The EU AI Act Article 50 compliance checklist for content teams

Area 1 — Scope: establish whether (and where) you're covered

• ☐ 1.1

  List every place AI touches your content pipeline: drafting, images, video, audio, chat, personalization. You are a deployer for each system you use under your authority.

• ☐ 1.2

  Apply the territorial test: does any of this content reach EU audiences? (Public English-language content on the open internet: assume yes.) Article 2 extends the Act to non-EU deployers whose AI output is used in the EU.

• ☐ 1.3

  Record the determination — a dated, one-page scope memo. “We assessed and concluded X” is itself evidence of governance.

• ☐ 1.4

  Diarize the dates: 2 Aug 2026 (Article 50 applies) · 2 Dec 2026 (end of the marking grace period for generator systems already on the market before 2 Aug 2026 — a provider-side duty, but know it) · high-risk dates are moving to Dec 2027 / Aug 2028 under the Omnibus (adopted by Parliament and Council in June 2026, awaiting Official Journal publication — confirm current status when you rely on it).

Area 2 — Interaction disclosure (chatbots & assistants)

• ☐ 2.1

  Inventory every AI system your audience interacts with: site chatbots, AI SDRs, voice agents.

• ☐ 2.2

  Ensure people are informed they're interacting with AI, unless it's obvious to a reasonably well-informed person. Test that the disclosure survives your real UI — mobile, embedded widgets.

• ☐ 2.3

  Screenshot and archive each disclosure with a date — the evidence habit matters more than the banner.

Area 3 — Synthetic media (images, video, audio, “deepfakes”)

• ☐ 3.1

  Inventory AI-generated or AI-manipulated image, video and audio in your marketing — including realistic synthetic presenters: under the Commission's draft guidelines, a fictitious-but-realistic AI person still counts as a deepfake.

• ☐ 3.2

  Apply the right test: not “would our audience be fooled” but the guidelines' broadened average-consumer standard accounting for the actual, potentially diverse exposed audience (children, older viewers, lower AI-literacy). And note: intent to deceive is irrelevant to the obligation.

• ☐ 3.3

  Where content falsely appears authentic, disclose the artificial generation or manipulation visibly, and archive proof of the disclosure.

• ☐ 3.4

  Ask your AI vendors for their Article 50(2) machine-readable marking status. That duty sits mostly with providers; your risk is relying on tools that ignore it.

Area 4 — AI-generated text: the human-review route (Article 50(4))

The area most content teams get wrong — and the one with the best-designed escape hatch.

• ☐ 4.1

  Decide per channel: label AI-generated public-interest text as AI-generated, or run genuine human review with editorial responsibility — Article 50(4) recognizes that reviewed content with a person holding editorial responsibility need not carry the public label.

• ☐ 4.2

  If you take the review route, make it a process, not a policy: a defined step content actually passes through before publishing.

• ☐ 4.3

  Put a name on every review. “The team checked it” is not editorial responsibility; a named person is.

• ☐ 4.4

  Review the final bytes — an approval given to draft 3 says nothing about draft 5. Your process must void approvals when content changes afterward.

• ☐ 4.5

  Ban bulk approval. Fifty assets “approved” in one click is not a process of human review — it's a liability with a timestamp.

• ☐ 4.6

  Keep a durable, per-asset record: who reviewed, when, exactly what content, against which source material.

Area 5 — Evidence: the audit trail that survives a “prove it”

• ☐ 5.1

  For each published AI-assisted asset, be able to answer: what model, what inputs, what human touched it, when, and what exactly shipped.

• ☐ 5.2

  Make records tamper-evident — a record that could be quietly rewritten is worth little under scrutiny. Cryptographic hashing or chaining is the clean answer; at minimum, use storage with immutable history.

• ☐ 5.3

  Make evidence exportable — regulators, clients' procurement teams, and your own counsel will ask in their format, not your tool's UI.

• ☐ 5.4

  Set retention: document how long provenance records are kept and who owns them if you change vendors.

• ☐ 5.5

  Know the Code of Practice on marking & labelling AI-generated content (published 10 June 2026): signatories get a presumption of good-faith compliance — softer than a safe harbour, but real enforcement predictability. The initial-signatory window closed 22 July 2026; the underlying practices remain the reference bar either way.

• ☐ 5.6

  Run one fire drill before 2 August: pick a random published AI-assisted asset and try to produce its full evidence file in under 15 minutes. That drill will tell you more than any vendor pitch.