Maybe one thing that you can consider is not only “why people should give it a try” but also the opposite - what are the hurdles that may stop people from doing so.
You probably know the “main language” in your field but can look in the fields of your audience in the talk. For example, my research field applied macroeconomics, particularly Bayesian Econometrics and like 90% of the codes of papers that get published in the good journals are in Matlab. So if I want to integrate the latest and the greatest from the research in my work I either have to translate thousands of lines of code or just build on top of the others (the standing on the shoulders of giants). If we get a new PhD at our institution that wants to work in this field they have to, more or less, learn matlab. Maybe look around if there are julia codes in the fields of others that might help.
Building on that it would be great if you can find particular applications (w.r.t. the people in the audience) where Julia’s strengths are highlighted. For example I am still struggling and constantly abandon the language because I cannot find an instance where Julia is better for me and my particular codes are always slower than comparable matlab codes. In some instances it was actually non-language related (I have touched on this here). In any case switching to any new programming language is extremely costly, so it has to be very, very well justified.