AI-Supported Companionship During Older Adults’ Physical Activity: A Comparative Experimental Study of Post-Exercise Perceived Exertion

Background/Objectives: Maintaining physical activity is important for functional independence in older adults. Perceived exertion may affect their exercise experience and participation. Social companionship may alleviate perceived exertion, and artificial intelligence (AI) offers a new form of companionship. This study aimed to compare human and AI companionship on post-exercise perceived exertion and examine the relationships among AI acceptance, social presence, and perceived exertion. Methods: Ninety-four older adults were randomly assigned to four conditions: no companionship, human companionship, low-interaction AI, or high-interaction AI. Participants completed 4 sets of 12 dumbbell curls using 2.5 kg dumbbells. Post-exercise perceived exertion was assessed using the Borg 6–20 scale. AI groups additionally completed AI acceptance and social presence measures. One-way ANOVA, Pearson correlations, and regression analyses were conducted. Results: Companionship condition significantly affected post-exercise rating of perceived exertion (RPE) (F (3, 90) = 11.407, p < 0.001, η2 = 0.275). RPE was significantly higher in the no-companionship group than in the human-companionship (p = 0.003), low-interaction AI-companionship (p < 0.001), and high-interaction AI-companionship (p < 0.001) groups. No significant differences were found among the three companionship groups. Within the AI-companionship groups, perceived usefulness (PU), sense of others’ presence (SOOP), emotional bonding (EB), and perceived interaction (PI) were negatively correlated with RPE. In multiple regression analysis, SOOP was the only significant negative predictor of RPE (β = −0.323, p < 0.05), while PU positively predicted SOOP (β = 0.326, p < 0.05). Conclusions: Human and AI companionship were associated with lower immediate post-exercise RPE than no companionship. However, high-interaction AI companionship was not shown to be superior to low-interaction AI or human companionship. The exploratory analyses suggest that SOOP and PU may be relevant to older adults’ exercise experiences. These findings support further investigation of AI exercise companions that integrate functional guidance with social interaction, though a larger sample size is needed to confirm the observed associations.