After the EU's Artificial Intelligence Act was officially passed in 2024, the transparency obligation was specifically set to take effect on August 2, 2026, earlier than the full compliance requirements for high-risk systems; this implementation is a phased execution arrangement clearly reserved during legislation, rather than a temporary policy adjustment.

On the capital path, generative AI companies and platforms must add machine-readable labels and user-visible disclosures at the output level, shifting compliance costs from front-end model training to deployment and distribution stages, forcing resources toward detection technologies, watermarking solutions, and auditing tools, creating new intermediate service demands.

A similar path was seen during the initial implementation of the EU GDPR: platforms were forced to restructure data processes and user notification mechanisms, giving rise to privacy technologies and compliance service providers; the current AI content ecosystem is transitioning from "freely generated" to "traceably generated," with labeling capabilities becoming a market entry threshold.

This is essentially a regulatory change: when the scale of generated content impacts the foundation of information authenticity, legislation chooses to rebuild user trust mechanisms through mandatory disclosure, shifting the verification cost from individual judgment to system and platform responsibility.

ABAB News · Cognitive Law

After content scales, authenticity must rely on institutional enforcement
Disclosure obligations shift verification costs from users to producers
The real threshold for regulatory implementation lies not in the model but in the output layer