But with the rise of AI, the dynamic is changing: We are observing a significant increase in request volume, with most of this traffic being driven by scraping bots collecting training data for large language models (LLMs) and other use cases. Automated requests for our content have grown exponentially, alongside the broader technology economy, via mechanisms including scraping, APIs, and bulk downloads. This expansion happened largely without sufficient attribution, which is key to drive new users to participate in the movement, and is causing a significant load on the underlying infrastructure that keeps our sites available for everyone.

- https://diff.wikimedia.org/2025/04/01/how-crawlers-impact-the-operations-of-the-wikimedia-projects/

This is part of the larger problem that AI tools are trained on (and profit off of) content that is produced and hosted by others who are now seeing their traffic change from humans to bots. For content sources that pay for hosting with ads, this means a loss in revenue to pay for hosting. For content sources like Wikipedia, they are seeing their hosting costs increase significantly due to the increase in bot traffic. Even if you want every website that depends on ad revenue to fail (which I don’t entirety agree with), AI is still damaging the open web in other ways. Websites like Wikipedia for example may soon be forced to lock content behind logins or leverage aggressive captchas just to fight the bot traffic, which makes things worse for those of us that still prefer to use actual websites over AI summaries.