Currently humans are much better at proofs that require this kind of deep thinking. Automated tools are better for proofs that are based on a simple structure, like a large enumeration of cases (as in SAT solving and model checking, oversimplifying things a bit). This is the very reason they are automated: the reasoning performed by them is so simple/well-structured that we are able to write a program to do it for us.
However, many proofs fall outside of this easy-to-automate subset, and require human assistance. Human intuition does consistently do better than automated tools, but there is no single easily recognizable "trick" or "method" to it, which makes it hard to implement in a tool.
In my view, the reason that theoretical results do not apply very directly to human reasoning is precisely that human reasoning is "intuitive" and hard to capture in a program. We are not really Turing machines in any practical sense. We are more adept at proving things (perhaps creating automated tools to help us along the way) than any known algorithm.
I absolutely agree that automated tools make much more sense for your average industry application, but if you want to be able to use the full power of human intuition, instead of restricting yourself to program properties that are easy to prove automatically, then there is no way around manual proofs.