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In the hearts and minds of employees: A model of pre-adoptive appraisal toward artificial intelligence in organizations

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  • Chiu, Yi-Te
  • Zhu, Yu-Qian
  • Corbett, Jacqueline

Abstract

Organizations face increasing pressure to implement artificial intelligence (AI) within a variety of business processes and functions. Many perceived benefits surround AI, but a considerable amount of trepidation also exists because of the potential of AI to replace human employees and dehumanize work. Questions regarding the future of work in the age of AI are particularly salient in pre-adoption organizations, before employees have the opportunity to gain direct experience with AI. To cope with this potentially stressful situation, employees engage in cognitive appraisal processes based on their own knowledge and personal use of AI. These pre-adoptive appraisals of AI influence both affective and cognitive attitudes, which in turn trigger behavioral responses that influence an organization’s ability to leverage AI successfully. Our survey of 363 Taiwanese employees shows that perceptions of AI’s operational and cognitive capabilities are positively related to affective and cognitive attitudes toward AI, while concerns regarding AI have a negative relationship with affective attitude only. Interaction effects of employee knowledge and affective attitude are also observed. This work’s main contribution lies in the development of an empirically-tested model of the potential impact of AI on organizations from an employee perspective in the pre-adoption phase. These results have practical implications for how organizations prepare for the arrival of this transformative technology.

Suggested Citation

  • Chiu, Yi-Te & Zhu, Yu-Qian & Corbett, Jacqueline, 2021. "In the hearts and minds of employees: A model of pre-adoptive appraisal toward artificial intelligence in organizations," International Journal of Information Management, Elsevier, vol. 60(C).
    • Handle: RePEc:eee:ininma:v:60:y:2021:i:c:s0268401221000724
    DOI: 10.1016/j.ijinfomgt.2021.102379
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    Cited by:

    1. Nan Zhu & Yuxin Liu & Jianwei Zhang & Na Wang, 2023. "Contingent reward versus punishment and compliance behavior: the mediating role of affective attitude and the moderating role of operational capabilities of artificial intelligence," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    2. Nonye Chukwuma & Loganathan Govender & Stanley C Onwubu, 2023. "Role of change leadership styles on cognitive rigidity at selected automobile dealerships in Durban, South Africa," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 12(1), pages 121-133, January.
    3. Saeed, Abubakr & Ali, Ashiq & Ashfaq, Saira, 2024. "Employees' training experience in a metaverse environment? Feedback analysis using structural topic modeling," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    4. Brendan James Keegan & Denis Dennehy & Peter Naudé, 2024. "Implementing Artificial Intelligence in Traditional B2B Marketing Practices: An Activity Theory Perspective," Information Systems Frontiers, Springer, vol. 26(3), pages 1025-1039, June.
    5. Olimpia Ban & Irina Maiorescu & Mihaela Bucur & Gabriel Cristian Sabou & Betty Cohen Tzedec, 2024. "AI between Threat and Benefactor for the Competences of the Human Working Force," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(67), pages 762-762, August.
    6. Ma, Xiaoyue & Huo, Yudi, 2023. "Are users willing to embrace ChatGPT? Exploring the factors on the acceptance of chatbots from the perspective of AIDUA framework," Technology in Society, Elsevier, vol. 75(C).
    7. Ahn, Suhyoung & Park, JungKun & Ye, Sangbeak, 2025. "How AI enhances employee service innovation in retail: Social exchange theory perspectives and the impact of AI adaptability," Journal of Retailing and Consumer Services, Elsevier, vol. 84(C).
    8. Zhang, Xi-xi & Hao, Xing-lin, 2025. "Linkage mechanism of antecedents for employees' continuous adoption of artificial intelligence virtual assistants," Technological Forecasting and Social Change, Elsevier, vol. 220(C).
    9. Bilal, Muhammad & Zhang, Yunfeng & Cai, Shukai & Akram, Umair & Halibas, Alrence, 2024. "Artificial intelligence is the magic wand making customer-centric a reality! An investigation into the relationship between consumer purchase intention and consumer engagement through affective attachment," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    10. Meng Bai & He Zhang & Junrui Zhang & Yuhui Jiang & Junmin Xu, 2025. "Challenging or Threatening? The Double-Edged Sword Effect of Intelligent Technology Awareness on Accountants’ Unethical Decision-Making," Journal of Business Ethics, Springer, vol. 197(1), pages 159-175, February.
    11. Tinofirei Museba, 2024. "Attitudes and perceptions of people towards Artificial Intelligence in human dominated job roles: A bibliometric study," International Journal of Business Ecosystem & Strategy (2687-2293), Bussecon International Academy, vol. 6(4), pages 91-104, September.
    12. María T. Soto-Sanfiel & Ariadna Angulo-Brunet & Christoph Lutz, 2025. "The scale of artificial intelligence literacy for all (SAIL4ALL): assessing knowledge of artificial intelligence in all adult populations," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-14, December.
    13. George Thomas & Norah Ali Albishri & Jamid Ul Islam & Muhammad Tanveer, 2025. "Exploring the Determinants of Artificial Intelligence Adoption Intention in the SMEs of United Arab Emirates," SAGE Open, , vol. 15(4), pages 21582440251, November.
    14. Zhang, Yangting & Fang, Jiaming & Liao, Miyan & Han, Lintong & Wen, Chao & Clement, Addo Prince, 2025. "Typography meets question type: Unveiling their matching effect on willingness to pay for AI products," Journal of Business Research, Elsevier, vol. 192(C).
    15. Ilanit SimanTov-Nachlieli, 2025. "More to Lose: The Adverse Effect of High Performance Ranking on Employees’ Preimplementation Attitudes Toward the Integration of Powerful AI Aids," Organization Science, INFORMS, vol. 36(1), pages 1-20, January.
    16. Qin, Min & Qiu, Shanshan & Mou, Jian, 2025. "Task supported or task decision-making? Which AI workplace enhances employee AI identity more in manufacturing enterprise," Technology in Society, Elsevier, vol. 83(C).
    17. Yanyan Liu & Fan Sheng & Ruyue Liu, 2025. "Generative AI adoption and employee outcomes: a conservation of resources perspective on job crafting, career commitment, and the moderating role of liking of AI," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-17, December.
    18. Janarthanan Balakrishnan & Yogesh K. Dwivedi & Laurie Hughes & Frederic Boy, 2024. "Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model," Information Systems Frontiers, Springer, vol. 26(3), pages 921-942, June.

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