Legally compliant publication of AI images: Alt text, labeling, copyright status

Brief overview: AI images are created quickly, but are legally complex. Three levels are crucial: Firstly, copyright (human authorship, barriers, chains of rights), secondly, labeling and transparency (AI Act, platform and product obligations) and thirdly, publication practice (alt text/accessibility, SEO, metadata). Those who dovetail publication, licenses, labelling and technical provenance properly reduce the risk of warnings and increase findability.

Copyright status and chain of rights: what is protected in AI images – and what is not

The concept of a work under copyright law presupposes a personal intellectual creation (Section 2 (2) UrhG). The author is only the creator of the work, i.e. a natural person (Section 7 UrhG). It follows from this: Pure, completely automatically generated images without any formative human contribution do not regularly achieve work status. Protection can arise if the human contribution has a personal level of design – for example through targeted prompt sequences, curated variants, compositing, retouching and an overall creative concept. Borderline cases depend on the individual case.

This means for publishing practice:

• If there is no human work quality, there is no copyright on the result. This does not make the use “without rights”: trademark, design, competition, personality and contract law (e.g. model terms and conditions of the generators) remain relevant.
• If there is human authorship, the classic rules apply: moral rights (e.g. attribution), transfer of rights of use, doctrine of achievement of purpose (Section 31 (5) UrhG). If you work in a team, co-authorship and shares should be clearly regulated.
• If third-party elements are integrated (stock, logos, purchase licenses), a clean rights chain is required: rights clearance for works and ancillary copyrights, editing rights (Section 23 UrhG) and exemptions in contracts.

Limitations: Quotation (§ 51 UrhG) and caricature/parody/pastiche (§ 51a UrhG) remain important corrective measures. A meme or montage can therefore be permissible – but only to a very limited extent and only for a specific purpose. For portraits of real people, the right to portraits also applies (§§ 22 ff. KUG): The rule is consent; exceptions are narrow.

Practical tip: For external creatives, record in briefings how the human creative contribution is made (prompting documentation, selection decisions, versioning). This makes it easier to justify copyright status later on or – conversely – to clearly classify the result as copyright-free.

Labeling obligations and transparency: what will actually be required in 2025

The AI Act applies throughout the EU. There are transparency obligations for synthetic or manipulated content: Users must be able to recognize that content is artificially generated or modified. For providers of general AI models, there are additional obligations regarding copyright compliance and the aggregation of training content. The Digital Services Act (DSA) also creates platform processes (reporting channels, risk mitigation, transparency reports). Special national standards for the “AI label” do not yet exist across the board; AI Act transparency, industry standards and platform requirements are therefore decisive.

Concrete ideas for implementation:

• Labeling in the front end: In the case of editorial or advertising content, clearly indicate “artificially generated/AI image” in the immediate vicinity of the image (e.g. caption or info icon with tooltip).
• Metadata labeling: Use of content credentials (C2PA) for tamper-proof origin and processing documentation. This means that the proof is retained even if the content is reused, provided that metadata is not removed.
• Internal policy: Define in which product areas labeling is mandatory (e.g. category lead, newsletter, social ads). Stricter defaults for sensitive contexts (politics, health).
• Observe platform rules: Large platforms are increasingly checking for synthetic content and requiring labels. Standardized, reusable references in asset management save rework.

Labeling is not an admission of guilt. It fulfills transparency obligations, reduces moderation and reputational risks and strengthens evidence in the event of a conflict.

Publishing practice: Alt text, SEO, accessibility and metadata

Alt texts are not a decoration, but a must: they make images accessible to screen readers and search engines. Good alt texts are precise, describe the motif and function of the image in the context of the page and avoid keyword stuffing lists. For more extensive motifs, an extended description (long desc) is added. SEO side effects: Meaningful file names, structured data where appropriate, surrounding context and image sitemaps.

Checklist for image delivery:

• Alt text: Short, precise, contextual. For decorative elements alt="".
• Extended description: For complex diagrams, store in the immediate context.
• File name: Descriptive and consistent (no cryptic hashes in the delivery level).
• Image sitemaps: Maintain relevant attributes; media-rich pages benefit noticeably.
• IPTC fields: Creator/Credit, Copyright Notice, DigitalSourceType, Rights-Statements, Keywords – maintained centrally in the DAM. Dedicated accessibility fields (Alt Text/Extended Description) have existed in the IPTC specification since 2021/2024; their use facilitates consistent transfer to CMS/CDN.
• C2PA/content credentials: bind the provenance manifest to the asset (creation tools, processing steps, camera attestation if necessary, seal/time stamp). For sensitive areas, additional robust watermarks or “durable credentials” so that evidence can be reconstructed in the event of metadata loss.

Accessibility is more than just alt text: Contrasts, zoom capability, keyboard navigation, focus visibility and sufficient tap targets are all part of the overall picture. For images, this means: no pure color communication without text repetition, no essential information exclusively in the image.

Risk matrix for AI images: TYPOLOGIES that lead to disputes in practice

Portraits of real people: Problematic without consent. Even synthetically created “photoclones” can violate general personal rights. For commissioned work with real models: Model release in writing, scope (advertising/editorial), territories, duration, AI specifics (training/face-swap prohibited). For generative “lookalikes”, pay attention to trademarks, naming rights and competition law.

Logos/brands/designs: Images originating from AI can also infringe trademark rights if they are used to indicate origin or exploit the reputation. In advertising environments, also consider unfair exploitation of reputation. Own brands should be used consciously in generative workflows (approval process, brand protection guidelines).

Stock and third-party licenses: Many image generators contain license clauses on output usage; the spectrum ranges from very liberal to restrictive. In the case of mixed works (AI + stock), the most restrictive license conditions apply. Training materials must be considered separately from this: Permitted training says nothing about the permissibility of the subsequent output in a specific use (e.g. logo use in advertising).

Reference styles and artist names: Style imitation is rarely justiciable under copyright law as an independent object of protection, but can be tricky under unfair competition law or naming law (misleading about the origin, unlawful exploitation of the reputation). In campaign communication, clear distancing is advisable (“inspired by”, no deceptive impression).

Sensitive contexts: politics, health, children. Stricter internal approvals apply here. Plan and document the labeling of synthetic image elements at an early stage. Standardize provenance assurance for election campaign or crisis communication (C2PA + qualified time stamp).

Workflows that enable legally compliant publications

A. Rights and document management

1. Create project file: prompt history, intermediate steps, final selection, processing steps.
2. Record rights chain: Own contributions, purchased elements, releases, license IDs, output rights according to tool terms and conditions.
3. Document barrier check: If quotation/parody/pastiche is used, record the purpose and scope.

B. Labeling and metadata

1. Define front-end labeling (location, wording, icon).
2. Maintain IPTC fields in the DAM, use accessibility fields (Alt-Text/Extended Description).
3. Generate C2PA manifest; where possible, link with eIDAS timestamp/seal to increase evidential value.

C. Review & Release

1. Legal review list: Copyright status, personal rights, trademarks/design, general terms and conditions conflicts.
2. Editorial four-eyes principle for sensitive motifs.
3. Log approval; note regional specifics for social ads.

D. Operation & Incident Response

1. Provide takedown path and counter-notification processes.
2. For objectionable images: Immediate action (depublishing/steaming), clarify the facts, take evidence from the project file, document the decision.
3. Incorporate lessons learned into the image policy (e.g. additional labeling, blacklist for sensitive motifs).

FAQ for daily practice

Is every AI image to be labeled?
Not every – but wherever the origin is significant or confusion with real recordings is likely, labeling is recommended. The AI Act requires transparency for artificially created/manipulated content; many platforms require labels anyway. In editorial contexts, the classification is decisive (photojournalism vs. illustration).

Can an AI image be used “freely” without copyright status?
Caution. Even copyright-free results can affect the rights of third parties (trademarks, designs, personal rights, contract law). If there are no exclusive rights of your own, the exclusivity of the motif is also not guaranteed.

How is the alt text formulated?
Task-oriented and context-related: What does the image show and why is it here? No keyword chains, no redundant phrases. For decorative images alt="". For complex image information, an extended description in the body text or via a linked detailed description.

How do I secure the evidence?
Bind C2PA manifests to the file, archive hash/logs in the DAM and – where possible – provide them with a qualified time stamp/seal. In this way, the creation, processing and publication can be substantiated in a court of law.

Sample policy (short version) for teams

1. Definitions: “AI image” = created in whole or in part using generative processes; “synthetic part” = image information without a real template.
2. Labeling: Mandatory for media, political, health and advertising environments; otherwise depending on the context. Placement close to the image; wording short and clear.
3. Rights: Check rights chain before publication; portraits only with release; logos/trademarks only with release.
4. Metadata: Maintain IPTC fields completely, alt text mandatory, use image sitemaps.
5. Provenance: C2PA mandatory for in-house productions in editorial/advertising environments; in the case of additional purchases, providers with content credentials are preferred.
6. Review: Sensitive motifs released by legal/editors.
7. Incident response: takedown path, correction instructions, documentation obligations.

Conclusion

Legally compliant publishing means correctly classifying human authorship, securing rights chains, setting transparent labels and implementing accessibility properly. Alt text, IPTC metadata and C2PA provenance are not “nice-to-have extras”, but the backbone of scalable image governance. If you standardize these building blocks, you can publish faster, with more certainty and more visibility.

Author: Marian Härtel

Marian Härtel ist Rechtsanwalt und Fachanwalt für IT-Recht mit einer über 25-jährigen Erfahrung als Unternehmer und Berater in den Bereichen Games, E-Sport, Blockchain, SaaS und Künstliche Intelligenz. Seine Beratungsschwerpunkte umfassen neben dem IT-Recht insbesondere das Urheberrecht, Medienrecht sowie Wettbewerbsrecht. Er betreut schwerpunktmäßig Start-ups, Agenturen und Influencer, die er in strategischen Fragen, komplexen Vertragsangelegenheiten sowie bei Investitionsprojekten begleitet. Dabei zeichnet sich seine Beratung durch einen interdisziplinären Ansatz aus, der juristische Expertise und langjährige unternehmerische Erfahrung miteinander verbindet. Ziel seiner Tätigkeit ist stets, Mandanten praxisorientierte Lösungen anzubieten und rechtlich fundierte Unterstützung bei der Umsetzung innovativer Geschäftsmodelle zu gewährleisten.