Abstract
The relationship between human and artificial intelligence has attracted debates and polarized views. A key area of this debate that received research attention is human and AI capability to augment each other to achieve better outcomes. While there is a growing research interest in the topic, research is currently dispersed and spread across the management disciplines making it hard for researchers to benefit from an accumulated knowledge in this domain. This study synthesises the literature and describes the current research findings in order to provide foundation for future research in this area. Based on a systematic review, we identify and discuss three emerging themes in the literature and highlight different possible challenges related to integrating AI in organisations. A future research agenda is also presented.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
McCarthy, J., et al.: Artificial Intelligence (AI) Coined at Dartmouth. Retrieved October, 1956 28 (2021)
McCarthy, J., et al.: A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence. wwwformal. p. 11 (1955). http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html
Allen, G.: Understanding AI technology. Joint Artificial Intelligence Center (JAIC) The Pentagon United States (2020)
Gkinko, L., Elbanna, A.: Hope, tolerance and empathy: employees’ emotions when using an AI-enabled chatbot in a digitalised workplace. Information Technology & People (2022) (ahead-of-print)
Dwivedi, Y.K., et al.: Artificial Intelligence (AI): multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int. J. Inf. Manage. 57, 101994 (2021)
Park, H., et al.: Human-AI interaction in human resource management: understanding why employees resist algorithmic evaluation at workplaces and how to mitigate burdens. In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (2021)
Haenlein, M., Kaplan, A.: A brief history of artificial intelligence: on the past, present, and future of artificial intelligence. Calif. Manage. Rev. 61(4), 5–14 (2019)
Wamba-Taguimdje, S.L., et al.: Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Bus. Process. Manag. J. 26(7), 1893–1924 (2020)
Basri, W.: Examining the impact of artificial intelligence (AI)-assisted social media marketing on the performance of small and medium enterprises: toward effective business management in the Saudi Arabian context. International Journal of Computational Intelligence Systems 13(1), 142 (2020)
Buntak, K., Kovačić, M., Mutavdžija, M.: Application of artificial intelligence in the business. International Journal for Quality Research 15(2), 403 (2021)
Needham, M.: Worldwide Spending on AI-Centric Systems Forecast to Reach $154 Billion in 2023, According to IDC (2023)
Schneider, J., et al.: Artificial intelligence governance for businesses. Inf. Syst. Manag. 40(3), 229–249 (2023)
Michael Chui, M.I., Roberts, R., Yee, L.: Technology Trends Outlook 2023. Digital McKinsey (2023)
Van Veldhoven, Z., Vanthienen, J.: Digital transformation as an interaction-driven perspective between business, society, and technology. Electron. Mark. 32(2), 629–644 (2022)
Brynjolfsson, E., McAfee, A.: The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. WW Norton & Company (2014)
Wilson, H.J., Daugherty, P.R.: Collaborative intelligence: humans and AI are joining forces. Harv. Bus. Rev. 96(4), 114–123 (2018)
Davenport, T.H., Kirby, J.: Only Humans Need Apply: Winners and Losers in the Age Of Smart Machines. Harper Business New York (2016)
Johnson, P.C., et al.: Digital innovation and the effects of artificial intelligence on firms’ research and development–Automation or augmentation, exploration or exploitation? Technol. Forecast. Soc. Chang. 179, 121636 (2022)
Xue, M., et al.: Is college education less necessary with AI? evidence from firm- level labor structure changes. J. Manag. Inf. Syst. 39(3), 865–905 (2022)
Enholm, I.M., et al.: Artificial intelligence and business value: a literature review. Inf. Syst. Front. 24(5), 1709–1734 (2022)
Raisch, S., Krakowski, S.: Artificial intelligence and management: the automation– augmentation paradox. Acad. Manag. Rev. 46(1), 192–210 (2021)
Amershi, S., et al.: Power to the people: the role of humans in interactive machine learning. AI Mag. 35(4), 105–120 (2014)
Rahwan, I., et al.: Machine behaviour. Nature 568(7753), 477–486 (2019)
Grewal, D., et al.: Frontline cyborgs at your service: how human enhancement technologies affect customer experiences in retail, sales, and service settings. J. Interact. Mark. 51, 9–25 (2020)
Metcalf, L., Askay, D.A., Rosenberg, L.B.: Keeping humans in the loop: pooling knowledge through artificial swarm intelligence to improve business decision making. Calif. Manage. Rev. 61(4), 84–109 (2019)
Gronsund, T., Aanestad, M.: Augmenting the algorithm: emerging human-in-the- loop work configurations. J. Strat. Inf. Syst. 29(2), 16 (2020)
Siemon, D.: Elaborating team roles for artificial intelligence-based teammates in human-AI collaboration. Group Decis. Negot. 31(5), 871–912 (2022)
Coombs, C., et al.: The strategic impacts of intelligent automation for knowledge and service work: an interdisciplinary review. J. Strat. Inf. Syst. 29(4), 30 (2020)
Cao, L.: AI in finance: challenges, techniques, and opportunities. ACM Computing Surveys (CSUR) 55(3), 1–38 (2022)
Chintalapati, S., Pandey, S.K.: Artificial intelligence in marketing: a systematic literature review. Int. J. Mark. Res. 64(1), 38–68 (2022)
Zhang, K., Aslan, A.B.: AI technologies for education: recent research & future directions. Computers and Education: Artificial Intelligence 2, 100025 (2021)
Budhwar, P., et al.: Artificial intelligence–challenges and opportunities for international HRM: a review and research agenda. The International Journal of Human Resource Management 33(6), 1065–1097 (2022)
Rajpurkar, P., et al.: AI in health and medicine. Nat. Med. 28(1), 31–38 (2022)
Fink, A.: Conducting Research Literature Reviews: From the Internet to Paper. Sage publications (2019)
Nilsson, N.J.: Problem-Solving Methods in Artificial Intelligence. McGraw-Hill (1971)
Stone, P., et al.: Artificial Intelligence and Life in 2030: The One Hundred Year Study On Artificial Intelligence. arXiv preprint arXiv:2211.06318 (2022)
Rai, A., Constantinides, P., Sarker, S.: Next generation digital platforms: toward human-ai hybrids. MIS Q. 43(1), iii–ix (2019)
Androutsopoulou, A., et al.: Transforming the communication between citizens and government through AI-guided chatbots. Gov. Inf. Q. 36(2), 358–367 (2019)
Newell, A., Simon, H.: The logic theory machine–a complex information processing system. IRE Transactions on Information Theory 2(3), 61–79 (1956)
Newell, A., Shaw, J.C., Simon, H.A.: Report on a General Problem Solving Program. in IFIP Congress. Pittsburgh, PA (1959)
Lindebaum, D., Vesa, M., Den Hond, F.: Insights from “the machine stops” to better understand rational assumptions in algorithmic decision making and its implications for organizations. Acad. Manag. Rev. 45(1), 247–263 (2020)
Amabile, T.: GUIDEPOST: Creativity. Artificial Intelligence, and a World of Surprises Guidepost Letter for Academy of Management Discoveries. Academy of Management Discoveries (2019)
Tegmark, M.: Life 3.0: Being Human in the Age of Artificial Intelligence. Vintage (2018)
Maragno, G., et al.: AI as an Organizational Agent to Nurture: Effectively Introducing Chatbots in Public Entities. Public Management Review, pp. 1–31 (2022)
Schanke, S., Burtch, G., Ray, G.: Estimating the impact of “humanizing” customer service chatbots. Inf. Syst. Res. 32(3), 736–751 (2021)
Huang, M.-H., Rust, R.T.: A framework for collaborative artificial intelligence in marketing. J. Retail. 98(2), 209–223 (2022)
Arslan, A., et al.: Artificial intelligence and human workers interaction at team level: a conceptual assessment of the challenges and potential HRM strategies. International Journal of Manpower (2021)
Loske, D., Klumpp, M.: Intelligent and efficient? An empirical analysis of human– AI collaboration for truck drivers in retail logistics. The International Journal of Logistics Management (2021)
Vassilakopoulou, P., et al.: Developing human/AI interactions for chat-based customer services: lessons learned from the Norwegian government. Eur. J. Inf. Syst. 32(1), 10–22 (2023)
Brachten, F., Kissmer, T., Stieglitz, S.: The acceptance of chatbots in an enterprise context–a survey study. Int. J. Inf. Manage. 60, 102375 (2021)
Marr, B.: The Amazing Ways how Unilever uses Artificial Intelligence to Recruit & Train thousands of Employees. Forbes (2018)
Fuegener, A., et al.: Cognitive challenges in human–artificial intelligence collaboration: investigating the path toward productive delegation. Inf. Syst. Res. 33(2), 678–696 (2022)
Makarius, E.E., et al.: Rising with the machines: a sociotechnical framework for bringing artificial intelligence into the organization. J. Bus. Res. 120, 262–273 (2020)
Vassilakopoulou, P., et al.: Developing human/AI interactions for chat-based customer services: lessons learned from the Norwegian government. European Journal of Information Systems, pp. 1–13 (2022)
Teodorescu, M.H., et al.: Failures of fairness in automation require a deeper understanding of human-ML augmentation. MIS Quarterly 45(3) (2021)
Barile, S., et al.: Empowering value co-creation in the digital age. Journal of Business & Industrial Marketing (2021)
Dellermann, D., et al.: Hybrid intelligence. Bus. Inf. Syst. Eng. 61(5), 637–643 (2019)
Larson, D.A.: Artificial intelligence: robots, avatars, and the demise of the human mediator. Ohio St. J. on Disp. Resol. 25, 105 (2010)
Webster, J., Watson, R.T.: Analyzing the past to prepare for the future: Writing a literature review. MIS quarterly, pp. 13-23 (2002)
Liñán, F., Fayolle, A.: A systematic literature review on entrepreneurial intentions: citation, thematic analyses, and research agenda. International Entrepreneurship and Management Journal 11(4), 907–933 (2015)
Guest, G., MacQueen, K.M., Namey, E.E.: Applied Thematic Analysis. sage publications (2011)
Braun, V., Clarke, V.: Using thematic analysis in psychology. Qual. Res. Psychol. 3(2), 77–101 (2006)
Benbya, H., Pachidi, S., Jarvenpaa, S.: Special issue editorial: artificial intelligence in organizations: implications for information systems research. J. Assoc. Inf. Syst. 22(2), 10 (2021)
Lebovitz, S., Lifshitz-Assaf, H., Levina, N.: To engage or not to engage with Al for critical judgments: how professionals deal with opacity when using AI for medical diagnosis. Organ. Sci. 33(1), 126–148 (2022)
Huang, M.H., Rust, R.T.: Artificial intelligence in service. J. Serv. Res. 21(2), 155–172 (2018)
Jarrahi, M.H.: Artificial intelligence and the future of work: human-AI symbiosis in organizational decision making. Bus. Horiz. 61(4), 577–586 (2018)
Cooper, A.F., Abrams, E.: Emergent Unfairness: Normative Assumptions and Contradictions in Algorithmic Fairness-Accuracy Trade-Off Research (2021)
Weber, M., et al.: Organizational capabilities for ai implementation—coping with inscrutability and data dependency in ai. Information Systems Frontiers, pp. 121 (2022)
Chowdhury, S., et al.: AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework. J. Bus. Res. 144, 31–49 (2022)
Chowdhury, S., et al.: Unlocking the value of artificial intelligence in human resource management through AI capability framework. Hum. Resour. Manag. Rev. 33(1), 100899 (2023)
Raftopoulos, M., Hamari, J.: Human-Ai Collaboration In Organisations: A Literature Review On Enabling Value Creation (2023)
Chatterjee, S., et al.: Assessing the implementation of AI integrated CRM system for B2C relationship management: Integrating contingency theory and dynamic capability view theory. Information systems frontiers pp. 1–19 (2022)
Vössing, M., et al.: Designing transparency for effective human-AI collaboration. Inf. Syst. Front. 24(3), 877–895 (2022)
Chuang, S.: Indispensable skills for human employees in the age of robots and AI. European Journal of Training and Development (2022) (ahead-of-print)
Russell Stuart, J., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice Hall (2009)
Di Vaio, A., Hassan, R., Alavoine, C.: Data intelligence and analytics: a bibliometric analysis of human–artificial intelligence in public sector decision-making effectiveness. Technol. Forecast. Soc. Chang. 174, 121201 (2022)
Puranam, P.: Human–AI collaborative decision-making as an organization design problem. J. Organization Design 10(2), 75-80 (2021)
Christensen, C.M.: The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Harvard Business Review Press (2013)
Bazerman, M.H., et al.: Book review: blind spots: why we fail to do what’s right and what to do about it. Public Integrity 14(4), 413–422 (2012)
Frank, D.-A., et al.: Human decision-making biases in the moral dilemmas of autonomous vehicles. Sci. Rep. 9(1), 1–19 (2019)
Faraj, S., Pachidi, S., Sayegh, K.: Working and organizing in the age of the learning algorithm. Inf. Organ. 28(1), 62–70 (2018)
Einola, K., Khoreva, V.: Best friend or broken tool? exploring the co-existence of humans and artificial intelligence in the workplace ecosystem. Hum. Resour. Manage. 62(1), 117–135 (2023)
Huang, M.-H., Rust, R., Maksimovic, V.: The feeling economy: managing in the next generation of artificial intelligence (AI). Calif. Manage. Rev. 61(4), 43–65 (2019)
Spring, M., Faulconbridge, J., Sarwar, A.: How information technology automates and augments processes: insights from artificial-Intelligence-based systems in professional service operations. J. Oper. Manag. 68(6–7), 592–618 (2022)
Jussupow, E., et al.: Augmenting medical diagnosis decisions? an investigation into physicians’ decision-making process with artificial intelligence. Inf. Syst. Res. 32(3), 713–735 (2021)
Huang, M.H., Rust, R.T.: Engaged to a robot? the role of AI in service. J. Serv. Res. 24(1), 30–41 (2021)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 IFIP International Federation for Information Processing
About this paper
Cite this paper
Trinh, N., Elbanna, A. (2024). AI and Human Relationship in the Workplace: A Literature Review and Future Research Agenda. In: Sharma, S.K., Dwivedi, Y.K., Metri, B., Lal, B., Elbanna, A. (eds) Transfer, Diffusion and Adoption of Next-Generation Digital Technologies. TDIT 2023. IFIP Advances in Information and Communication Technology, vol 698. Springer, Cham. https://doi.org/10.1007/978-3-031-50192-0_14
Download citation
DOI: https://doi.org/10.1007/978-3-031-50192-0_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-50191-3
Online ISBN: 978-3-031-50192-0
eBook Packages: Computer ScienceComputer Science (R0)