No one sees the full process
AI tools are used across teams while a central register of content types, roles and decisions is missing.
ShowAI translates European transparency rules into a workable publishing process: identify, review, document and publish responsibly.
No black box. Each step shows who decided, on what basis and what was checked before publication.
Organisations increasingly publish text, images, audio and video created with generative AI. Without a fixed process, review, transparency and accountability become inconsistent.
AI tools are used across teams while a central register of content types, roles and decisions is missing.
Employees do not always know when transparency is legally relevant or voluntarily appropriate.
Without consistent records, it is difficult to show who substantively reviewed and approved content.
From 2 August 2026, organisations within the scope of Article 50 must meet the applicable transparency obligations. A clear record helps teams make consistent decisions and explain what happened when clients, auditors or authorities ask.
Without a consistent record, an organisation may struggle to show why content was disclosed, not disclosed or routed through human review.
Natural and legal persons may submit complaints to a market-surveillance authority. Poor records make a response slower and less reliable.
Teams may need to search old files, interview staff, review past publications and obtain external legal support to reconstruct what happened.
Inconsistent AI disclosures can create client concerns, contractual friction and reputational damage even where no formal penalty is imposed.
Important boundary: Article 50 does not create a universal legal duty to keep a complete log for every item of AI-assisted content. Documentation is valuable because it supports consistent decisions and evidence, especially where an organisation relies on human review and editorial responsibility.
Map AI tools, content types, publishing channels and the roles involved.
Examine the real workflow: who creates, reviews, changes, approves and publishes?
Translate recurring situations into consistent questions, outcomes and escalation points.
Set up a practical register, review procedure and allocation of responsibilities.
Define concrete actions for adoption, staff guidance and periodic control of the publishing process.
The service begins with the real decisions people must make before publication, not with software.
Collect information on use cases, audiences, channels and current policies.
Trace several real content routes from creation to publication.
Design decision questions, roles, review steps and documentation.
Deliver templates and concrete implementation actions to the team.
For agencies producing AI-assisted content for multiple clients.
For teams publishing about politics, policy and matters of public interest.
For organisations that value public trust and demonstrable accountability.
For smaller publishing organisations that want to document human oversight consistently.
The knowledge base separates binding law, official guidance, voluntary measures and practical recommendations — with primary sources and review dates.
A source-based guide to provider and deployer duties, deepfakes, public-interest text, human review and the 2026 application dates.
Read the full guide → CodeWhy the Code is voluntary while applicable Article 50 obligations are not.
Read the explanation → WorkflowHow substantive review, authority and editorial responsibility differ.
Read the explanation → Risk & evidenceThe legal penalty framework and the practical cost of weak documentation.
Read the explanation →ShowAI is an independent initiative by Lotta Punt at the intersection of AI, European regulation and public communication. The method is in its pilot phase and is being developed using official sources and practical cases.
The initial pilot is intended for a small organisation that wants to examine and structure its current AI-content process.