AI models are interchangeable, but their impacts are not. Whether a system poses a low or high risk depends not on the technology, but on its intended use. Modern AI governance must therefore focus on the use case, not the specific tool. This article explains how companies can make risks manageable.
With reference to its previous case law, the ECJ has clarified the meaning of the term "personal data" in connection with the Transmission pseudonymized data to Third specified.
As part of the „Digital Omnibus,“ the European Commission is planning a far-reaching reform of the General Data Protection Regulation, which will focus in particular on the rules for online—Tracking and cookie banners. Here are the most important changes.
In Ailance, you can use the Share button to share a context-specific link from any record or view. This is ideal when you need colleagues to quickly review, approve, or adopt something. The recipient is taken directly to the right place without having to click through multiple levels of menus.
The AI Regulation requires companies to provide a complete technical Documentation to create. But the documentation requirement also provides a crucial tool for ensuring traceability and quality. Those who document their AI understand it and can also take responsibility for it. Here’s how that works in practice.
Anyone who works with Ailance RoPA on a regular basis knows this: You’re constantly switching back and forth between processing activities, involved parties, and data protection impact assessments (DPIAs). It’s easy to lose focus and waste time in the process. There’s a simple trick that can help: the multi-tab workflow.
What is the relationship between the Digital Markets Act (DMA) and the General Data Protection Regulation (GDPR)? The European Data Protection Board (EDPB) and the European Commission have published joint Guidelines have been drawn up. These show how the two legal acts interact with each other and how potential conflicts can be avoided.
From chatbots to scoring: Every AI system in a company requires measurable accountability, clear documentation, and a robust process. Taking a structured approach now protects data, brand value, and the ability to innovate. The starting point: A centralized AI inventory, standardized workflows, and model maps, all managed through Ailance AI Governance.
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