When Workout Buddies Are Virtual: AI Agents and Human Peers in a Longitudinal Physical Activity Study

2026-02-02

AI Summary

This study addresses the challenge of sustaining long-term physical activity adherence due to the lack of scalable and sustainable motivational strategies. Through a six-month randomized controlled trial, it compares exercising alone, with a human peer, or with a large language model–driven anthropomorphic virtual exercise partner (Simulated Exercising Peer, SEP). Findings indicate that human peers foster stronger motivation through authentic social interaction and accountability, whereas the AI-driven SEP offers more consistent, low-pressure support despite weaker social presence. The two approaches exhibit complementary motivational mechanisms, and their combined use significantly enhances long-term exercise adherence. The results suggest that in digital health interventions, AI should augment—rather than mimic—human authenticity, offering a novel paradigm for sustainable, scalable behavioral support in health promotion.

Technology Category

• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Intelligent Robots: Human-Robot Interaction

Application Category

• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation

Abstract

Physical inactivity remains a critical global health issue, yet scalable strategies for sustained motivation are scarce. Conversational agents designed as simulated exercising peers (SEPs) represent a promising alternative, but their long-term impact is unclear. We report a six-month randomized controlled trial (N=280) comparing individuals exercising alone, with a human peer, or with a large language model-driven SEP. Results revealed a partnership paradox: human peers evoked stronger social presence, while AI peers provided steadier encouragement and more reliable working alliances. Humans motivated through authentic comparison and accountability, whereas AI peers fostered consistent, low-stakes support. These complementary strengths suggest that AI agents should not mimic human authenticity but augment it with reliability. Our findings advance human-agent interaction research and point to hybrid designs where human presence and AI consistency jointly sustain physical activity.

Problem

• physical inactivity
• sustained motivation
• conversational agents
• human-agent interaction
• long-term engagement

Innovation

• conversational agents
• simulated exercising peers
• human-agent interaction
• long-term motivation
• hybrid design