You may laugh, but it seems scarily plausible to develop a machine algorithm that generates 12 articles, have a human go through to pick the 3 least-ridiculous ones and do some light editing, and push it out to the news.
Motley Fool seems to be the leaders in this -- if you search google news for any stock you're interested in then you'll find that Motley Fool seems to be cranking out largely-boilerplate articles about it; sometimes they seem to have had some human intervention, other times they seem to be fully computer-generated.
I was seeing credible copy produced for financial reporting in the late 1990s.
The underlying data are available, the vocabulary is distinctly limited, and the reporting was already highly pro-forma. Mad-libbing a few variants of language and selecting the best of the lot does work fairly well.
That actually raises the underlying question: why publish narrative copy at all in cases such as this, rather than data tables or charts? News and journalism are curiously allergic to data or presenting it in a usable fashion -- I've seen tables essentially written out over several paragraphs that could have been expressed in a few grid squares.
Routine financial news, sports... Anything that can be largely churned out in boilerplate fashion based on some standard facts. This has been done for a while now and it will only increase as long as there's a business model for quickly published, largely undifferentiated, rote stories. It's a low-cost, high-volume game.