Math is like code: technical debt makes moving forward much harder.
On a long enough timeline, you're right! But if we limit ourselves to, say, the next 5,000 years, it gets a lot easier to accomplish. ;)
Fast Fourier transforms, complex numbers, complexity classes, etc. are clearly useful. It's much harder to rigorously claim that a result will _never_ be practical or useful.
Just to be clear, I think it's fair to say that a result isn't _immediately_ useful. But who can say whether or not it will have a more practical application down the road? Only time will tell.
Mendel's discoveries weren't appreciated until after he died. When Narinder Singh Kapany invented fiber optic cable in the 50s he had no idea it would lead to revolutions in computer networking, gastroenterology, and other fields.
Aleksandr Lyapunov's theory of stability for dynamical systems, which forms the bedrock for much of control theory, was first proposed in 1892 and went unnoticed until the 1930's [2]. How practical was it for Lyapunov to study that topic?
It's virtually impossible to predict which mathematical tools will be "practical" or "useful" in the future. The point is that if someone needs the tool down the road, they'll have access to the solution due to the efforts of these mathematicians.
[1]: https://en.wikipedia.org/wiki/Neural_network#History
[2]: https://en.wikipedia.org/wiki/Lyapunov_stability#History