In this study, we explore the feasibility and efficacy of leveraging Sanbot Elf – a humanoid intelligent assistive robot – integrated with artificial intelligence (AI), specifically the Vivaldi AI system, for functional assessment in amyotrophic lateral sclerosis (ALS) patients. Our investigation involves evaluating and comparing the performance of the Sanbot Elf in administering the ALS Functional Rating Scale–Revised (ALSFRS-R) to that of human operators, using a structured format where patients respond with either “yes” or “no” answers. This approach is intentionally adopted to minimize ambiguity in patient responses. Patients were given the option to respond either verbally or by utilizing the touchscreen display, particularly beneficial for those experiencing dysarthria or hypophonia. In addition, we examined patient emotional responses to this novel approach. A cohort of 28 ALS patients participated in the study, with a subset undergoing longitudinal follow-up assessments. Our results demonstrate strong agreement between human and robotic administrations of the ALSFRS-R, indicating the potential for AI-enabled robotics to accurately assess ALS functional status. Furthermore, the patients’ feedback underscores their acceptability of this technology as a supportive tool in healthcare settings. Our findings also highlight the potential benefits of employing robotic devices with algorithmic capabilities, such as the binary tree method, in hospitals. Moreover, such integration has the potential to alleviate operators’ workload. Importantly, this research contributes to the burgeoning field of AI-enabled healthcare operations, highlighting the promising role of robotic systems in enhancing functional assessment and management of ALS.