Objective. The aim was to explore possible biomarkers and to start researching voice-related biomarkers. Introduction. Biomarkers must have a prognostic/predictive value and a monetary value. Although it appears trivial, the content and subjects of phoniatric aspects of voice-related biomarkers is not obvious, for phonation, ventilation, and airway protection, as well as related to artificial intelligence (AI). Material. The frequency of dysphonia is 3–9% of the adult population. As an example related to dysphonia Parkinson’s disease means many millions worldwide. Method. The literature was therefore searched for voice-related parameters in Parkinson’s disease that were measured and evaluated, as indications of voice, pathogenic processes, and responses to therapeutic interventions. Evaluations for further searches were made. Other newer papers, especially those involving aspects of AI usability in connection with biomarkers, were also focused upon. Results. The Union of European Phoniatricians and the European Laryngology Association have made an updated consensus paper, 2023, of advisable clinical voice parameters. Parkinson’s disease is a good example of biomarkers, measuring patient complaints, evaluation of hoarseness, and suggestions for measurable acoustic and airflow parameters. In recent years, AI has focused on usable software in some of the AI literature. Conclusion. A suggestion for voice-related biomarkers is given. Parkinson’s disease is used as an example.