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The Feeling Economy: Managing in the Next Generation of Artificial Intelligence (AI)
Abstract
The capability of AI is currently expanding beyond mechanical and repetitive to analytical and thinking. A “Feeling Economy” is emerging, in which AI performs many of the analytical and thinking tasks, and human workers gravitate more toward interpersonal and empathetic tasks. Although these people-focused tasks have always been important to jobs, they are now becoming more important to an unprecedented degree. To manage more effectively in the Feeling Economy, managers must adapt the nature of jobs to compensate for the fact that many of the analytical and thinking tasks are increasingly being performed by AI, and, thus, human workers must place increased emphasis on the empathetic and emotional dimensions of their work.
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“Ordered by the difficulty with which AI can address them, there are mechanical, thinking, and feeling AI intelligences (Huang and Rust 2018; Huang et al. 2019).”
From A strategic framework for artificial intelligence in marketing (2021) · cites this paper as Huang et al. 2019
In the citing paper
“managers and management education underpreparing the next generation for feeling and emotional intelligence (Huang and Rust 2018; Huang et al. 2019)”
From A strategic framework for artificial intelligence in marketing (2021) · cites this paper as Huang et al. 2019
In the citing paper
“A consistent finding across domains was the necessity of a central entity to ensure transparency and alignment throughout the lifecycle of AI implementation39–41.”
From Advancing healthcare AI governance through a comprehensive maturity model based on systematic review (2026) · cites this paper as [39]
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Jain, R., Garg, N., & Khera, S. N. (2023) · Kybernetes · doi:10.1108/k-04-2022-0548 · Cited by 85
Fenwick, A., Molnár, G., & Frangos, P. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1272823 · Cited by 149
Gu, C., Zhang, Y., & Zeng, L. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03879-5 · Cited by 110
“Past research has veri fi ed differences in attitudes and behavioral choices toward AI systems between individuals characterized as “ technologists ” and “ conservatives, ” as well as the impact of factors such as individual time orientation (Huang et al. 2019).”
Telkamp, J. B., & Anderson, M. H. (2022) · Journal of Business Ethics · doi:10.1007/s10551-022-05057-6 · Cited by 89
“It is used to mimic or surpass human intelligence (Huang et al., 2019), 1 and several recent applications of AI have been revolutionary in their implications.”
BackgroundLu, Z., Min, Q., Jiang, L., & Chen, Q. (2024) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2024.102767 · Cited by 99
Gardezi, M., & Stock, R. (2021) · Journal of Rural Studies · doi:10.1016/j.jrurstud.2021.03.004 · Cited by 83
The impacts of artificial intelligence on managerial skills
Giraud, L., Zaher, A., Hernandez, S., & Akram, A. A. (2022) · Journal of Decision System · doi:10.1080/12460125.2022.2069537 · Cited by 116
“Because AI can handle simple and repetitive cognitive tasks (Decker et al., 2017), it may also take over most administrative (Kolbjørnsrud et al., 2016), analytical, and thinking skills (Huang et al., 2019).”
BackgroundResultInfluentialHow does service robot anthropomorphism affect human co-workers?
Tojib, D., Sujan, R., Ma, J., & Tsarenko, Y. (2023) · Journal of service management · doi:10.1108/josm-03-2022-0090 · Cited by 83
Working with AI: can stress bring happiness?
Loureiro, S. M. C., Bilro, R. G., & Neto, D. (2022) · Service Business · doi:10.1007/s11628-022-00514-8 · Cited by 97
“Mechanical AI is more indicated for standardization, while analytical, intuitive, and empathetic can be used for personalization and feeling AI (Huang et al. 2019).”
BackgroundMethodChhillar, D., & Aguilera, R. V. (2022) · Business & Society · doi:10.1177/00076503221080959 · Cited by 96
“Relatedly, Huang et al. (2019) foresee increasing importance of “feeling tasks” which they claim machines cannot perform better than humans, such as influencing, assisting, and caring for others and their emotions, or resolving interpersonal conflicts and building relationships.”
BackgroundFan, H., Han, B., & Wang, W. (2023) · Journal of Travel Research · doi:10.1177/00472875231201505 · Cited by 77
“With the emergence of a “feeling economy,” wherein AI can go beyond analytical and mechanical tasks and take over more empathetic and emotional dimensions of human work (Huang & Rust, 2018, 2021; Huang et al., 2019), more research on AI–human collaborative empathic response is needed.”
Metadata
- Authors
- Huang, M.-H., Rust, R., & Maksimovic, V.
- Affiliations
- National Taiwan University (TW)
- University of Maryland, College Park (US)
- Venue
- California Management Review
- Publisher
- SAGE Publications
- Published
- 2019-07-21
- Volume
- 61
- Issue
- 4
- Pages
- 43-65
- ISSN
- 0008-1256 (ISSN-L)
- 2162-8564
- OpenAlex
- W2964167195
- Cited by
- 591
- References
- 0
- Citations by year
- 2026: 90 · 2025: 131 · 2024: 116 · 2023: 86 · 2022: 73 · 2021: 59 · 2020: 32 · 2019: 4
- FWCI
- 58.87
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- California Management Review (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Corporate Management and Leadership
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Keywords
- artificial intelligence, human-AI collaboration, job design, emotional labor, empathy, interpersonal work, future of work
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