Maybe this kind of AI-based exploration would lower the costs. The more something is automated, the cheaper it should be to test many concepts in parallel.
But no one is going to bring it to market because it costs millions and millions to synthesize, get through PK, ADMET, mouse, rat and dog tox, clinicals, etc. And the FDA won't approve marginal drugs, they need to be significantly better than the SoC (with some exceptions).
Point is, coming up with new ideas is cheap, easy, and doesn't need help. Synthesizing and testing is expensive and difficult.
If you could run that on a few thousand targets and a few million molecules in a month, you'd be able to make a compelling argument to the committee that approves molecules to go into development (probability of approval * revenue >> cost of approval)