Even for stuff that a lot of other programs can do just fine, SAS often has an edge. For example, everybody and their brother can do a logistic regression model... but SAS can give you confidence intervals for all kinds of crazy parts of the model that SPSS won't even bother calculating and that R will only give you point estimates for.
The other great thing about SAS is that a lot of the good statistics books from the last twenty or thirty years include SAS sample code- for example, I'm currently having to do some off-the-beaten-path ANOVA stuff, and the reference I'm using (Edwards' "Analysis of Variance for the Behavioral Sciences") uses SAS as its language of choice.
That said, I personally find the SAS "language" to be alternatively bewildering and nostalgia-inducing (the "cards" command, anybody?). SAS is the only language about which I can honestly say "it makes R's syntax look clean and predictable". Also, the Windows version of SAS is an absolute abomination from a UI standpoint. And, their licensing schemes are draconian, and installing the damn thing can easily take an entire day, especially if (say, for example) the installer gets confused because you've already got a JDK installed on your computer. Not that I'm bitter, or anything...
Of course, as others have noted, in bioinformatics, R either is already the default or is almost there. I know that in my department's bioinformatics courses, they use R, Python, and Perl almost exclusively, and only break out the SAS when there's something specific they need it to do.