National Enforcement Procedures: What to Expect

Understanding the procedural mechanics of regulatory enforcement is a critical competency for any entity deploying artificial intelligence, advanced robotics, or data-intensive biotechnologies within the European Union. While the Artificial Intelligence Act (AI Act) establishes a harmonized framework of rights and obligations, the actual exercise of regulatory power—investigations, evidence gathering, and the imposition of sanctions—remains largely a function of national authorities. The European Union does not possess a standing “AI Police” with the authority to raid offices or seize servers directly; instead, it relies on a network of Member State regulators who translate the text of the regulation into tangible administrative action. For legal counsel, compliance officers, and system architects, grasping the lifecycle of a national enforcement procedure is not merely a theoretical exercise; it is a prerequisite for operational resilience.

This article dissects the typical procedural steps that a regulated entity can expect when facing scrutiny from a national market surveillance authority. We will trace the trajectory from the initial information request to the finality of appeals, focusing on the interplay between the procedural autonomy of Member States and the harmonized obligations imposed by EU legislation. The analysis draws upon established patterns in GDPR enforcement, the emerging practices under the Digital Services Act (DSA), and the specific procedural mandates outlined in the AI Act, offering a practical guide to navigating the regulatory landscape.

The Anatomy of an Investigation: Initiation and Information Requests

Enforcement rarely begins with a dramatic raid. More commonly, it starts with a subtle but legally binding inquiry. Under the AI Act, the market surveillance authorities (MSAs) are tasked with monitoring the compliance of high-risk AI systems. These authorities possess broad powers to request information, which serves as the primary tool for preliminary assessment. A request for information (RFI) is not a casual email; it is a formal procedural act that triggers specific legal duties for the recipient.

The Formal Information Request

When a national authority suspects non-compliance—perhaps triggered by a whistleblower report, a media investigation, or a post-market surveillance report—it will issue a formal request for information. The AI Act (Article 74) mandates that providers of high-risk AI systems, or their authorized representatives, supply the requested information within a fixed timeframe.

Legal Obligation: Providers must respond to requests for information from the market surveillance authority within a period specified by the authority, which shall be at least 15 days.

In practice, this 15-day deadline is often tight, especially when the request involves complex technical documentation or data logs from legacy systems. It is a common mistake to treat these requests as administrative correspondence. Failure to reply, or replying with incomplete or misleading information, constitutes a separate breach of the regulation, punishable by administrative fines. From a procedural standpoint, the RFI establishes the “file” of the case. The answers provided here will form the baseline against which subsequent evidence is measured. Inconsistencies between the RFI response and later discovered documents can escalate a case from a compliance check to a finding of intentional deception.

Scope and Granularity

The scope of these requests varies significantly across Member States. Authorities in jurisdictions with a longer history of digital regulation, such as France’s CNIL or the Irish Data Protection Commission, tend to issue highly granular RFIs that probe the specific logic of the AI system (e.g., requesting the “prompts in, prompts out” data sets for generative models). In contrast, authorities in newer regulatory ecosystems may focus initially on documentation compliance—checking for the existence of a risk management system or a conformity assessment—before delving into the technical substance of the algorithm.

For the recipient, the strategy must be to treat the RFI as a discovery phase. It is advisable to map the requested data against the organization’s internal knowledge base immediately. If the request asks for “all data used to train the model,” the legal and technical teams must collaborate to define the scope precisely. Ambiguity in the request can be challenged, but silence is dangerous. A proactive approach involves asking for clarifications on the deadline or scope if the request is technically imprecise, thereby creating a procedural record of good-faith cooperation.

On-Site Inspections and the Power of Evidence Handling

If the information request yields unsatisfactory answers, or if the authority reasonably suspects a serious breach that puts public safety at risk, the procedure escalates to physical or remote inspections. This is the phase where the regulatory power becomes most tangible. The AI Act harmonizes these powers, allowing national authorities to enter premises, seize evidence, and conduct interviews.

Entry and Seizure

Article 74(6) of the AI Act grants market surveillance authorities the power to enter and inspect any premises, land, or means of transport of providers or deployers. This includes the right to access data processing systems and to take or obtain copies of information and data.

It is crucial to distinguish between the right to access and the right to seize. Authorities generally have the right to access data on-site (or remotely) to inspect it. They may also have the right to seize physical hardware or servers if there is a risk that evidence might be altered or destroyed. However, the seizure of evidence is a measure of last resort and usually requires a specific judicial order in many Member States, depending on the national transposition of the AI Act and the procedural codes.

Operational Preparedness: Organizations should have a clear protocol for “Regulatory Raids.” This is not about hiding evidence, but about ensuring procedural rights are respected. Who is authorized to speak to the inspectors? Where can the inspectors go? Is there a designated “clean room” for the inspection to avoid contaminating sensitive intellectual property? Having a trained internal team (or external counsel) present during an inspection is vital to ensure that the scope of the inspection is not exceeded.

Handling of Confidential Information

During evidence handling, a tension arises between the regulator’s need to know and the company’s need to protect trade secrets. The AI Act explicitly states that authorities shall preserve the confidentiality of trade secrets and sensitive commercial information. However, in practice, this boundary is often tested.

If an authority requests access to source code or proprietary algorithms, the company can (and should) request the imposition of confidentiality agreements or “clean teams” (where only specific, vetted experts view the code). In some jurisdictions, such as Germany, the Federal Office for Information Security (BSI) has established rigorous protocols for handling such data. In others, the procedural safeguards may be less codified, leading to potential disputes over how evidence is stored, who has access to it, and when it is destroyed or returned.

Corrective Orders and Non-Compliance Measures

Following the evidence gathering phase, the authority will evaluate whether the AI system poses a risk to health, safety, or fundamental rights. If non-compliance is identified, the authority is not necessarily required to jump immediately to fines. The regulatory philosophy is one of “corrective action first,” though this is balanced by the severity of the breach.

The Hierarchy of Interventions

The AI Act provides a graduated scale of corrective measures. The authority will typically issue a formal decision requiring the provider to:

• Bring the system into compliance within a specific timeframe.
• Recall the system from the market.
• Make the system permanently unavailable.

These measures are binding. The “request to rectify” is the most common outcome. The authority will specify the exact deficiencies found (e.g., lack of robustness against adversarial attacks, missing CE marking, or failure to meet data governance requirements) and set a deadline for remediation.

Timeline Sensitivity: The deadline for rectification is a critical variable. In cases involving imminent risk (a risk of death or serious injury), the authority can impose immediate corrective orders, effectively banning the system from operation with immediate effect. For less critical non-compliance, the provider may be given weeks or months to update their technical documentation or retrain the model.

Procedural Rights in Corrective Phases

When a corrective order is issued, the provider has the right to be heard. This is a fundamental principle of EU administrative law. The authority must allow the provider to submit written comments or, in complex cases, an oral hearing before confirming the measure. This is the moment to present technical evidence proving that the perceived non-compliance is actually a misunderstanding of the system’s function, or that the proposed corrective measure is technically disproportionate.

For example, if an authority orders the “recall” of a software-based AI system, the provider might argue that a “remote patch” or an update is sufficient, rendering a physical recall impossible or unnecessary. Negotiating the specific form of the corrective order is often more effective at this stage than during an appeal.

Administrative Fines and Penalties

If the provider fails to comply with a corrective order, or if the violation is deemed intentional or negligent and causes significant harm, the authority will move to the final stage of enforcement: financial penalties. The AI Act harmonizes the ceiling of fines to ensure a consistent deterrent across the EU, but the calculation of the actual fine remains subject to national guidelines.

Calculating the Fine

The AI Act sets maximum fines at a level comparable to the GDPR: up to €35 million or 7% of total worldwide annual turnover for the preceding financial year, whichever is higher. However, this is the ceiling. The actual fine is determined by the national authority based on a set of aggravating and mitigating factors.

Typical factors include:

• Nature and Gravity: Was the violation a procedural slip-up (e.g., missing documentation) or a substantive failure (e.g., a biased algorithm causing discrimination)?
• Intention or Negligence: Did the company know, or should it have known, about the breach?
• Cooperation: Did the provider facilitate the investigation or obstruct it?
• Previous Infringements: Does the company have a history of regulatory issues?

It is worth noting that national authorities often have “starting points” for fines. For instance, under the GDPR, many authorities have internal grids that start with a baseline percentage of the maximum fine and adjust it up or down. While the AI Act does not mandate such grids, the procedural culture of the national MSA will heavily influence the outcome.

The Burden of Proof

In enforcement proceedings, the burden of proof generally lies with the regulator. The authority must demonstrate that the conditions for the infringement are met. However, once the authority has established a prima facie case (e.g., by showing the system failed a specific performance metric or lacked required documentation), the burden may shift to the provider to prove that they took all reasonable measures to ensure compliance. This is particularly relevant for “state of the art” defenses, where a provider argues that the technology simply did not exist to meet a higher standard. Proving this requires meticulous documentation of the development process and the market landscape at the time of deployment.

Appeals and Judicial Review

The administrative decision is not the end of the road. The EU legal framework guarantees the right to an effective remedy and a fair trial. If a provider disagrees with a corrective order or a fine, they can challenge it before the national courts.

Administrative vs. Judicial Appeal

Some Member States have a two-tier system. The first tier is an administrative appeal to a higher body within the regulatory agency itself (e.g., an appeal board). The second tier is a judicial appeal to the competent administrative court. Other jurisdictions allow for direct judicial review of the authority’s decision.

For example, in Spain, the administrative appeal (recurso administrativo) must be filed before the same administration that issued the decision, which then has a set period to reconsider. If rejected, the case moves to the contentious-administrative court. In contrast, in the Netherlands, one might go directly to the administrative court.

Strategic Consideration: The choice of venue matters. Administrative appeals are often faster and cheaper but may be seen as “friendly” to the regulator. Judicial appeals are more rigorous, involving independent judges, but are slower and more expensive. However, the judicial route often provides a better opportunity to introduce new evidence or expert opinions that were not part of the original administrative file.

Grounds for Appeal

Appeals against AI Act enforcement will likely focus on several key arguments:

1. Procedural Errors: Did the authority respect the deadline for the information request? Was the right to be heard properly exercised? Was the evidence gathered lawfully?
2. Factual Errors: Did the authority misunderstand the technical nature of the AI system? (e.g., confusing a statistical model with a causal inference engine).
3. Legal Interpretation: Did the authority apply the wrong legal standard? (e.g., applying a strict liability standard where negligence was required).
4. Proportionality: Is the corrective order (e.g., a ban) disproportionate to the risk identified?

It is important to recognize that courts generally show deference to the technical expertise of regulatory authorities. They will not easily overturn a technical assessment unless it is “manifestly incorrect.” Therefore, the appeal must be backed by robust independent technical evidence, not just legal arguments.

Member State Variations: The “Gold-Plating” Risk

While the AI Act is a Regulation (meaning it applies directly in all Member States without needing national transposition laws), the enforcement procedures are often governed by national administrative law. This creates a patchwork of procedural realities.

Germany: The Federal Structure

In Germany, enforcement is decentralized. The Länder (federal states) are responsible for market surveillance. This means that an investigation by the authority in Bavaria might proceed differently than one in Hamburg. Germany has a strong tradition of “federal states” (Landesgesetze) that can supplement EU law in procedural matters. Furthermore, Germany often engages in “gold-plating”—adding stricter requirements to EU directives. While the AI Act is a Regulation, German procedural law might impose stricter documentation or transparency requirements on the investigation itself.

France: The CNIL Precedent

France’s data protection authority, the CNIL, is one of the most active regulators in Europe. Their procedural playbook—issuing public warnings, conducting tech audits, and negotiating compliance commitments—is likely to be mirrored by the French MSA for AI enforcement. The French approach is often characterized by a rapid escalation to fines if the regulator feels the company is stalling. They are also very aggressive on the “right to explanation” for algorithms used in public services.

Ireland: The Hub for Big Tech

Ireland hosts the European headquarters of many major US tech companies. The Irish Data Protection Commission (DPC) has been criticized for the slow pace of its GDPR investigations. However, the DPC has recently ramped up its resources and procedural efficiency. For AI companies based in Dublin, the Irish MSA will likely be the primary enforcer. The procedural culture here is heavily influenced by common law traditions, emphasizing written submissions and detailed legal arguments.

Italy: The Garante and the “Stop” Order

The Italian Garante per la protezione dei dati personali gained fame for temporarily banning ChatGPT. Their procedural style is interventionist. They are quick to issue “cease and desist” orders (ordine di sospensione) if they perceive an immediate risk to data subjects. The Italian approach prioritizes the immediate protection of rights over a lengthy investigation, meaning companies operating in Italy must be prepared for sudden procedural stops.

Practical Guidance for Compliance Teams

To navigate these procedures effectively, organizations must integrate procedural awareness into their compliance strategy. It is not enough to build a compliant AI system; the organization must be able to defend it procedurally.

Documentation as a Procedural Shield

The single most important procedural safeguard is documentation. When an authority issues an RFI, the ability to produce a clear “Compliance File” containing the risk management system, data governance logs, conformity assessments, and post-market monitoring plans can often close the investigation at the information stage. If these documents are missing or disorganized, the authority is forced to dig deeper, increasing the likelihood of finding other errors.

The “First Responder” Team

Organizations should designate a cross-functional “First Responder” team for regulatory inquiries. This team should include legal counsel, a technical lead (who understands the architecture of the AI), and a compliance officer. This team is responsible for:

• Acknowledging receipt of the RFI immediately.
• Verifying the legal validity of the request.
• Drafting a response strategy that is truthful but legally protected.
• Preparing for a potential site visit.

Simulation and Training

Just as companies conduct fire drills, they should conduct “regulatory raid drills.” Simulate an information request or an on-site inspection. Test how quickly the team can locate specific technical documentation. Practice how to handle requests for source code. This training reduces panic and ensures that procedural rights are asserted calmly and professionally during the actual event.

Conclusion: The Procedural Path to Trust

The enforcement procedures of the AI Act are designed to be robust, yet respectful of national administrative traditions. They represent a bridge between the high-level goals of EU digital policy and the messy reality of code, data, and human oversight. For the regulated community, the message is clear: compliance is not a static state achieved once, but a dynamic process of readiness. Understanding that an information request is not an accusation but a procedural step, and that a corrective order is a negotiation opportunity rather than a final judgment, allows organizations to maintain control over their regulatory destiny. By mastering the procedural rules of the game, European innovators can ensure that their technologies are judged on their merits and their risks, rather than on procedural missteps.