With the goal of uncovering the challenges faced by European AI students during their research endeavors, we surveyed 28 AI doctoral candidates from 11 European countries. The outcomes underscore challenges in three key areas: (1) the findability and quality of AI resources such as datasets, models, and experiments; (2) the difficulties in replicating the experiments in AI papers; (3) and the lack of human-centrism and interdisciplinarity.  Critically, there is a need for immediate adoption of responsible and reproducible AI research practices, crucial for society at large, and essential for the AI research community in particular. In this talk, we describe the results that we found in the survey and we analyze how the Reproducibility Initiative from AI4Europe and the AI on Demand platform can help overcome these challenges.