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

arXiv: https://arxiv.org/abs/2602.01918 · HTML: https://mlsanity.com/paper/2602.01918/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use.
- Builds on 9 of its 88 references that are in the map.
- First posted on arXiv 2 Feb 2026.

## Placed in

- LLM agents and tool use / [General LLM agent frameworks and benchmarks](https://mlsanity.com/agents/general-llm-agent-frameworks-and-benchmarks/)

## Builds on (most cited first, 9 of 9)

- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Towards Understanding Sycophancy in Language Models](https://mlsanity.com/paper/2310.13548/) (2023)
- [How should my chatbot interact? A survey on human-chatbot interaction design](https://mlsanity.com/paper/1904.02743/) (2019)
- [Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistant](https://mlsanity.com/paper/2502.01390/) (2025)
- [GPTCoach: Towards LLM-Based Physical Activity Coaching](https://mlsanity.com/paper/2405.06061/) (2024)
- [AI Companions Reduce Loneliness](https://mlsanity.com/paper/2407.19096/) (2024)
- [RiskRAG: A Data-Driven Solution for Improved AI Model Risk Reporting](https://mlsanity.com/paper/2504.08952/) (2025)
- [Exercise with Social Robots: Companion or Coach?](https://mlsanity.com/paper/2103.12940/) (2021)
- [When motivation can be more than a message: designing agents to boost physical activity](https://mlsanity.com/paper/2508.12388/) (2025)

## Abstract (arXiv)

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.