EU AI Act: Why Transparency Obligations Are Now a GRC Topic

The EU AI Act is becoming operational. One of the first areas companies need to address is transparency. Under Article 50, certain AI systems must clearly inform people when they are interacting with AI or when content has been generated or manipulated by AI.

This affects more companies than many expect. The rules are not limited to high-risk AI systems. Chatbots, virtual assistants, AI-generated marketing content, synthetic images, audio, video and certain deepfake use cases can all trigger transparency obligations.

For GRC teams, this marks an important shift. AI governance is no longer just about principles, policies or innovation control. It now requires concrete inventories, clear roles, risk assessments, approval processes, controls and evidence.

Key Takeaways

Transparency obligations under the EU AI Act apply to specific AI systems and use cases, including interactive AI systems such as chatbots, AI-generated or AI-manipulated content, deepfakes and certain biometric or emotion-related systems.

The core idea is simple: people should be able to recognise when they are interacting with AI or when content has been artificially generated or manipulated. In practice, however, this requires much more than adding a disclaimer.

Companies need to understand where AI is used, who owns each use case, which obligations apply, how users are informed and how implementation is documented. This makes transparency a classic governance, risk and compliance topic.

Why Article 50 Matters

Many AI Act discussions focus on high-risk AI. Article 50 shows that even companies without high-risk systems may still be affected. A customer service chatbot, an AI assistant on a website, AI-generated product images or synthetic video content may already be enough to create transparency requirements.

The aim is to prevent people from being misled. Customers, employees, partners or the public should not be left uncertain about whether they are interacting with a person or a machine, or whether a piece of content is authentic or AI-generated.

That sounds straightforward, but implementation can be complex. AI tools are often introduced quickly and decentralised across teams. Marketing uses generative content tools. Customer service pilots chatbots. HR tests AI assistants. Product teams integrate AI features. Without central oversight, companies quickly lose visibility.

Transparency Is More Than a Disclaimer

A common mistake is to treat AI transparency as a wording task. Add a label, update a footer, include a short notice and move on. That is not enough.

Transparency needs to be embedded in processes. Companies must know which AI systems are in use, what they do, who is responsible, which users are affected, whether content is generated or manipulated and which disclosure obligation applies.

A disclaimer may be the visible output. The actual GRC work happens behind the scenes: classification, approval, risk assessment, control design, documentation and review.

Chatbots and Interactive AI Systems

Chatbots and virtual assistants are among the most obvious examples. If customers interact with an AI system, they generally need to be informed that they are dealing with AI.

This is particularly relevant for customer support, online banking, insurance portals, HR helpdesks, e-commerce and SaaS platforms. The key issue is not only whether the chatbot says “I am an AI assistant”. Companies also need to ensure that the information is provided at the right moment, in a clear way and consistently across channels.

GRC teams should therefore treat chatbot deployment as a controlled process. Before go-live, the use case should be documented, transparency requirements assessed, content reviewed and ownership assigned.

AI-Generated Content and Deepfakes

The AI Act also addresses AI-generated and AI-manipulated content. This includes synthetic images, videos, audio files and deepfakes. For companies, this can affect marketing campaigns, social media, product visuals, training videos, recruitment content or public communications.

The risk is not only regulatory. It is also reputational. If customers or employees feel misled by synthetic media, trust can be damaged quickly. Transparent use of AI therefore protects both compliance and brand credibility.

Companies should define when AI-generated content needs review, approval and labelling. External agencies and service providers should also be included, because AI-generated content is often created outside the organisation.

The Role of an AI Inventory

The practical starting point is an AI inventory. Without one, companies cannot reliably identify which transparency obligations apply.

An effective AI inventory should capture the AI system, purpose, business owner, provider, user groups, data involved, output type, regulatory role, risk level, required disclosures, controls and available evidence.

For smaller and mid-sized companies, this does not need to be overly complex. But it needs to be structured, maintained and connected to responsibilities. Otherwise AI use will grow faster than governance can follow.

Conclusion: Transparency Is the First Step Toward Trustworthy AI Governance

The EU AI Act makes transparency one of the first practical AI governance obligations for many companies. Chatbots, AI-generated content and deepfakes are no longer just innovation or communication topics. They require clear ownership, controls and evidence.

For GRC leaders, this is an opportunity to build AI governance pragmatically. The first step is not a perfect AI strategy. It is visibility: knowing where AI is used, which obligations apply and how the company can prove compliance.

Zazoon supports companies in building this foundation by connecting AI use cases, risks, controls, responsibilities and evidence in one central GRC system.

FAQ

What are AI Act transparency obligations?

They are requirements that ensure people can recognise when they interact with certain AI systems or when content has been generated or manipulated by AI.

Which AI systems are relevant?

Typical examples include chatbots, virtual assistants, AI-generated content, synthetic media, deepfakes and certain biometric or emotion-related systems.

Why is transparency a GRC topic?

Because transparency requires more than a label. Companies need inventories, responsibilities, risk assessments, controls, approvals and evidence.

What should companies do first?

They should create or update an AI inventory and identify use cases that may trigger transparency obligations.

How does Zazoon help?

Zazoon helps companies manage AI use cases, risks, controls, responsibilities, vendor dependencies and evidence in one central GRC platform.