Web scraping faces challenges due to the dynamic nature of websites and the vast amount of data generated daily, which traditional scraping methods struggle to handle effectively. Artificial Intelligence (AI) enhances web scraping by using machine learning techniques to adapt to dynamic website structures and advanced anti-scraping technologies, thereby improving accuracy, scalability, and speed. Conventional web scraping involves sending HTTP requests and parsing HTML to extract data, but it struggles with dynamic content, complex website structures, frequent changes, and sophisticated anti-scraping measures like IP blocking and CAPTCHAs. AI-powered scrapers, however, can autonomously adapt to changes, handle large-scale data scraping, and mimic human browsing behavior to circumvent advanced anti-scraping technologies. While training AI web scrapers can be complex, tools like Bright Data provide solutions with proxies and web unlocking features that facilitate efficient and accurate data extraction from websites.