Does AI Coaching Prepare us for Workplace Negotiations?
Not on the map. Why?
Abstract (arXiv)
Workplace negotiations are undermined by psychological barriers, which can even derail well-prepared tactics. AI offers personalized and always -- available negotiation coaching, yet its effectiveness for negotiation preparedness remains unclear. We built Trucey, a prototype AI coach grounded in Brett's negotiation model. We conducted a between-subjects experiment (N=267), comparing Trucey, ChatGPT, and a traditional negotiation Handbook, followed by in-depth interviews (N=15). While Trucey showed the strongest reductions in fear relative to both comparison conditions, the Handbook outperformed both AIs in usability and psychological empowerment. Interviews revealed that the Handbook's comprehensive, reviewable content was crucial for participants' confidence and preparedness. In contrast, although participants valued AI's rehearsal capability, its guidance often felt verbose and fragmented -- delivered in bits and pieces that required additional effort -- leaving them uncertain or overwhelmed. These findings challenge assumptions of AI superiority and motivate hybrid designs that integrate structured, theory-driven content with targeted rehearsal, clear boundaries, and adaptive scaffolds to address psychological barriers and support negotiation preparedness.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 34 of its 152 references that are in the map. First posted on arXiv 26 Sep 2025.
Builds on
34 of 152 references.
References · 34
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
- 2019Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIcited by 1,552
- 2018Datasheets for Datasetscited by 1,386
- 2018Model Cards for Model Reportingcited by 1,080
- 2020Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditingcited by 384
- 2018Dear Sir or Madam, May I introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfercited by 211
- 2020A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Supportcited by 182
- 2016Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussionscited by 110
- 2019Human-Centered Tools for Coping with Imperfect Algorithms during Medical Decision-Makingcited by 109
- 2024Limitations of the LLM-as-a-Judge Approach for Evaluating LLM Outputs in Expert Knowledge Taskscited by 106
- 2019Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approachescited by 101
- 2023CoMPosT: Characterizing and Evaluating Caricature in LLM Simulationscited by 97
22 more
- 2023Cognitive Reframing of Negative Thoughts through Human-Language Model Interactioncited by 77
- 2023Rehearsal: Simulating Conflict to Teach Conflict Resolutioncited by 55
- 2018Modeling Empathy and Distress in Reaction to News Storiescited by 52
- 2023Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systemscited by 41
- 2022Advancing Human-AI Complementarity: The Impact of User Expertise and Algorithmic Tuning on Joint Decision Makingcited by 33
- 2022A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithmscited by 30
- 2023Understanding Frontline Workers' and Unhoused Individuals' Perspectives on AI Used in Homeless Servicescited by 29
- 2023Don't lose the message while paraphrasing: A study on content preserving style transfercited by 25
- 2020Overcoming Failures of Imagination in AI Infused System Development and Deploymentcited by 22
- 2022TyDiP: A Dataset for Politeness Classification in Nine Typologically Diverse Languagescited by 21
- 2024Can LLM "Self-report"?: Evaluating the Validity of Self-report Scales in Measuring Personality Design in LLM-based Chatbotscited by 20
- 2023`It is currently hodgepodge'': Examining AI/ML Practitioners' Challenges during Co-production of Responsible AI Valuescited by 18
- 2023Investigating Agency of LLMs in Human-AI Collaboration Taskscited by 15
- 2024ACE: A LLM-based Negotiation Coaching Systemcited by 13
- 2023Can Workers Meaningfully Consent to Workplace Wellbeing Technologies?cited by 6
- 2024"ChatGPT, Don't Tell Me What to Do": Designing AI for Context Analysis in Humanitarian Frontline Negotiationscited by 6
- 2025How Managers Perceive AI-Assisted Conversational Training for Workplace Communicationcited by 5
- 2022A Survey of Passive Sensing for Workplace Wellbeing and Productivitycited by 4
- 2024Supporting Co-Adaptive Machine Teaching through Human Concept Learning and Cognitive Theoriescited by 4
- 2025AI Trust Reshaping Administrative Burdens: Understanding Trust-Burden Dynamics in LLM-Assisted Benefits Systemscited by 4
- 2024Beyond Prompts: Learning from Human Communication for Enhanced AI Intent Alignmentcited by 3
- 2024DISCERN: Designing Decision Support Interfaces to Investigate the Complexities of Workplace Social Decision-Making With Line Managerscited by 2
Built on by
Citing papers per year: 2026: 2.
2 papers.
- 2026AI-Mediated Negotiation: Design Reflections and Lessons20 Jun 2026
- 2026Designing KRIYA: An AI Companion for Wellbeing Self-Reflection21 Jan 2026