Artificial Intelligence (AI) and Chemometrics are revolutionizing data interpretation in analytical sciences by enhancing accuracy, speed, and predictive capabilities. Chemometrics involves applying mathematical and statistical methods to extract meaningful information from complex chemical data, improving the reliability of analytical results. AI, including machine learning and deep learning algorithms, enables automated pattern recognition, classification, and decision-making from large datasets. When combined, AI and chemometrics help in optimizing experimental design, modeling multivariate data, and interpreting results from techniques like spectroscopy, chromatography, and mass spectrometry. These tools are particularly valuable in pharmaceutical development, environmental analysis, and quality control. Their integration reduces human error, enhances sensitivity, and accelerates research by transforming raw data into actionable insights, driving innovation across scientific and industrial domains.