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Muscle ultrasound is a valuable addition to the neuromuscular toolkit in both the clinic and research settings, with proven value and reliability. However, it is currently not fulfilling its full potential in the diagnostic care of patients with neuromuscular disease. This review highlights the possibilities and pitfalls of muscle ultrasound as a diagnostic tool and biomarker, and discusses challenges to its widespread implementation. We expect that limitations in visual image interpretation, posed by user inexperience, could be overcome with simpler scoring systems and the help of deep-learning algorithms. In addition, more information should be collected on the relation between specific neuromuscular disorders, disease stages, and expected ultrasound abnormalities, as this will enhance specificity of the technique and enable the use of muscle ultrasound as a biomarker. Quantified muscle ultrasound gives the most sensitive results but is hampered by the need for device-specific reference values. Efforts in creating dedicated muscle ultrasound systems and artificial intelligence to help with image interpretation are expected to improve usability. Finally, the standard inclusion of muscle and nerve ultrasound in neuromuscular teaching curricula and guidelines will facilitate further implementation in practice. Our hope is that this review will help in unleashing muscle ultrasound's full potential.