Artificial intelligence opens up numerous new possibilities in online research. Synthetic data, automated quality assurance, intelligent recruitment strategies, and new pattern recognition tools promise unprecedented efficiency—while also raising fundamental questions: How reliable are AI-generated samples? Can algorithmic methods really reduce nonresponse? And how can we prevent models from reproducing systematic biases on a large scale?

Using concrete examples, the presentation shows how AI can improve data quality, what pitfalls lurk in automated data generation, and what skills are needed to work with it responsibly. The goal: a realistic, inspiring look at the interplay between statistics, humans, and machines – practical and future-oriented.