AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework
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Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023) · Human Resource Management Review · doi:10.1016/j.hrmr.2022.100899 · Cited by 927 · see citing works
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Artificial intelligence in logistics and supply chain management: A primer and roadmap for research
Richey, R. G., Chowdhury, S., Davis‐Sramek, B., Giannakis, M., & Dwivedi, Y. K. (2023) · Journal of Business Logistics · doi:10.1111/jbl.12364 · Cited by 471 · see citing works
“Organizations might increasingly lean towards a workforce that can collaborate seamlessly with AI systems, fostering a symbiotic relationship that leverages the strengths of both humans and machines, i.e., collaborative intelligence (Chowdhury et al., 2022; Peng et al., 2022).”
Self-citationDey, P. K., Chowdhury, S., Abadie, A., Vann Yaroson, E., & Sarkar, S. (2024) · International Journal of Production Research · doi:10.1080/00207543.2023.2179859 · Cited by 330 · see citing works
“…workforce needs, government policies and regulations, external turbulent and dynamic business environment, consumer needs and evolving preferences, SC partners’ requirements, organisations’ corporate social responsibility and ethos and sustain unprecedented disruptions ( Chowdhury et al. 2022b).”
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A study of Artificial Intelligence impacts on Human Resource Digitalization in Industry 4.0
Murugesan, U., Subramanian, P., Srivastava, S., & Dwivedi, A. (2023) · Decision Analytics Journal · doi:10.1016/j.dajour.2023.100249 · Cited by 217 · see citing works
Khan, A., Mehmood, K., & Kwan, H. K. (2023) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2023.100455 · Cited by 210 · see citing works
“Although no other study has tested the moderating impacts of AI in these relationships, we postulate that AI ’ s signi fi - cant moderating effect on GHC is due to employees ’ use of technical resources to improve their knowledge (Chowdhury et al., 2022).”
InfluentialChowdhury, S., Budhwar, P., & Wood, G. (2024) · British Journal of Management · doi:10.1111/1467-8551.12824 · Cited by 221 · see citing works
“Central to this transformation is the emphasis on fostering AI–employee collaboration (Chowdhury et al. , 2022) and promoting hybrid problem-solving approaches (Raisch and Fomina, 2023) by creating environments where GAI tools and human expertise can co-exist to work as a team.”
BackgroundSelf-citationKong, H., Yin, Z., Chon, K., Yuan, Y., & Yu, J. (2023) · Journal of Hospitality Marketing & Management · doi:10.1080/19368623.2023.2258116 · Cited by 194 · see citing works
“AI trust represents employees’ positive attitudes toward AI and its potential impacts on employees in work domains (Chowdhury et al., 2022).”
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Vărzaru, A. A., & Bocean, C. G. (2024) · Systems · doi:10.3390/systems12090359 · Cited by 265 · see citing works
Explainable artificial intelligence and agile decision-making in supply chain cyber resilience
Kiarash Sadeghi, R., Ojha, D., Kaur, P., Mahto, R. V., & Dhir, A. (2024) · Decision Support Systems · doi:10.1016/j.dss.2024.114194 · Cited by 169 · see citing works
Implementing and scaling artificial intelligence: A review, framework, and research agenda
Haefner, N., Parida, V., Gassmann, O., & Wincent, J. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122878 · Cited by 179 · see citing works
Managing with Artificial Intelligence: An Integrative Framework
Hillebrand, L., Raisch, S., & Schad, J. (2025) · Academy of Management Annals · doi:10.5465/annals.2022.0072 · Cited by 193 · see citing works
Fenwick, A., Molnár, G., & Frangos, P. (2024) · Discover Artificial Intelligence · doi:10.1007/s44163-024-00125-4 · Cited by 199 · see citing works
“As firms increasingly implement advanced digital AI tools, human resource management (HRM) becomes more complex [5, 6].”
Laupichler, M. C., Aster, A., & Raupach, T. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100126 · Cited by 149 · see citing works
“On the other hand, AI applications are also increasingly finding their way into the workplace, and employees have to learn how to deal with these novel systems (Chowdhury et al., 2022) to ensure they can continue to work in decent work environments.”
BackgroundArtificial intelligence in interactive marketing: a conceptual framework and research agenda
Peltier, J. W., Dahl, A. J., & Schibrowsky, J. A. (2023) · Journal of Research in Interactive Marketing · doi:10.1108/jrim-01-2023-0030 · Cited by 163 · see citing works
The Road to corporate sustainability: The importance of artificial intelligence
Chen, P., Chu, Z., & Zhao, M. (2023) · Technology in Society · doi:10.1016/j.techsoc.2023.102440 · Cited by 158 · see citing works
Artificial Intelligence and Knowledge Management: Impacts, Benefits, and Implementation
Taherdoost, H., & Madanchian, M. (2023) · De Computis · doi:10.3390/computers12040072 · Cited by 124 · see citing works
Chowdhury, S., Joel-Edgar, S., Dey, P. K., Bhattacharya, S., & Kharlamov, A. (2023) · The International Journal of Human Resource Management · doi:10.1080/09585192.2022.2066981 · Cited by 140 · see citing works
“The primary goal of embedding transparency within AI-based ML models is to help the decision-making authorities understand what the AI system is doing, how it is generating the output responses and why a particular response is generated (Choudhury et al., 2020).”
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Yaroson, E. V., Chowdhury, S., Mangla, S. K., Dey, P. K., Chan, F. T. S., & Roux, M. (2023) · International Journal of Production Research · doi:10.1080/00207543.2023.2270586 · Cited by 122 · see citing works
“Such an undertaking necessitates the development of a comprehensive knowledge management strategy, taking into account the investment in technical resources like information systems and platforms that facilitate efficient information storage and dissemination (Chowdhury et al. 2022b).”
BackgroundSelf-citationJain, R. M., Garg, N., & Khera, S. N. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.893691 · Cited by 155 · see citing works
“The potential benefits of human-AI collaboration can only be realized when employees in the organization trust, accept, and use technology for work processes (Caputo et al., 2019; Wamba-Taguimdje et al., 2020; Chowdhury et al., 2022).”
BackgroundInfluentialBlockchain technology and supply chain performance: The role of trust and relational capabilities
Pattanayak, S., Ramkumar, M., Goswami, M., & Rana, N. P. (2024) · International Journal of Production Economics · doi:10.1016/j.ijpe.2024.109198 · Cited by 103 · see citing works
Yin, Z., Kong, H., Baruch, Y., Decosta, P. L., & Yuan, Y. (2024) · Tourism Management · doi:10.1016/j.tourman.2024.104966 · Cited by 120 · see citing works
AI and employee wellbeing in the workplace: An empirical study
Valtonen, A., Saunila, M., Ukko, J., Treves, L., & Ritala, P. (2025) · Journal of business research · doi:10.1016/j.jbusres.2025.115584 · Cited by 120 · see citing works
Adoption of artificial intelligence: a TOP framework-based checklist for digital leaders
Tursunbayeva, A., & Chalutz-Ben Gal, H. (2024) · Business Horizons · doi:10.1016/j.bushor.2024.04.006 · Cited by 102 · see citing works
Unveiling trust in AI: the interplay of antecedents, consequences, and cultural dynamics
Dang, Q., & Li, G. (2025) · AI & Society · doi:10.1007/s00146-025-02477-6 · Cited by 111 · see citing works
“…power (Agnihotri and Bhattacharya 2024; Gillath et al. 2021; Li and Bitterly 2024), competence-related variables such as personal AI familiarity, technical self-efficacy, and perceived mastery demonstrate robust positive effects (Chowdhury et al. 2022; Gillath et al. 2021; Montag et al. 2023).”
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Effective human–AI work design for collaborative decision-making
Jain, R., Garg, N., & Khera, S. N. (2023) · Kybernetes · doi:10.1108/k-04-2022-0548 · Cited by 85 · see citing works
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Shao, Y., Huang, C., Song, Y., Wang, M., Song, Y. H., & Shao, R. (2024) · Journal of Management · doi:10.1177/01492063241266503 · Cited by 96 · see citing works
“However, it does not speak to how AI augments human intellect and talent beyond simply replacing human labor at work, which lies at the core of AI augmentation (Chowdhury et al., 2022; Daugherty & Wilson, 2018; Jarrahi, 2018).”
InfluentialChakraborty, D., Polisetty, A., Sowmya, G., Rana, N. P., & Khorana, S. (2024) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2024.103842 · Cited by 84 · see citing works
Abadie, A., Roux, M., Chowdhury, S., & Dey, P. K. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2023.113866 · Cited by 73 · see citing works
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“Thus, through the efficient and flexible performance of problem-solving tasks, ambidexterity can effectively reduce the level of uncertainty regarding chatbots (Chowdhury et al., 2022).”
AI Adoption and Educational Sustainability in Higher Education in the UAE
Shwedeh, F., Salloum, S. A., Aburayya, A., Fatin, B., Elbadawi, M. A., Ghurabli, Z. A., & Aldabbagh, T. (2024) · Studies in big data · doi:10.1007/978-3-031-52280-2_14 · Cited by 83 · see citing works
Understanding Human-AI Augmentation in the Workplace: A Review and a Future Research Agenda
Trinh, N. T. T., & Elbanna, A. R. (2025) · Information Systems Frontiers · doi:10.1007/s10796-025-10591-5 · Cited by 89 · see citing works
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“…and psychological perspectives in organizational research, suggesting that the value of AI extends beyond operational efficiency to include sig - nificant enhancements in human cognitive capabilities and creative performance (Huang & Rust, 2018; Chowdhury et al., 2022; Li et al., 2024).”
Roux, M., Chowdhury, S., Dey, P. K., Yaroson, E. V., Pereira, V. E., & Abadie, A. (2023) · Annals of Operations Research · doi:10.1007/s10479-023-05760-1 · Cited by 69 · see citing works
“…adoption on business productivity and firm performance, and factors impacting the adoption of these technologies from the managers’ and employees’ perspectives in business organisations (2021b; Chowdhury et al., 2022a; Lindell, et al., 2020; Queiroz et al., 2021a; Rodríguez-Espíndola et al., 2022).”
InfluentialSelf-citationAI based suitability measurement and prediction between job description and job seeker profiles
Sridevi, G. M., & Suganthi, S. K. (2022) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2022.100109 · Cited by 60 · see citing works
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“While AI holds promise in solving some of humanity’s most persistent problems (Chowdhury et al., 2022; Tomasˇev et al., 2020), concerns such as job security, AI surveillance, and abuse of personal data have emerged.”
Halbusi, H. A., Popa, S., Soto‐Acosta, P., & Alshallaqi, M. (2025) · Technology in Society · doi:10.1016/j.techsoc.2025.102937 · Cited by 60 · see citing works
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Business Model Innovation through AI Adaptation: The Role of Strategic Human Resources Management
Roy, S. K., Dey, B. L., Brown, D. M., Abid, A., Apostolidis, C., Christofi, M., & Tarba, S. Y. (2025) · British Journal of Management · doi:10.1111/1467-8551.12894 · Cited by 60 · see citing works
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Yaroson, E. V., Abadie, A., & Roux, M. (2025) · Annals of Operations Research · doi:10.1007/s10479-025-06534-7 · Cited by 74 · see citing works
“This study examined the contribution of CAIT in enhancing SCWB and SBP mediated by the holistic dimensions of RAI (fairness, accountability, and sustainability) using the RBV and STS theories.”
InfluentialSelf-citationWang, Q., Qi, Y., & Li, R. (2026) · Sustainable Development · doi:10.1002/sd.70200 · Cited by 55 · see citing works
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AI ethics in action: a circular model for transparency, accountability and inclusivity
Tabaghdehi, S. A. H., & Arda, Ö. A. (2025) · Journal of Managerial Psychology · doi:10.1108/jmp-03-2024-0177 · Cited by 54 · see citing works
Artificial intelligence, workers, and future of work skills
Bankins, S., Hu, X., & Yuan, Y. E. (2024) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2024.101828 · Cited by 80 · see citing works
“In terms of upsides, workers will generally have better experiences of using AI when they trust it [31], when they perceive good system quality [32], and when they are skilled to use it effectively [33].”
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Rialti, R., & Filieri, R. (2024) · Business Horizons · doi:10.1016/j.bushor.2024.04.003 · Cited by 51 · see citing works
Abadie, A., Chowdhury, S., & Mangla, S. K. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.123202 · Cited by 51 · see citing works
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“Effective policies and systems clearly express acceptable and unacceptable employee behavior [50].”
BackgroundTrust in AI and Top Management Support in Generative-AI Adoption
Korzyński, P., Silva, S. C. L. D. C. E., Górska, A. M., & Mazurek, G. (2024) · Journal of Computer Information Systems · doi:10.1080/08874417.2024.2401986 · Cited by 61 · see citing works
“The potential advantages of human-AI collaboration materialize when employees within an organization adopt, trust, and utilize technology within their workflows 39,40 and increase job satisfaction.”
Qi, M., Wu, T., Duan, W., & Li, S. (2025) · Behavioral Sciences · doi:10.3390/bs15050696 · Cited by 62 · see citing works
“In the context of employee–AI collaboration, AI serves as an effective means to enhance employee productivity and work efficiency, thereby providing a competitive advantage for organizations (Chowdhury et al., 2022).”
Yang, F., Luo, C., & Pan, L. (2023) · Resources Policy · doi:10.1016/j.resourpol.2023.104345 · Cited by 47 · see citing works
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Tandon, A., Dhir, A., Malik, A., Budhwar, P. S., & Kaur, P. (2024) · Human Resource Management · doi:10.1002/hrm.22263 · Cited by 47 · see citing works
Self-citationDoes Artificial Intelligence Promote or Inhibit On-the-Job Learning? Human Reactions to AI at Work
Li, C., Zhang, Y., Niu, X., Chen, F., & Zhou, H. (2023) · Systems · doi:10.3390/systems11030114 · Cited by 52 · see citing works
Li, B., Liu, L., Mao, W., Qu, Y., & Chen, Y. (2023) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2023.101261 · Cited by 45 · see citing works
Al-Balushi, H. A. A., Singh, H., & Saleem, I. (2025) · Society and Business Review · doi:10.1108/sbr-07-2024-0249 · Cited by 50 · see citing works
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Robertson, J., Botha, E., Oosthuizen, K., & Montecchi, M. (2025) · Journal of Business Research · doi:10.1016/j.jbusres.2025.115198 · Cited by 57 · see citing works
Zheng, J., Zhang, Z., Kamal, M. M., Liang, X., & Alzeiby, E. A. (2025) · Journal of Business Research · doi:10.1016/j.jbusres.2025.115406 · Cited by 62 · see citing works
Fan, J., Zhang, L., Li, N., & Man, S. (2025) · BMC Nursing · doi:10.1186/s12912-025-03265-9 · Cited by 45 · see citing works
“Advanced search technologies such as natural language processing and semantic understanding filter relevant content, ensuring accuracy and real-time updates [85].”
Deng, N., Gong, Y., & Wang, J. (2024) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2024.141686 · Cited by 40 · see citing works
Ji, M., Chen, X. S., & Wei, S. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2355399 · Cited by 43 · see citing works
“The theory of socio-technical systems can help address both the technical features and customers’ perceptions during the interaction with these features (Chowdhury et al., 2022; Li et al., 2021).”
AI in Context: Harnessing Domain Knowledge for Smarter Machine Learning
Miller, T. I., Durlik, I., Łobodzińska, A., Dorobczyński, L., & Jasionowski, R. (2024) · Applied Sciences · doi:10.3390/app142411612 · Cited by 40 · see citing works
Impact of AI applications on corporate green innovation
Xi, K., & Shao, X. (2025) · International Review of Economics & Finance · doi:10.1016/j.iref.2025.104007 · Cited by 38 · see citing works
Bringing employee learning to AI stress research: A moderated mediation model
Zhou, Q., Chen, K., & Shuang, C. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2024.123773 · Cited by 43 · see citing works
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ChatGPT and Beyond: Exploring the Responsible Use of Generative AI in the Workplace
Söllner, M., Arnold, T., Benlian, A., Bretschneider, U., Knight, C., Ohly, S., Rudkowski, L., Schreiber, G., & Wendt, D. H. (2025) · Business & Information Systems Engineering · doi:10.1007/s12599-025-00932-8 · Cited by 43 · see citing works
“…workers need to trust the AI, perceive it to be helpful and appropriate, and learn how to interact with it effectively to generate useful outputs (Chowdhury et al. 2022), which might explain why individuals do not see the benefits when having limited experience and no feedback (Noy and Zhang…”
Hwang, B., Jitanugoon, S., & Puntha, P. (2025) · Journal of Services Marketing · doi:10.1108/jsm-10-2024-0511 · Cited by 31 · see citing works
Science and Technology Financial Policies and Enterprise Digital Technology Innovation
Shao, X., Xi, K., & Chen, Z. (2025) · Finance research letters · doi:10.1016/j.frl.2025.107646 · Cited by 40 · see citing works
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Intelligent Productivity Transformation
Liu, B., Li, M., Ji, Z., Li, H., & Luo, J. R. (2024) · Journal of Organizational and End User Computing · doi:10.4018/joeuc.336284 · Cited by 36 · see citing works
“In this research field, the development of virtual assistants has penetrated into many aspects such as customer service, personal life management, and even enterprise automated decision-making (Chowdhury et al., 2022).”
BackgroundExtending application of explainable artificial intelligence for managers in financial organizations
Sabharwal, R., Miah, S. J., Wamba, S. F., & Cook, P. G. (2024) · Annals of Operations Research · doi:10.1007/s10479-024-05825-9 · Cited by 41 · see citing works
“Further, Chowdhury et al. (2022c) have explained the value of AI transparency in identifying and resolving flaws in ML models, thereby enhancing their utility for business organizations.”
InfluentialKhandelwal, K., Upadhyay, A. K., & Rukadikar, A. (2024) · Human Resource Development International · doi:10.1080/13678868.2024.2375935 · Cited by 35 · see citing works
“Businesses gain from enhanced efficiency and personalisation resulting from the adoption of AI (Chowdhury et al., 2022).”
Ma, K., Zhang, Y., & Hui, B.-H. (2024) · Behavioral Sciences · doi:10.3390/bs14121223 · Cited by 35 · see citing works
“AI trust: The 11 item scale developed by Chowdhury et al. was used to measure AI trust [41].”
Liu, D., Wang, H., & Zhu, Y. (2025) · Journal of Business Research · doi:10.1016/j.jbusres.2025.115598 · Cited by 35 · see citing works
Liu, Q., Tian, Q., Li, X., & Tan, H. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1690238 · Cited by 43 · see citing works
Cui, W., Liu, M. J., & Yuan, R. (2025) · Journal of Advertising Research · doi:10.1080/00218499.2024.2445362 · Cited by 43 · see citing works
AI literacy and trust: A multi-method study of Human-GAI team collaboration
Pan, Z., Moore, O. A., Papadimitriou, A., & Zhu, J. (2025) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2025.100162 · Cited by 42 · see citing works
Chen, L., Li, S., & She, Z. (2025) · International Review of Economics & Finance · doi:10.1016/j.iref.2025.104490 · Cited by 33 · see citing works
Shan, B., Liu, K., Lu, X., & Liu, X. (2025) · Journal of Knowledge Management · doi:10.1108/jkm-04-2025-0588 · Cited by 33 · see citing works
Creative abilities and digital competencies to transitioning to Business 4.0
Sergi, B. S., Ključnikov, A., Popkova, E. G., Bogoviz, A. V., & Lobova, S. V. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.08.026 · Cited by 32 · see citing works
Yaroson, E. V., Chowdhury, S., Mangla, S. K., & Dey, P. K. (2024) · Annals of Operations Research · doi:10.1007/s10479-024-05845-5 · Cited by 35 · see citing works
Self-citationEmployees’ foe or friend: artificial intelligence and employee outcomes
Tahir, M. A., Da, G., Javed, M., Akhtar, M. W., & Wang, X. (2024) · Service Industries Journal · doi:10.1080/02642069.2024.2375746 · Cited by 31 · see citing works
“Previous studies have demonstrated that various aspects of AI knowledge can lead to positive attitudes toward technology among individuals and can facilitate positive job-related outcomes for employees (Chowdhury, Budhwar, et al., 2022; Cicerone et al., 2023; He et al., 2023).”
Chew, Y.-C., & Zainal, S. R. M. (2024) · SAGE Open · doi:10.1177/21582440241261851 · Cited by 30 · see citing works
“…and a substantial number of the articles propagate collaboration intelligence as cooperation between humans and artificial intelligence (Abraham et al., 2020; Chowdhury et al., 2022; M. H. Huang & Rust, 2022; Lin & Mattila, 2021; Paschen et al., 2020; Wilson & Daugherty, 2018; Zhong et al., 2015).”
Savolainen, I., Ylinen, L., Grönroos, R., & Oksanen, A. (2025) · Digital Business · doi:10.1016/j.digbus.2025.100162 · Cited by 41 · see citing works
- Authors
- Chowdhury, S., Budhwar, P., Dey, P. K., Joel-Edgar, S., & Abadie, A.
- Affiliations
- TBS Education (FR)
- Aston University (GB)
- Northeastern University London (GB)
- Corresponding author
- Chowdhury, Soumyadeb
- Venue
- Journal of Business Research
- Publisher
- Elsevier BV
- Published
- 2022-05
- Volume
- 144
- Pages
- 31-49
- ISSN
- 0148-2963 (ISSN-L)
- OpenAlex
- W4210465889
- Cited by
- 531
- References
- 128
- Citations by year
- 2026: 195 · 2025: 177 · 2024: 88 · 2023: 55 · 2022: 16
- FWCI
- 79.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Business Research (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Sociology and Political Science › Information Systems Theories and Implementation
- Social Sciences › Communication › Knowledge Management and Sharing
- Keywords
- human-AI collaboration, collaborative intelligence, firm performance, knowledge sharing, AI competencies, trust, role clarity, knowledge-based view, socio-technical systems, organizational socialization, creative industries
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