It just doesn't deliver on performance, or energy consumption. That was always going to be the case (you are adding a layer of abstraction at the
silicon level). So for anything that is measured on "operations / second" or "operations / joule", FPGAs will always lose out. By now industry has learned that the key is to tailor algorithms for what we can do fast (vector+branching on CPU, everything branchless on GPU), not shoehorn silicon into algorithms.
So what can FPGA do? Fast, low latency, high bandwidth interaction with peripherals. The irony here is that to have this work out, you kind of want to have your peripheral connected to the FPGA.. which takes away all the fun from the reconfigurable stuff, because you can't reroute your PCB. So now 99% of FPGAs deployed end up running in the same configuration always and companies with the necessary scales pour it into ASICs.
FPGAs solve a niche problem of interacting with very fast, massively parallel data buses and systems (think CCD sensors, ADC sampling, ..) that a linear execution, Turing style processor isn't suitable for. And pretty much only for applications where you don't have the volume to convince a chip manufacturer to put your peripheral into silicon.