Traditional ordinal models, such as cumulative logit/probit, struggle when data show excess zeros, which may indicate absolute non-knowledge or occasional participation. Zero-inflated approaches address this by distinguishing structural from sampling zeros. Our study applies these methods to 599 Italian Millennials and Generation Z respondents from the CA19130 Fintech and Artificial Intelligence in Finance project. Using a six-point ordinal scale, we analyze knowledge of cryptocurrencies, a growing yet underexplored asset among younger generations. Preliminary results reveal higher knowledge linked to blockchain/AI awareness, while women, less-educated, and low-income individuals more often report “zero knowledge.”