1) Big-picture Op/Ed (of the kind you're talking about)
2) Investigation (of the deep, involved, I-need-to-know-where-to-start, I-need-to-get-people-to-talk variety)
3) Narrative nonfiction (profiles, colorful takes on a subject; see: The New Yorker, Michael Lewis, etc.)
The interesting thing is that each of these domains could be enhanced by the use of better software. And that's the best way to start looking at bot-fueled journalism. I'd love a machine-based fact checker for my pieces. I'd love AI-driven help with compiling and analyzing data. I'd love to outsource the high-frequency grunt work to a machine, just as it's done in many other industries. It would give me more time to think. It would let me focus where my focus matters. Instead of spending 99% of my time chasing raw research, and 1% of my time scrambling to assemble the piece, I could get more data, better, faster, up front, and thus put deeper thought into the analysis.
On that note: the journalists who thrive in the machine age will be the ones who understand what the machine is doing. Data-literacy is already a big, differentiating factor in the market now. Statistical competency will be very important, and the bar for competency will be positioned higher every few years. Beautiful logic will trump beautiful fluff.
This will accelerate the bimodal shake-out of journalism that we're already starting to see. We'll have base, commodified, LCD-pandering content farms on one end, and deep thought on the other. Quantity shops and quality shops, both of them improved by the automation of certain functions. Anyone in the middle ground is in trouble. This will be a good thing for both poles -- provided we can find a way to make the economics of quality work as well as those of quantity.