Our study showed that improvement in balance performance is task-specific, with transfer depending on functional similarities between the trained and the untrained tasks. Computational nonlinear methods highlighted that training could extend the improved efficiency and automaticity of balance control of the trained task to a similar untrained task. Therefore, the benefits of balance training may not generalize to all balance challenges, highlighting the importance of targeted testing and training approaches.