How data science and the next wave of open-source innovation are closing the €50B efficiency gap in Enterprise AI.

Today, 75% of data science output is lost to fragmented data, scattered tooling, manual workflows, and poor reproducibility. Yet nearly every data scientist relies on scikit-learn — the backbone of modern AI/ML.

We’ll unpack the root causes of inefficiency in enterprise data science — and show how open-source tools are unlocking performance, reproducibility, and strategic autonomy at scale.