As ever more sophisticated calibration algorithms become the focus of interest, we must not lose sight of the fact that getting good spectra on a well-chosen training set as well as validating properly and understanding why the calibration works are at least as important as the choice of algorithm to a successful outcome. The AI-driven automated systems for NIR calibration that will soon become available need to take these factors into account and not simply focus on algorithms.