In this paper, we attempt to analyse the problem of conveying gender-neutral language when working with notional and grammatical languages (English and German) from the point of view of adaptive machine translation (MT). More specifically, we assess the efficiency of adaptive MT when it comes to gender-neutral language use, the purpose of which is to "reduce gender stereotyping, promote social change and contribute to achieving gender equality". We conclude that the initial output largely reflects cases of misgendering and generic masculine – problems that are well documented in the MT field, but which still remain unresolved. Moreover, our experiment revealed that ModernMT faces systematic difficulties in adapting to gender-neutral language when working with the English-German translation direction.