EU AI Act Fine Calculation: How Regulators Actually Set the Amount

Updated 7 Oct 2026: Digital Omnibus on AI (Regulation (EU) 2026/1744).

A €35 million headline figure grabs attention. What it hides is that EU AI Act fine calculation is a structured process with multiple stages, and the inputs at each stage are things your business can actually influence before an investigation begins.

Understanding the mechanics is not just useful for lawyers. HR directors deciding whether to deploy an AI screening tool, compliance officers building an audit trail, and managing directors signing off on AI procurement all need to know how enforcement math works.

# The Three Penalty Tiers

The AI Act establishes three distinct fine ceilings in Article 99.

Tier 1 applies to the most serious violations: deploying a prohibited AI system listed in Article 5, such as social scoring or real-time biometric surveillance in public spaces. The ceiling is €35 million or 7% of total annual worldwide turnover, whichever is higher.

Tier 2 covers non-compliance with obligations that apply to high-risk AI systems. These include failures around conformity assessments, technical documentation, human oversight, or transparency requirements. The ceiling is €15 million or 3% of global turnover.

Tier 3 targets supplying incorrect, incomplete, or misleading information to regulators and notified bodies. The ceiling is €7.5 million or 1% of global turnover.

Note the word "or" in each tier. For most companies, regulators take whichever figure is higher, not lower. SMEs, including start-ups, are the exception: under Article 99(6) their ceiling is whichever figure is lower. A small company (an SME) with €10 million in annual revenue that commits a Tier 2 violation therefore faces a ceiling of €300,000, not €15 million. Since the Digital Omnibus, small mid-cap enterprises (SMCs) also get the lower figure, but only for Tier 2 and Tier 3, not for prohibited practices.

# How the Starting Point Is Set

The European Commission's approach, mirrored in guidance from national market surveillance authorities, follows a logic borrowed from GDPR enforcement. Regulators begin with the gravity and nature of the infringement, then adjust upward or downward based on specific circumstances.

Gravity assessment looks at three things:

1. What category of system was involved? A prohibited system triggers Tier 1 regardless of how briefly it was used. A high-risk system in the wrong configuration triggers Tier 2.
2. How many people were affected? A recruitment AI that screened 500 candidates unlawfully is treated differently from one that screened 50,000.
3. What actual harm occurred? Job rejections, loan denials, or medical triage errors each carry different weight.

The AI Act's recital 161 explicitly instructs supervisory authorities to consider the nature, gravity, and duration of the infringement when setting fines. Duration matters more than most deployers expect. Running a non-compliant system for 14 months is dramatically worse than running it for 6 weeks before correcting course.

# The "Turnover" Definition

One technical point that catches SMEs off guard: "total annual worldwide turnover" is measured at the group level, not the entity level. If your Dutch operating company is owned by a holding structure, regulators will look at consolidated group revenue. A subsidiary with €8 million in local revenue but a parent group with €400 million in turnover faces percentage-based fines calculated on €400 million.

This is consistent with how Dutch and Belgian data protection authorities already apply GDPR Article 83, and there is no reason to expect AI Act enforcement to diverge.

# Aggravating Factors That Push Fines Up

Regulators applying Article 99 have explicit authority to consider aggravating circumstances. Based on both the Act's text and enforcement patterns established under GDPR by authorities including the Autoriteit Persoonsgegevens (AP), the following factors reliably increase final amounts:

• Intentional or negligent conduct. Deliberately disabling a human oversight mechanism is treated far more harshly than a configuration error.
• Refusal to cooperate. Stonewalling investigators, providing incomplete documentation, or delaying responses multiplies the base amount.
• Prior violations. If your organisation has received warnings or fines under GDPR for related AI processing, that history is admissible.
• Obstructing access. Denying regulators access to technical logs or training data is an aggravating factor in its own right, separate from the original violation.
• Targeting vulnerable groups. AI systems that affect children, people with disabilities, or asylum seekers receive heightened scrutiny.

# Mitigating Factors That Push Fines Down

The same framework cuts the other way. Documented mitigation can meaningfully reduce final amounts, sometimes by half or more based on GDPR precedent from the European Data Protection Board's guidelines on calculating administrative fines.

The most effective mitigating factors are:

• Proactive disclosure. Reporting an incident before regulators discover it independently carries significant weight.
• Immediate corrective action. Disabling the non-compliant system the moment a problem is identified, with documented timestamps, demonstrates good faith.
• Existing compliance infrastructure. A written AI governance policy, completed staff training records, and a system inventory all signal organisational maturity.
• Full cooperation during investigation. Providing complete documentation promptly, making staff available for interviews, and avoiding procedural challenges each contribute.
• Limited actual harm. If no individual suffered a concrete negative outcome, regulators have grounds to reduce the amount.

This is where the preparation you do now has a direct monetary value. A compliance officer who can produce a dated training log, a risk classification decision, and a supplier contract with Article 26 responsibilities assigned is in a structurally different negotiating position than one who cannot.

# What Enforcement Is Starting to Look Like

National market surveillance authorities have supervised the AI Act since 2 August 2026. The Digital Omnibus moved the main obligations for high-risk systems in Annex III to 2 December 2027 (Annex I: 2 August 2028), so formal enforcement of those high-risk deployer duties starts then. Supervisory authorities are building capacity now. The AP in the Netherlands has published its AI supervision priorities and is actively auditing algorithmic systems under existing GDPR powers in the meantime.

The pattern from GDPR enforcement is instructive. When the AP fined a Dutch insurer for algorithmic fraud detection in 2023, the final amount was reduced substantially because the company had documented its human review process, even though that process was ultimately found inadequate. Documentation of intent and effort matters even when the outcome fails.

The EDPB's coordinated enforcement actions have consistently shown that the gap between maximum and actual fines is largest for organisations that cooperate fully and demonstrate they had a compliance programme, even an imperfect one. Organisations that treat enforcement as adversarial from day one tend to end up at the higher end of the range.

# The SME Proportionality Provision

Article 99(6) gives small and medium-sized enterprises, including startups, a lower ceiling: for them, each tier's maximum is whichever of the two amounts is lower, not higher. Since the Digital Omnibus, new Article 99(6a) gives small mid-cap enterprises (SMCs) the same lower figure, but only for Tier 2 and Tier 3, not for prohibited practices in Tier 1.

That cap is a ceiling, not the fine. Within it, the factors above still decide where you land, and demonstrating that you acted in good faith works in your favour. The proportionality argument is weakest when the violation is in Tier 1 (prohibited systems) and strongest when it involves a technical documentation failure in Tier 2 or 3.

For a company with 50 employees and €5 million in revenue, the theoretical Tier 2 maximum is therefore €150,000 (3% of turnover), not €15 million, and a well-documented case combined with mitigating factors could realistically bring the actual amount down to a fraction of that. The EU legislator built this in deliberately.

# The One Number You Can Control

Every factor that drives fines downward — proactive disclosure, cooperation, documented governance, limited harm — is something you build before the investigation starts, not during it. The fine calculation process rewards organisations that treated compliance as an ongoing operational function rather than a crisis response.

Start with knowing what AI systems you deploy and how they are classified. A system inventory, a risk tier for each tool, and a clear record of who is responsible for oversight costs almost nothing to build. It is the foundation every other mitigating factor rests on.

If you are not certain how your current AI deployments would be classified under Annex III or what obligations attach to them, the two-minute compliance check at comply.khairos.ai will give you a starting point — and the documentation trail that regulators look for when deciding where on the penalty scale your organisation lands.