The EU’s Structural Challenges in AI Act Enforcement — and a Sustainable Path Forward

The European Union faces three structural challenges in enforcing the AI Act:

1. 24 official languages — Maintaining identical meaning across languages and over time is not possible without a semantic foundation.
2. 27 Member States — Each with its own legal culture and administrative interpretation, creating unavoidable semantic divergence.
3. A strict enforcement timeline — Meaning may drift faster than compliance can be coordinated unless a unifying semantic structure is introduced.

These challenges share a single root cause: Semantic Drift.

They therefore require a single category of solution:
Semantic Management — a structure that stabilises meaning across languages, jurisdictions, and time.

Crucially, this is not a temporary or stop-gap measure.
Semantic Management is designed as a long-term governance mechanism, capable of incremental and continuous improvement as regulations, guidance, and interpretations evolve.

Any such solution must also meet a decisive requirement: Implementability under real EU operational conditions.

For this reason, Semantic Management cannot rely on manual processes alone.
The scale and velocity of EU-wide semantic alignment require the use of GenAI.
At the same time, GenAI must remain human-guided and interactive to preserve intention, accountability, and legal consistency.

Semantic Management therefore forms a hybrid structure in which:

• GenAI supports large-scale semantic extraction, comparison, and verification;
• Humans retain semantic judgment and oversight;
• Both operate interactively and continuously.

Importantly, a practical and sustainable method exists.
This approach enables the EU not only to address current enforcement challenges,
but to progressively strengthen semantic consistency over time,
without relying on ad-hoc corrections or repeated structural resets.

I would be pleased to provide further details if useful.