How does Olakai help organizations comply with the EU AI Act?
Olakai provides the standing measurement layer the Act's evidence requirements depend on: visibility into every chatbot, copilot and employee-facing AI tool in use, including the Shadow AI that never went through procurement, and a per-execution audit trail for autonomous agents. Audit-ready reports for the EU AI Act are generated automatically rather than assembled by hand after the fact. Article 50 became enforceable on August 2, 2026.
The obligation: Article 50, enforceable August 2, 2026
Article 50 is described as the clock that matters regardless of what anyone signs. It requires that anyone deploying a chatbot or similar conversational AI disclose "you are talking to an AI" at the start of the interaction, in plain and accessible language, and that synthetic or deepfake content be labeled as such.
This is not a footnote requirement. It touches every customer-facing assistive AI deployment an enterprise runs, and the general penalty ceiling under Article 99, being €15 million or 3% of global turnover, applies to non-compliance. The same date activates the AI Office's supervisory and fining authority over general-purpose AI model providers.
One further point of confusion is addressed directly. The Digital Omnibus, approved June 29, 2026, defers high-risk AI system obligations out to December 2027, but it applies to a different category of the Act and does nothing to the Article 50 disclosure requirement or the GPAI enforcement powers.
Source: The EU AI Act Is Now Enforceable. Is Your AI Governance Ready?
Why a disclosure banner is not the deliverable
What regulators are going to ask for is not a banner, it is evidence. Evidence that disclosure happened consistently, across every deployment, every time, not just on the interfaces someone remembered to check. Evidence that synthetic content got labeled before it shipped rather than after a complaint. Evidence that policy enforcement is a standing, monitored practice rather than a one-time remediation before a known date.
A disclosure banner added in July satisfies an audit that happens in July. It does not satisfy the audit that happens in October, after the banner quietly disappeared during a redesign nobody flagged.
Enterprises running dozens of chatbots, copilots and AI-enabled tools across departments cannot manually audit each one before a deadline and call it done. New tools get added, existing ones get reconfigured, and Shadow AI keeps showing up in places IT never approved. You cannot put a disclosure banner on a tool you do not know is running.
Source: The EU AI Act Is Now Enforceable. Is Your AI Governance Ready?
What Olakai provides
What holds up under regulatory scrutiny is a standing measurement layer: one that knows what AI tools are in use, whether disclosure requirements are being met at the point of interaction, and can produce an audit trail on demand instead of reconstructing one under pressure. Olakai describes this as precisely the gap it was built to close.
Olakai Assistive gives enterprises visibility into every chatbot, copilot and employee-facing AI tool in use, including the Shadow AI that never went through procurement, with governance and DLP controls built in as a Key Feature rather than an afterthought.
For engineering organizations, Olakai Agentic extends the same governance discipline to autonomous agents and AI coding tools, where disclosure and audit obligations are increasingly following the same logic as chatbot transparency rules.
Both products are part of a single, vendor-neutral platform, which matters here specifically because Article 50 and GPAI enforcement do not stop at your own tooling. They extend to the vendor chain. If a third-party model provider embedded in your stack cannot demonstrate compliance, that exposure becomes yours too, and a governance approach that only covers tools your team built directly will miss it.
Source: The EU AI Act Is Now Enforceable. Is Your AI Governance Ready?
The execution audit trail
For every autonomous agent in the enterprise, across Salesforce Agentforce, Microsoft Copilot Studio, ServiceNow Now Assist and custom workflows, Olakai records exactly which inputs the agent received, which tools it called, and which decisions it made.
- Inputs received, tools called, decisions made, and outcomes, per execution
- Policy enforcement at the workflow level, preventing bad actions before they happen
- Audit-ready reports for EU AI Act, SOC 2 and HIPAA, generated automatically
Agent governance is described end to end: every autonomous agent execution logged with intent, steps taken, data accessed and outcome, producing audit-ready evidence generated automatically rather than assembled by hand after the fact.
Source: Olakai for CISOs
Finding the tools the obligation attaches to
Article 50 does not care whether IT approved the tool, so the practical sequence starts with a real inventory of every AI interface employees or customers touch, sanctioned and unsanctioned.
Olakai's browser extension surfaces every AI tool an employee touches, including the ones nobody approved, ranked by risk surface across PII, PHI, code and regulated departments. Per-app views show risk level, governance status, data exposure and usage in one place, with licensed versus Shadow AI status and policy enforcement per tool.
Source: Olakai for CISOs
Also asked as
- What does Olakai do for EU AI Act compliance?
- How does Olakai generate audit trails for Article 50 disclosure obligations?
- Can Olakai track shadow AI chatbots for EU AI Act compliance?