IT projects

Episode 44 of the Data Navigator podcast focuses on FRAND in the Data Act – specifically, the conditions under which data owners must disclose IoT data to third parties and what they are permitted to charge for this. Martin Schirmbacher and Hubertus von Rönne explain the details of the new legal framework. The starting point is the familiar triangle: a user (e.g. a wind farm operator) instructs the manufacturer (e.g. Vestas) to send operational data directly to a third party (e.g. the start-up Turbit). To this end, a contract must be concluded between the manufacturer and the third party (see Art. 8 Data Act), and remuneration is governed by Art. 9 DA, all on FRAND terms. The user, however, may request the data free of charge. Martin and Hubertus go through in detail which costs the manufacturer is permitted to charge (provision costs, onboarding, margin where applicable, and investment costs – though the latter, for example, not vis-à-vis SMEs), which billing models the Commission’s draft guidelines provide for, and what ‘non-discriminatory’ means in practice. Key principle: The value of the data itself must not be priced. The conclusion: Remuneration issues will develop differently depending on the sector. At present, progress is often still stalling on fundamental issues: What data is actually being shared, and how should it be categorised? The call remains: producers, users and data recipients must come together within their respective sectors and also discuss the terms of data provision.

Artificial intelligence is fundamentally transforming drug development – making it faster, more efficient and data-driven. However, the more powerful the systems become, the greater the regulatory challenges. New guidelines from Swissmedic, the WHO and international organisations show that without clear governance, there is a risk to patient safety and market integrity. Companies are faced with the question of how to ensure both innovation and compliance at the same time.

The Data Act harbours many ambiguities. We have collected and answered the most frequently asked questions about the Data Act from presentations and client work. Is your question not included? Then please get in touch with us!

Cloud computing is now regarded as the backbone of the digital economy. However, as soon as critical infrastructure is affected, a key question arises: how can the benefits of the cloud be reconciled with the high demands placed on security and business continuity?

Artificial intelligence (AI) that takes over purchasing in companies, autonomously monitors product stocks, researches prices and triggers orders. The proactive assistant that answers emails, manages calendars and checks in for flights. Or AI-to-AI or multi-agent systems that take over the entire checkout and where all processes on both the buyer's and seller's side run entirely within an AI interface - the use of AI agents or agentic AI promises completely new possibilities. Companies, and in particular retailers, that decide to participate in this new AI-based ecosystem must also be aware of the legal pitfalls: What are the legal rules of the game when AI suddenly negotiates and concludes contracts independently? Who is liable for what?

How can incorrect personal data in the Central Migration Information Systembe corrected? Three recent rulings by the Federal Administrative Court and the Federal Supreme Court provide answers and show how the Data Protection Act (DPA) is applied in practice.

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With the new e-ID, users will be able to identify themselves digitally securely, quickly and easily in future with the best possible data protection.

AI can be used to write dialogue, quests and item descriptions. In addition, it can generate art assets, game items and other objects. AI models will also greatly simplify the procedural generation of game worlds. The limits of the use of generative AI seem to depend solely on the imagination of the developers.