Early Enforcement Signals: What Regulators Are Prioritising

1. Introduction: Enforcement as the Real Test of the AI Act

The EU Artificial Intelligence Act (Regulation (EU) 2024/1689) marks a decisive shift from ethical soft law to hard, enforceable public regulation of artificial intelligence. While much early commentary has focused on classification and compliance design, the true regulatory impact of the AI Act will be determined by how it is enforced, by whom, and against which actors first.

Early enforcement signals—drawn from the structure of the Act itself, preparatory guidance, regulator mandates, and the EU's broader digital enforcement trajectory—already indicate that regulators are not aiming for symbolic enforcement, but rather for strategic, precedent-setting interventions. These interventions are designed to shape market behaviour, discipline risk allocation, and deter regulatory arbitrage.

This article analyses those early signals and identifies what EU regulators are most likely to prioritise in the first enforcement cycle.

2. The Enforcement Architecture of the AI Act

2.1 Decentralised enforcement with central coordination

Enforcement under the AI Act follows a hybrid governance model. Primary enforcement authority lies with national market surveillance authorities, while coordination, interpretation, and systemic oversight are exercised at EU level through the European Artificial Intelligence Board and the European Commission.

This structure mirrors the enforcement logic of the GDPR and the Digital Services Act (DSA), where decentralised enforcement is tempered by centralised interpretive gravity. Academic literature on EU digital regulation suggests that such models tend to produce selective but high-impact enforcement, particularly in early phases.

2.2 Enforcement objectives embedded in the Act

The AI Act is explicit about its enforcement philosophy. Its objectives are not limited to sanctioning non-compliance but include:

• preventing systemic fundamental rights harm;
• ensuring trust in high-risk AI markets;
• avoiding regulatory circumvention via technical or contractual design; and
• aligning AI development with existing EU product safety and consumer protection norms.

This framing signals that regulators will prioritise structural risks, not isolated technical defects.

3. Early Enforcement Signal I: Classification Integrity Will Be Heavily Scrutinised

3.1 The centrality of high-risk classification

High-risk classification is the gateway obligation under the AI Act. Regulators are acutely aware that misclassification—particularly the strategic down-classification of Annex III systems—poses the greatest threat to the Act's effectiveness.

The inclusion of Article 6(4) (mandatory documentation when providers classify Annex III systems as non-high-risk) and Article 80 (specific procedures for supervisory challenge) strongly indicates that classification decisions themselves are enforcement targets, not merely background assessments.

3.2 Expected enforcement focus

Early enforcement is likely to prioritise:

• systems operating at the margins of Annex III, particularly in employment, creditworthiness, insurance pricing, and education;
• "assistive" or "decision-support" tools claimed not to materially influence outcomes; and
• profiling-adjacent systems, where providers attempt to rely on functional minimisation arguments.

Academic analysis already suggests that the "material influence" test in Article 6(3) will be interpreted narrowly, especially where human oversight is nominal rather than substantive.

4. Early Enforcement Signal II: Fundamental Rights Risk Over Pure Technical Non-Compliance

4.1 Rights-centric enforcement logic

The AI Act is explicitly anchored in the EU Charter of Fundamental Rights. Regulators are therefore incentivised to prioritise cases where AI deployment intersects with dignity, equality, access to services, due process, and non-discrimination, even if technical compliance failures appear secondary.

This mirrors enforcement behaviour under the GDPR, where supervisory authorities increasingly focus on systemic rights impact, rather than formalistic documentation gaps.

4.2 High-priority domains

Based on Annex III structure and legislative debates, early enforcement is likely to focus on:

• employment and worker management AI (algorithmic hiring, performance monitoring);
• credit scoring and insurance risk assessment systems affecting access to essential services;
• public sector AI in welfare allocation, migration, and administrative decision-making; and
• emotion recognition and biometric categorisation, given their proximity to prohibited practices.

The Act's emphasis on "reasonably foreseeable misuse" further broadens the enforcement lens beyond stated intended use.

5. Early Enforcement Signal III: Governance Failures Over Model Performance

5.1 Process failures as enforcement leverage

A defining feature of the AI Act is its emphasis on organisational governance, not just algorithmic outputs. Regulators are therefore likely to target failures such as:

• absence of a functioning risk management system;
• inadequate training data governance;
• failure to implement meaningful human oversight mechanisms;
• insufficient post-market monitoring and incident response.

This approach aligns with scholarship on "proceduralisation" in EU risk regulation, where defective governance processes are treated as substantive violations.

5.2 Why governance is attractive for regulators

Governance failures are:

• easier to evidence than model bias claims;
• less dependent on technical interpretability disputes; and
• more scalable as enforcement precedents.

As a result, early enforcement actions are likely to resemble GDPR-style governance cases, rather than technical audits of model weights or architecture.

6. Early Enforcement Signal IV: Supply-Chain Accountability Will Be Tested

6.1 Provider vs deployer responsibility

The AI Act deliberately distributes obligations across providers, deployers, importers, and distributors. Regulators have signalled—through the Act's structure—that contractual outsourcing of responsibility will not shield primary actors.

This is particularly relevant for:

• foundation model providers whose systems are integrated downstream;
• platform operators enabling third-party AI deployment; and
• public bodies procuring AI systems developed externally.

Comparative analysis with EU product liability and market surveillance law suggests that regulators will actively test joint and derivative responsibility in early cases.

7. Early Enforcement Signal V: Deterrence Through Selective, High-Visibility Cases

7.1 Enforcement strategy, not enforcement volume

There is little indication that regulators intend to pursue mass enforcement in the initial phase. Instead, enforcement is likely to be:

• selective (targeting influential market actors);
• strategic (clarifying grey areas); and
• norm-setting (establishing interpretive baselines).

This strategy is consistent with the EU's enforcement posture under the DSA and DMA, where early cases were chosen for systemic impact rather than numerical coverage.

7.2 Penalties as signalling tools

The AI Act's administrative fines—reaching up to €35 million or 7% of global annual turnover—are designed less as routine sanctions and more as credible deterrence instruments. Early enforcement actions are therefore likely to emphasise:

• reputational impact;
• mandatory remediation orders; and
• compliance restructuring obligations.

8. Conclusion: Enforcement Will Shape the Meaning of "Compliance"

Early enforcement under the EU AI Act will not be a technical exercise in box-ticking. It will be a norm-defining process, through which regulators articulate what counts as genuine risk management, meaningful human oversight, and responsible AI deployment.

The clearest early signals suggest that regulators are prioritising:

• classification integrity,
• fundamental rights risk,
• governance robustness,
• supply-chain accountability, and
• strategic deterrence through precedent cases.

For organisations, the implication is clear: formal compliance without substantive risk ownership will not be sufficient. Enforcement will reward those who can demonstrate not only adherence to the letter of the Act, but alignment with its regulatory purpose.

Footnotes (OSCOLA)

1. Deirdre Curtin, Executive Power of the European Union (OUP 2009).
2. Regulation (EU) 2024/1689 (Artificial Intelligence Act) arts 1–2.
3. Artificial Intelligence Act, arts 6(4), 80.
4. Federico Palmiotto, 'The AI Act Roller Coaster' (2024) European Journal of Risk Regulation.
5. Paul De Hert and others, 'The GDPR as a Risk-Based Regulation' (2018) Computer Law & Security Review.
6. Artificial Intelligence Act, recital 44.
7. Julia Black, 'Proceduralising Regulation' (2000) Oxford Journal of Legal Studies.
8. Hans-W Micklitz, The New European Private Law (CUP 2014).
9. Alexandre de Streel and others, 'The European Digital Regulatory Framework' (2022) Journal of European Competition Law & Practice.
10. Artificial Intelligence Act, art 99.