AI in motion: a systematic review of artificial intelligence-driven virtual assistants for physical activity promotion and their comparison with traditional strategies

Physical inactivity remains a major public health concern globally, prompting the need for scalable, cost-effective interventions. Artificial Intelligence-driven Virtual Assistants (AIVAs) such as chatbots and virtual agents have emerged as novel methods to promote physical activity (PA), yet their effectiveness compared to traditional strategies remains unclear. This systematic review aimed at examining the characteristics, strategies, and effectiveness of AIVAs in promoting PA in adults and to compare them with traditional interventions. A systematic search of Scopus, Web of Science, PubMed, and Cochrane was conducted through May 2025. Eight interventional studies that employed AIVAs targeting PA were included. Risk of bias was assessed using ROBINS-I and RoB 2 tools. Intervention characteristics, outcomes, and behavioral strategies were extracted and synthesized. AIVAs were found to incorporate established behavior change techniques such as goal setting, feedback, and motivational support. Several studies demonstrated positive effects on PA metrics such as step counts and moderate to vigorous PA, though results were heterogeneous. Engagement and usability were generally high, particularly in interventions incorporating relational features. Compared to traditional interventions, AIVAs offered advantages in scalability and user autonomy but often lacked rigorous designs and long-term evaluation. AIVAs show promise as complementary tools for PA promotion, potentially overcoming scalability barriers associated with human-delivered programs. However, future research should prioritize methodologically robust designs, long-term assessments, and hybrid models that integrate both human and AI elements.