# Coaching Copilot: Blended Form of an LLM-Powered Chatbot and a Human Coach to Effectively Support Self-Reflection for Leadership Growth

arXiv: https://arxiv.org/abs/2405.15250 · HTML: https://mlsanity.com/paper/2405.15250/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 73 references that are in the map.
- First posted on arXiv 24 May 2024.

## Builds on (most cited first, 3 of 3)

- [Large Language Models are Zero-Shot Reasoners](https://mlsanity.com/paper/2205.11916/) (2022)
- [REsCUE: A framework for REal-time feedback on behavioral CUEs using multimodal anomaly detection](https://mlsanity.com/paper/1903.11485/) (2019)
- [Supporting Experts with a Multimodal Machine-Learning-Based Tool for Human Behavior Analysis of Conversational Videos](https://mlsanity.com/paper/2402.11145/) (2024)

## Built on by (most cited first, 7 of 7)

- [How Managers Perceive AI-Assisted Conversational Training for Workplace Communication](https://mlsanity.com/paper/2505.14452/) (2025)
- [Large Language Model Agents for Improving Engagement with Behavior Change Interventions: Application to Digital Mindfulness](https://mlsanity.com/paper/2407.13067/) (2024)
- [Reflective Verbal Reward Design for Pluralistic Alignment](https://mlsanity.com/paper/2506.17834/) (2025)
- [From Answer Givers to Design Mentors: Guiding LLMs with the Cognitive Apprenticeship Model](https://mlsanity.com/paper/2601.19053/) (2026)
- [Reflecti-Mate: A Conversational Agent for Adaptive Decision-Making Support Through System 1 and System 2 Thinking](https://mlsanity.com/paper/2605.22509/) (2026)
- [AI-Facilitated Episodic Future Thinking For Adults with Obesity](https://mlsanity.com/paper/2503.16484/) (2025)
- [Words to Describe What I'm Feeling: Exploring the Potential of AI Agents for High Subjectivity Decisions in Advance Care Planning](https://mlsanity.com/paper/2512.11276/) (2025)

## Abstract (arXiv)

Chatbots' role in fostering self-reflection is now widely recognized, especially in inducing users' behavior change. While the benefits of 24/7 availability, scalability, and consistent responses have been demonstrated in contexts such as healthcare and tutoring to help one form a new habit, their utilization in coaching necessitating deeper introspective dialogue to induce leadership growth remains unexplored. This paper explores the potential of such a chatbot powered by recent Large Language Models (LLMs) in collaboration with professional coaches in the field of executive coaching. Through a design workshop with them and two weeks of user study involving ten coach-client pairs, we explored the feasibility and nuances of integrating chatbots to complement human coaches. Our findings highlight the benefits of chatbots' ubiquity and reasoning capabilities enabled by LLMs while identifying their limitations and design necessities for effective collaboration between human coaches and chatbots. By doing so, this work contributes to the foundation for augmenting one's self-reflective process with prevalent conversational agents through the human-in-the-loop approach.