Good luck precomputing all those pairwise shortest paths. Storing the table might not be too bad. But standard algorithms like Floyd-Warshall are O(n^3) in the number of vertices. There are faster algorithms based on fast matrix multiplication but the precomputation time would still be prohibitive. Keeping it up to date would be even worse. The construction of a new highway could require updating the shortest paths for an enormous number of pairs.
The economic argument would go like this: The revenue generated from your maps business is proportional to the number of queries actually processed, not the total number of conceivable queries. The queries processed is such a tiny subset of the possible queries that you want your computational expenses to track the former, not the latter.
With a hierarchical shortest paths algorithm, you can still precompute all pairwise shortest paths at the coarser level. For road navigation you might precompute the shortest path between every pair of interstate highway exits in the USA like this paper is doing. In an open-world game like Skyrim you might precompute the shortest paths between all towns and other major hubs and points of interest. That might not yield truly optimal paths. For game use it's close enough and has the benefit of corresponding to how humans naturally navigate.
Sidebar: The old Crash Bandicoot games used precomputed shortest paths in a neat way. Their navigation was based on a triangular mesh, so every triangle had up to three edgewise neighbors. Thus for a navmesh with n triangles, they needed lg(3) n(n-1)/2 <= n(n-1) bits to store the table. For convenience they probably stored this in a redundant form requiring 2n^2 bits = n^2/4 bytes. But with only 64KB of additional memory, this still let them support 512 navmesh triangles per level with lightning-fast path finding.