The core of AI-driven recommendations lies in data analysis. By collecting and processing vast amounts of data, AI algorithms identify patterns and trends. This information is then used to make personalized suggestions tailored to individual users. Popular techniques include collaborative filtering, content-based filtering, and hybrid methods combining both approaches.