With modern AI programs, documentation should not be treated as mere paperwork, but as strategic control. In essence, it should serve as a dashboard for performance and risk. Without transparent and effective documentation, we are facing unmanaged risk that is not only a technical issue but also a matter of governance and, ultimately, business.
Two tools have become de facto standards for the documentation of AI-based programs: Datasheets for Datasets and Model Cards. They are the foundation for safe deployment, clear risk ownership, and faster decision-making.
This white paper provides an in-depth analysis of all relevant areas of documenting with model cards and datasheets:
- What they are and what data they contain
- What benefits they provide
- Why they are superior to static documentation
- How to roll them out without overhead
- A practical template you can implement
These “nutrition labels” that many AI models are missing make a significant impact because they are concise, structured, and focused on what leaders need to know: where the model and data came from, how they perform, where they are safe, and how they change over time.
Download the white paper to find out how to get started.
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