A Record of Processing Activities (VVT/RoPA) can become a significant economic factor—if used correctly. How a legal regulatory requirement can lead to a measurable return on investment (ROI).
At the end of September, the European Commission launched a public Consultation to Guidelines and a reporting form for "serious AI incidents" in accordance with the AI Regulation. The aim is to clarify the handling of serious incidents involving high-risk AI systems before the reporting obligations become mandatory from August 2026.
We see it every day: Companies use AI in isolated instances, but no one has a view of the big picture. However, a solid foundation for decision-making can only be created with an AI inventory, workflows, and reliable documentation. Find out now why an AI inventory is indispensable for your company, too.
On September 29, 2025, California Governor Gavin Newsom signed the „Transparency in Frontier Artificial Intelligence Act“ (SB 53) into law. It requires the state’s major AI companies to comply with new Transparency- and safety requirements. Why SB 53 sends a message that extends far beyond California.
A RoPA is much more than just a burdensome mandatory document. When implemented correctly, it becomes a strategic data and process map: It provides an overview, reduces risks, and enables efficiency gains. Here’s how to put it into practice.
At the very latest when companies are implementing multiple parallel AI projects, a common framework for evaluation becomes essential. Otherwise, it is nearly impossible to compare different departments, models, and types of applications. A centralized risk model ensures that all projects are evaluated according to the same criteria.
Model maps make AI transparent. They document the purpose, data sources, versions, performance metrics, and limitations of AI models. Those who consistently apply them and integrate them into workflows gain auditability and can scale reliably. Easily use model maps in conjunction with Ailance AI Governance.
While the use of AI in companies is increasing rapidly, the development of structures for responsible AI and its governance is lagging behind. Several recent studies clearly show how companies benefit from AI, but at the same time lack trust due to a lack of governance, Compliance and security.
Whether for texts, code or translations: AI tools have long since arrived in everyday working life. However, many AI tools are used without the departments responsible for IT, data protection or Compliance become aware of it. The phenomenon has a name: Shadow AI. What begins as a small help can quickly lead to data protection incidents and liability issues.
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