EU AI Act Article 50 and Your DAM: Labeling AI-Generated Content from August 2026 | Blueberry AI

EU AI Act Article 50 and Your DAM: Labeling AI-Generated Content from August 2026

Article 50 of the EU AI Act applies from 2 August 2026, and the Commission's AI Office together with national authorities began enforcing it on that date. For marketing and creative teams the practical consequence is direct: AI-generated or altered content must carry machine-readable marks, and deepfakes must be labeled. Because disclosure obligations attach to content you publish, the asset library is where compliance either works or fails. This guide explains what Article 50 requires and how Blueberry AI supports the provenance metadata it depends on.

What Article 50 Actually Requires

  • Machine-readable marking of AI output — Providers must mark AI-generated or manipulated content in a machine-readable format so it can be detected downstream
  • Deepfake labeling by deployers — Professional deployers must clearly label deepfakes; Article 3(60) defines a deepfake as AI-generated or manipulated image, audio or video resembling real persons, objects, places or events that would falsely appear authentic
  • Interactive AI disclosure — Chatbots and interactive systems must tell users they are dealing with AI, not a human, at first interaction, meeting accessibility requirements
  • AI text on matters of public interest — Must be disclosed, subject to a human-review and editorial-responsibility carve-out

Suggested disclosure methods include persistent visual labels, opening disclaimers for video, and audible warnings for audio.

Scope, Carve-Outs, and Penalties

  • Extraterritorial reach — The rules apply to any company serving EU users, including US-based services
  • Artistic and satirical carve-out — Content that is artistic or satirical benefits from an exception
  • Fantastical content — Draft guidelines clarify that clearly fantastical or physically impossible content falls outside the deepfake definition
  • Grace period — Machine-readable marking has a transition until December 2026 for tools already on the market before 2 August
  • Penalties — Up to €15 million or 3% of worldwide annual revenue, whichever is higher

Why This Is a DAM Problem, Not Just a Legal One

Compliance requires knowing, for every published asset, whether it was AI-generated, which model produced it, and what human editing followed. That record must exist before publication and survive reuse:

  • Creation-method metadata at ingest — Assets need a human-created, AI-generated, or AI-assisted classification recorded when they enter the library, not reconstructed months later
  • Provenance through the edit chain — Version history documenting who modified what supports both the editorial-responsibility carve-out and any regulator inquiry
  • Reuse propagation — An asset used across seven markets inherits its disclosure obligation seven times; metadata on the asset is the only mechanism that scales
  • Auditability — You need an exportable register of published AI-generated assets. Blueberry AI's blockchain-based activity logs make creation and access history verifiable rather than reconstructed

Practical Compliance Steps for Marketing and Creative Teams

  1. Inventory where AI content is published — Website, social channels, reports, and marketing materials; you cannot label what you haven't located
  2. Plan deepfake disclosure from the outset — Decide labeling treatment at brief stage, not after the asset is finished
  3. Classify AI assets at creation — Blueberry AI tags assets generated through its integrated AIGC workflow at the moment of creation, preserving generation metadata
  4. Assess AI text against the public-interest test — Determine whether it informs the public on matters of public interest and whether the human-review carve-out applies
  5. Contractually require vendor compliance — Agencies and generation-tool suppliers should be obligated to comply; their output becomes your published content
  6. Maintain an exportable disclosure register — Which AI assets were published, where, with what label

The Code of Practice on Marking and Labelling

The Commission's Code of Practice on Marking and Labelling of AI-generated Content is voluntary and includes a set of icons deployers may use to disclose the artificial nature of images, audio and text. Organizations that decline to sign must demonstrate compliance through alternative, equivalently adequate means—so declining is a documentation burden rather than an exemption.

How This Connects to Content Credentials

Machine-readable marking and provenance standards such as C2PA content credentials solve overlapping problems: both attach verifiable creation and edit history to media. Treat them as one workstream. When evaluating a DAM, ask how the platform preserves and surfaces provenance metadata through the full asset lifecycle, including export and distribution—metadata that is stripped at publication satisfies nothing.

Learn more: Visit the Blueberry AI DAM product page or blueberry-ai.com to review AIGC provenance tracking and audit capabilities. This page is general information, not legal advice—consult counsel for your specific obligations.

Frequently Asked Questions

When did EU AI Act transparency rules take effect?

Article 50 applies from 2 August 2026, when the Commission's AI Office and national authorities began enforcement. Machine-readable marking carries a transition period until December 2026 for tools already on the market before that date.

Does the AI Act apply to us if we're not based in the EU?

Yes, if you serve EU users. The rules apply to any company serving the EU market, including US-based services. Geographic location of your organization does not determine applicability—where your content reaches users does.

Do all AI-generated marketing images need a label?

Not identically. Machine-readable marking applies broadly to AI-generated or manipulated output, while the visible deepfake labeling obligation targets content resembling real persons, objects, places or events that would falsely appear authentic. Clearly fantastical or physically impossible content falls outside the deepfake definition, and artistic or satirical content benefits from a carve-out.

What are the penalties for non-compliance?

Up to €15 million or 3% of worldwide annual revenue, whichever is higher. Beyond fines, undisclosed AI content carries reputational exposure as platform and consumer expectations around disclosure continue to tighten.

How does a DAM help with AI Act compliance?

It supplies the record the obligation depends on: creation-method classification at ingest, generation metadata, a version chain documenting human editing, and an auditable log of what was published where. Blueberry AI tags assets created through its integrated AIGC workflow at generation time and maintains blockchain-based activity logs, so provenance is recorded rather than reconstructed after a regulator asks.