A more interesting example: substitute natural numbers with binary trees. After all, they're equivalent. Now univalence would have to implement the binary tree analogue for every function on naturals, in a way that preserves semantics with respect to our conversion function.
Another addendum to the discussion, from an angle more relevant to computer programmers: if we find a computational meaning for the univalence axiom, then it'll be a crazy nuclear weapon of generic programming and code generation.
The univalence axiom says that two types are equal if we can convert their values back and forth (without loss of information). For example, one Boolean type may be defined as an enum containing True and False. But we could rename the values to Foo and Bar and it would be still a fine implementation, because it's easy to convert between the two representations. We can imagine more far-fetched representations too, with more complicated conversion functions.
But in type theory, if two types are equal, then we can freely substitute one for another in any context! For example, if we have a function "Bool -> Bool", and we know that Bool is equal to Bool2, then we can coerce the function to type "Bool2 -> Bool2".
Imagine a complex program that uses a complex piece of data type. If we can provide a correct conversion function to another type (i. e. prove that the type is equivalent to another one), then the univalence axiom can take the conversion function and our program as input, and spits out a new program that uses the new data type, and also preserves all properties of the program. By our current standards of generic programming, this is just insane!
Now, the issue is that currently we don't actually have a computational interpretation for the univalence axiom, so the above magic doesn't yet work. But there is meaningful progress towards that, and there are already some experimental implementations that can do some magic, for example this one: