The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Artificial Intelligence Coaches for Sales Agents: Caveats and Solutions
Abstract
Firms are exploiting artificial intelligence (AI) coaches to provide training to sales agents and improve their job skills. The authors present several caveats associated with such practices based on a series of randomized field experiments. Experiment 1 shows that the incremental benefit of the AI coach over human managers is heterogeneous across agents in an inverted-U shape: whereas middle-ranked agents improve their performance by the largest amount, both bottom- and top-ranked agents show limited incremental gains. This pattern is driven by a learning-based mechanism in which bottom-ranked agents encounter the most severe information overload problem with the AI versus human coach, while top-ranked agents hold the strongest aversion to the AI relative to a human coach. To alleviate the challenge faced by bottom-ranked agents, Experiment 2 redesigns the AI coach by restricting the training feedback level and shows a significant improvement in agent performance. Experiment 3 reveals that the AI–human coach assemblage outperforms either the AI or human coach alone. This assemblage can harness the hard data skills of the AI coach and soft interpersonal skills of human managers, solving both problems faced by bottom- and top-ranked agents. These findings offer novel insights into AI coaches for researchers and managers alike.
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Citations
Cites
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BackgroundMethodInfluential
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Tong, S., Jia, N., Luo, X., & Fang, Z. (2021) · Strategic Management Journal · doi:10.1002/smj.3322 · Cited by 531
Self-citationHui, X., Reshef, O., & Zhou, L. (2024) · Organization Science · doi:10.1287/orsc.2023.18441 · Cited by 200
Algorithmic Management: Bright and Dark Sides, Practical Implications, and Research Opportunities
Benlian, A., Wiener, M., Cram, W. A., Krasnova, H., Maedche, A., Möhlmann, M., Recker, J., & Remus, U. (2022) · Business & Information Systems Engineering · doi:10.1007/s12599-022-00764-w · Cited by 180
AI Companions Reduce Loneliness
De Freitas, J., Oğuz-Uğuralp, Z., Uğuralp, A. K., & Puntoni, S. (2026) · Journal of Consumer Research · doi:10.1093/jcr/ucaf040 · Cited by 165
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AI Companions Reduce Loneliness
De Freitas, J., Uğuralp, A. K., Uğuralp, Z., & Puntoni, S. (2024) · doi:10.2139/ssrn.4893097 · Cited by 80
Towards relatable explainable AI with the perceptual process
Zhang, W., & Lim, B. Y. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501826 · Cited by 67
A multi-stakeholder ethical framework for AI-augmented HRM
Prikshat, V., Patel, P., Varma, A., & Ishizaka, A. (2022) · International Journal of Manpower · doi:10.1108/ijm-03-2021-0118 · Cited by 57
Li, Y., Gan, Z., & Zheng, B. (2025) · Information Systems Frontiers · doi:10.1007/s10796-023-10438-x · Cited by 47
Seeing the Bigger Picture? Ramping up Production with the Use of Augmented Reality
Wuttke, D., Upadhyay, A., Siemsen, E., & Wuttke-Linnemann, A. (2022) · Manufacturing & Service Operations Management · doi:10.1287/msom.2021.1070 · Cited by 36
Hautamäki, P., & Heikinheimo, M. (2025) · Journal of Business Research · doi:10.1016/j.jbusres.2025.115396 · Cited by 31
Transitioning to artificial intelligence-based key account management: A critical assessment
Prior, D. D., & Marcos-Cuevas, J. (2025) · Industrial Marketing Management · doi:10.1016/j.indmarman.2025.02.009 · Cited by 18
AI Companions Reduce Loneliness
De Freitas, J., Uguralp, A. K., Uguralp, Z. O., & Stefano, P. (2024) · arXiv · doi:10.48550/arxiv.2407.19096 · Cited by 12
GenAI-Infused Service Delivery: Micro-Level Augmentation Patterns at the Service Frontline
Reinhard, P., Li, M. M., Peters, C., Janson, A., & Leimeister, J. M. (2026) · Journal of Service Research · doi:10.1177/10946705251414283 · Cited by 6
Metadata
- Authors
- Luo, X., Qin, M. S., Fang, Z., & Qu, Z.
- Venue
- Journal of Marketing
- Publisher
- SAGE Publications
- Published
- 2020-10-14
- Volume
- 85
- Issue
- 2
- Pages
- 14-32
- ISSN
- 0022-2429 (ISSN-L)
- 1547-7185
- OpenAlex
- W3092728304
- Cited by
- 328
- References
- 13
- FWCI
- 25.19
- Type
- journal article
- Language
- en
- Open access
- closed
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