Background: Multiple sclerosis (MS) commonly affects balance and mobility, yet routine clinical tests may lack sensitivity to subtle change. Standardized mobility assessments such as the Timed Up and Go (TUG), six-minute walk test (6MWT), and Romberg balance test are widely used in neurorehabilitation but rely on manual timing or laboratory instrumentation. In this study we evaluated whether motor outcomes derived from augmented-reality (AR) glasses (Magic Leap 2) can provide valid, minimally instrumented measures of balance and gait. Methods: Forty-six adults (26 people with MS; 20 healthy controls, HC) completed Romberg balance testing, TUG, and 6MWT while wearing a head-mounted AR device. AR outcomes were derived from AR glasses and processed using proprietary Strolll algorithms. Gold-standard reference measures were collected concurrently using 18-camera motion capture (100 Hz) and force plates for Romberg (1000 Hz). Primary outcomes were sway area (Romberg; 95% ellipse area), task duration and total distance (TUG/6MWT); secondary outcomes included mean gait velocity and step count (TUG/6MWT) as well as cadence, step length, and number of laps (6MWT). Concurrent validity was quantified using ICC(2,1) absolute agreement, Bland-Altman plots, mean absolute error and root mean square error. Results: Agreement was excellent for primary outcomes, including TUG duration (ICC = 0.927–0.992) and 6MWT total distance (ICC = 0.966), with low absolute error relative to clinical variability. Secondary gait-derived metrics demonstrated good-to-excellent agreement (ICC range 0.750–0.980). AR-derived sway area showed poor-to-good agreement with force plate COP sway area across stance conditions. Agreement was preserved across healthy and clinical cohorts and across task variations. Conclusions: Head-mounted AR–derived outcomes demonstrated good-to-excellent concurrent validity against laboratory gold standards in MS and controls, with strongest performance for global mobility metrics (i.e., duration, distance, mean velocity) and more variable performance for step-derived measures (e.g. cadence, step length). These findings support AR-based assessment as a valid minimally instrumented approach, providing measurement performance consistent with gold-standard metrics for TUG and 6MWT (time, distance) and showing its potential for objectively monitoring disease progression and supporting rehabilitation in clinical and community settings.