The European Union's AI Act transparency rules have entered their first full enforcement phase, and organizations across sectors are bracing for the first wave of Article 50 actions. The regulation, which began applying its general provisions in stages, now places significant obligations on both providers and deployers of AI systems that interact with natural persons, generate deepfakes, or handle synthetic content. Industry experts expect the first year to reveal not only how regulators will interpret the new rules, but also how unprepared many organisations are for the practical consequences of a transparency failure.
In a recent interview, Edwin Weijdema, Field CTO at Veeam, offered a detailed look at what the first year of enforcement might bring. His insights span fines, corrective orders, direct interaction thresholds, simulated phishing exercises that use cloned voices, and the accountability questions that clients are asking but cannot yet answer.
Corrective Orders Expected to Outpace Fines in Year One
Article 50 breaches carry exposure up to 15 million euro or three percent of worldwide annual turnover. That headline figure has captured executive attention, but Weijdema cautions that the initial wave of penalties will not necessarily be financial. Drawing on the enforcement patterns of GDPR and NIS2, he points out that the EU's decentralized model means national authorities in each member state will apply their own procedures and priorities. That uneven landscape makes precise predictions difficult.
The first year of any regulation often functions as a bedding-in period, he said. It is far more likely that corrective orders will significantly outweigh the number of major financial penalties in the early phase, especially for organizations making a genuine effort to comply. Regulators are expected to look at proportionality, the scale of impact, whether a breach was intentional or negligent, how quickly the organization cooperated, and whether basic governance controls were already in place.
Even so, one or two large headline-making fines cannot be ruled out, as regulators may want to signal that they are serious about enforcement. But Weijdema thinks that such a fine is unlikely in year one. The more immediate operational risk is being ordered to suspend, relabel, change, or withdraw an AI-enabled process. "For an organisation, being ordered to suspend, relabel, change, or withdraw an AI-enabled process at speed could be far more disruptive than receiving a fine," he said. "In year one, the bigger risk likely won’t be the fine; it’ll be being told to stop using the system until you can prove it is compliant."
When Does an AI Agent Interact Directly with a Person?
One of the most nuanced areas of Article 50 is its transparency obligation: people must be informed when they are interacting with an AI system, unless it is obvious from the circumstances. In practice, agentic systems often interact with people indirectly through a ticketing queue, a shared inbox, or a supplier's procurement portal. Does that count as direct interaction? Weijdema says the channel is not decisive.
The key question is whether the AI system itself is actually communicating with a natural person, or whether a human intermediary is exercising meaningful review and control. If the AI drafts a response and a human reviews and sends it, the risk profile is very different from an AI agent autonomously replying to a customer, supplier, or employee. "The latter can start to look like direct interaction, even if it happens through a ticketing system or procurement portal rather than a chatbot window," he explained.
To stay compliant, organizations need to make deliberate choices about which agents are internal and which are customer-facing, and then set up appropriate barriers. Access and privacy controls should be present across the organisation, not just across the agents themselves. Weijdema used a useful analogy: "It’s all well and good telling an agent ‘don’t go into this room’; you also need to put a lock on the door." Ultimately, he said, "the AI Act does not care whether the interaction happens in a chatbot window or a ticket queue. It cares whether the human is effectively dealing with the machine."
Cloned Voices and Simulated Phishing: Transparency vs Realism
Security teams routinely run simulated phishing and vishing exercises to train employees, sometimes cloning an executive's voice to make the simulation more realistic. The exercise arguably fails if the material carries a label saying it is AI-generated. But Weijdema warns that these exercises are not automatically exempt from the AI Act's transparency requirements, and organisations should not assume they are.
Cloning an executive's voice is particularly sensitive because it can turn into a deepfake scenario. A security purpose does not automatically create an exemption, and the argument that the exercise works better without disclosure is not a compliance justification on its own. Weijdema advises security teams to involve legal and compliance departments early, and to document their reasoning thoroughly. Privacy, HR, and, where applicable, works council or employee representatives should also be consulted, especially when a real person's voice, image, or likeness is used.
In many cases, the safer route is to use fictional personas, synthetic voices that do not imitate real employees, prior general notice that simulations may use synthetic media, and immediate post-exercise disclosure. The goal is to preserve realism without normalising undisclosed executive impersonation inside the company. If an organization does choose to proceed without disclosure, the documentation should demonstrate the purpose of the exercise, its scope, the AI tools used, whether any real person was imitated, what disclosure was provided and when, what personal data was processed, why the approach was necessary and proportionate, what safeguards were in place, and how employees were debriefed after the exercise.
Weijdema’s advice to security teams is blunt: "A security objective does not magically turn an undisclosed deepfake into a compliant one. If you have to clone the CEO’s voice to make the test work, legal should be in the room before anyone presses send."
The First Article 50 Action: Regulator Led, but Likely Complaint Triggered
The readiness of national authorities remains uneven. As of mid-June, only nine of the twenty-seven member states had designated both a market surveillance authority and a notifying authority. Twelve had partial designations, and six had neither. This fragmented landscape raises the question of where the first Article 50 action will originate. Formally, enforcement responsibility sits with market surveillance authorities, so the first action will probably be regulator-led. But in practice, the trigger may come from a complaint.
Defamation claims are possible, especially where synthetic audio or video damages someone’s reputation, but that is more likely to be a parallel legal route than the first clean Article 50 case. Consumer groups are also strong candidates because some AI systems affect or interact with large numbers of people. Weijdema expects the first case to be regulator-led on paper but complaint-led in reality—triggered by a consumer group, competitor, employee, journalist, civil society organisation, or an affected individual. The uneven readiness of national authorities means that some jurisdictions may become attractive forums for early enforcement actions, while others lag behind.
The Accountability Question No One Can Answer Yet
The question clients keep asking, according to Weijdema, is: "How do we prove what an AI agent did, why it did it, and who was accountable?" It is a hard question with no real good answer yet. In cybersecurity and GRC, evidence is critical: logs, approvals, identities, access controls, retention, and audit trails. But agentic AI can reason, retrieve data, generate content, and take actions across multiple systems. Governance must therefore move from policy documents into technical controls.
Weijdema advises clients to treat AI agents like privileged digital identities. Each agent should have an owner, a defined role, least-privilege access, monitoring, approval gates, and a kill switch. Organisations that get this right, he says, "will not just be more compliant. They will be more resilient."
Another unresolved question is where transparency ends and security testing begins. Security teams need realistic simulations, but the AI Act pushes organisations toward disclosure when people interact with AI or are exposed to deepfakes. The hard part is designing exercises that remain realistic without crossing legal, ethical, or employee trust boundaries. "Security teams want realism. Regulators want transparency. The challenge is designing exercises that satisfy both."
Weijdema also lists other questions that remain unanswered: Who is ultimately accountable when an AI system causes harm—the vendor, the deployer, the business owner, or the executive team? How do we prove to regulators, customers, and the board that AI governance is working in practice, not just documented in policy? And how much business value are we willing to lose to stay compliant, transparent, and auditable when using AI at scale?
The EU AI Act is a landmark regulatory framework, and its transparency obligations under Article 50 are designed to ensure that people know when they are interacting with a machine rather than a human. The first year of enforcement will set important precedents. Organisations that treat this period as an opportunity to strengthen governance, document decisions, and build human oversight into agentic systems will be in a far stronger position as the regulatory landscape matures. As Weijdema notes, the compliance burden is significant, but resilience and transparency are not opposites. In the emerging world of agentic AI, they are two sides of the same coin.
Source:Help Net Security News