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What is web scraping?
Web scraping is the automated extraction of data from web pages into a structured format like rows or JSON. A scraper loads a page, finds the values you want (prices, listings, headlines), and saves them so software can use them. In 2026, AI scrapers write and repair the extraction rules themselves, so you no longer need to know CSS or XPath.
How web scraping works
A scraper fetches a page's HTML, locates the elements holding the data you care about, and copies their values into named fields. Traditionally you wrote CSS selectors or XPath to point at each field — brittle rules that broke whenever the site changed.
An AI scraper reads the page the way a person does. You describe the data in plain language and the model writes the selectors for you, then re-writes them when the layout shifts. This removes the single biggest maintenance cost of scraping: selector breakage.
What people use it for
The most common uses are competitive price monitoring, lead and market research, content and news aggregation, real-estate and job-listing tracking, and feeding live web data into AI and RAG pipelines.
The web scraping market was worth about USD 1.17 billion in 2026 and is growing near 13.8% a year, driven largely by demand for AI training and retrieval data.
Is it hard?
It used to require code. With a natural-language tool like Page Byte you paste a URL, describe the data in a sentence, and schedule it — no selectors, no servers. When the site changes, the extractor heals itself.