across several systems and a wrong output would be costly. Only governance will catch that.
How AI compliance and AI governance work together
The simplest way to see it: governance is the structure, compliance is one of the things it delivers.
A solid AI governance framework makes compliance sustainable. In practice, it usually rests on four building blocks:
- An AI register. An inventory of AI systems and their use cases, kept up to date. It plays the same role for AI governance as the record of processing activities does for data protection.
- A repeatable assessment. Each new tool or supplier goes through the same steps: what the supplier claims, how the tool will really be used, and what risks follow.
- Clear accountability. The business owner owns the use case and its risk. Legal, data protection and security teams advise and propose measures. Risk acceptance is documented.
- Ongoing review. Systems, suppliers and regulations change. Governance defines when a use case must be reassessed.
Compliance then becomes the output of a system that already works, rather than a separate project restarted at every deadline.
Where to start?
Most organisations are still early. Some rely on recent regulatory delays to start working on this later on. However, the best way is to start building the proper foundations.
A pragmatic starting point:
- Map what already exists: AI tools in use (declared or not), existing policies, and what the business plans to do next.
- Qualify each system: your role and its risk level under the AI Act.
- Assign owners: one accountable person per use case.
- Build on your GDPR program: AI systems that process personal data are already in your register, your DPIAs and your supplier reviews. There is no need to start from scratch.
Build your AI governance and compliance in one place
Dastra helps you build your AI register, qualify your systems under the AI Act, run supplier and use-case assessments, and link everything to your GDPR compliance.