Annex IV of the EU AI Act is often mentioned early in compliance discussions, usually in a way that creates unnecessary pressure.
Teams hear “Annex IV” and immediately think of heavy documentation, conformity assessment, or regulatory audits. That reaction is understandable, but it skips an important step. Annex IV is not a universal requirement, and it is not a starting point.
To understand Annex IV properly, it helps to first understand why it exists.
The EU AI Act is built around proportionality. Systems that create higher risks are subject to more structured obligations. Annex IV fits into this logic. It defines the technical documentation that must exist for certain AI systems, mainly those classified as high-risk.
In other words, Annex IV does not apply to every AI system. It applies only after two conditions are met.
First, the system must fall within the scope of the Act.
Second, it must qualify as high-risk under the Regulation.
If either of those conditions is not met, Annex IV does not apply.
Annex IV itself is not a template. It is a list of information categories that must be documented so that authorities can understand how a high-risk AI system was designed, developed, and intended to be used.
At a high level, Annex IV expects clarity around things such as the system’s purpose, its design choices, how it was trained and tested, and how risks were identified and mitigated. The focus is not on perfection. It is on traceability and accountability.
What matters is that someone reviewing the documentation can reasonably understand what the system does, what its limitations are, and how risks are controlled.
One common misunderstanding is assuming that Annex IV documentation is something to be created at the end of development.
In practice, most of the information required by Annex IV already exists implicitly during product development. Teams make decisions about intended purpose, data sources, model updates, performance metrics, and human oversight long before anyone mentions regulation.
Annex IV simply requires those decisions to be recorded and explained in a structured way.
This is why teams that treat Annex IV as a late compliance exercise often struggle. They are forced to reconstruct decisions that were never clearly documented. Teams that approach it as a design trace tend to find it much more manageable.
Another point that often causes confusion is who is responsible for Annex IV.
The primary responsibility lies with the provider of a high-risk AI system. This is the entity that develops the system or places it on the market under its name. Deployers do not usually create Annex IV documentation, but they may rely on it to understand the system they are using and to meet their own obligations.
In practice, this means startups building AI products are more likely to face Annex IV obligations than companies merely using third-party tools, assuming those tools are not being modified or repurposed in a way that changes their role.
It is also important to understand what Annex IV is not.
It is not a public disclosure document.
It is not a marketing artifact.
It is not a guarantee of compliance.
It is technical documentation intended for regulators and conformity assessment bodies, used when necessary to verify that high-risk systems meet the requirements of the Act.
Treating it as anything else usually leads to confusion.
For teams trying to plan realistically, the most effective approach is to delay Annex IV work until it is actually relevant, without ignoring it entirely.
A sensible sequence looks like this:
- identify AI systems and intended purposes
- clarify roles under the Act
- perform a high-risk screening
- only then assess whether Annex IV applies
Once Annex IV is confirmed as relevant, documentation can be built incrementally, aligned with product development rather than bolted on later.
This approach keeps effort proportional and avoids unnecessary work.
Annex IV matters, but only at the right time and for the right systems.
Understanding when it applies is what turns it from a source of anxiety into a manageable engineering and governance task.
