The evaluation of wine quality has shifted from the exclusive domain of expert tasters to an expansive collection of free comments—the unsolicited, user-generated tasting notes and opinions collected online without standardized prompts. Whereas these data enable analysis at an unprecedented scale, they also pose a significant challenge: extracting reliable insights from text that is inherently subjective, noisy, and potentially biased. Artificial intelligence (AI) developments offer powerful tools for analysing such data, while raising new concerns about synthetic or AI-generated reviews that may distort our understanding of wine reviews and notes. This chapter traces the historical transition from expert-driven tasting notes to free comment big data, situates the discussion within sensory and consumer science frameworks, and details computational methodologies (especially sentiment analysis) tailored to online wine reviews. A direct comparison between human-derived sentiment scores and AI-generated outputs demonstrates a moderate and statistically significant association, suggesting that AI can approximate human judgment with practical precision. The chapter concludes by examining the limitations of free comment data, including the emerging issue of AI-generated content, and offering perspectives on future directions as analytical capabilities and data-quality challenges continue to evolve.