So I guess I still see declarative languages as being part of the tech stack and something tantamount to AI being needed to handle all the "do what I mean" that accompanies business process documentation.
It could be done directly if every BA had enough programming knowledge to put together schemas and run CLI tools to verify them.
That's quite a lot of programming knowledge. It makes some sense to decouple the business-oriented from the more technical roles - BA's trying their hand at coding is how you get mammoth Excel spreadsheets and other big-balls-of-mud.
As for formal methods, oh, where shall I even begin? The amount of time to turn something intuitive into correct predicate logic can be prohibitive to most of professionals. HN used to feature Eric Hehner's Practical Theory of Programming. I actually read through his book. I could well spend hours specifying a searching condition even though I could solve the search problem in a few minutes. And have you checked out the model checking patterns (http://people.cs.ksu.edu/~dwyer/spec-patterns.ORIGINAL)? I honestly don't know how a mere mortal like me could spend my best days figuring how to correctly specify something as simple as an event will eventually have between an event Q and an event P. Just for fun, the CTL specification is as follows:
``` G(Q -> !E[!R U (!P & !R & EX(P & E[!R U (!P & !R & EX(P & E[!R U (!P & !R & EX(P & !R & EF(R)))]))]))]) ```
As I said, formally specifying a system, no matter what tools one uses, is essential complexity.
An extreme example of this are logic and verification systems like prolog and TLA+.
There is a sweet spot of low code I haven't seen explored yet, which is a declarative system that is not Turing complete. That would be an interesting avenue to explore.