When we get to the post-AI age, we can worry about that. In the early LLM age, where context space is fairly limited, structured data can be selectively retrieved more easily, making better use of context space.
https://en.wikipedia.org/wiki/Category:Articles_with_infobox...
edit: slightly wider scope category pointing to pages using wikidata in different ways:
https://en.wikipedia.org/wiki/Category:Wikipedia_categories_...
Wikidata is incredibly useful for things that I would considered valuable (e.g. the tMDb link for a movie) but due to the curation imposed upon Wikipedia itself isn't typically available for very many pages. An LLM won't help with that but another bit of information like where films are set would be a perfect candidate for an LLM to try and determine and fill in automatically with a flag for manual confirmation.
Even humans benefit quite a bit from structured data, I don't see why AIs would be any different, even if the AIs take over some of the generation of structured data.
By the way, NASA and NSF put out a request for proposals for an open AI network/protocol.
Mediawiki is notorious for being hard to parse:
* https://github.com/spencermountain/wtf_wikipedia#ok-first- - why it's hard
* https://techblog.wikimedia.org/2022/04/26/what-it-takes-to-p... - an entire article about parsing page TITLES
* https://osr.cs.fau.de/wp-content/uploads/2017/09/wikitext-pa... - a paper published about a wikitext parser