Agreed. It's great that we have domain-specific approaches that can beat humans in their domain (and that we're learning how to make these approaches more generic so that, with re-training, they can adapt to new domains), but the real "oh snap" moment will be when we build something that's barely-adequate but widely adaptable. Something with the adaptability of a corvid or an octopus, say. If we get to that level, it'll mean we've discovered the "universal glue" that joins specialist networks together into a conscious entity.
Universality is the real hard problem of AI. In the long run, a mediocre AI that does a lot of different things is far more useful that most targeted "superhuman" AIs. Most domains simply don't require better-than-human performance, but could still reap tremendous benefits from automation.