AI web scraping has moved from a niche engineering topic to something data teams across industries are actively building into their workflows. The tooling landscape has expanded quickly, and the options now range from open-source Python libraries to fully managed APIs with LLM-powered extraction. That variety is useful, but it also means the differences between approaches matter more than ever, especially when accuracy and cost at scale are on the line. This article breaks do