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How Artificial Intelligence affords digital innovation: A cross-case analysis of Scandinavian companies

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  • Trocin, Cristina
  • Hovland, Ingrid Våge
  • Mikalef, Patrick
  • Dremel, Christian

Abstract

Artificial Intelligence (AI) is fuelling a new breed of digital innovation in Human Resource Management (HRM) by creating new opportunities for complying with General Data Protection Regulation (GDPR) during data collection and analysis, decreasing biases, and offering targeted recommendations. However, AI is also posing challenges to organisations and key assumptions about digital innovation processes and outcomes, making it unclear how to combine AI affordances with actors, goals, and tasks. We conducted a qualitative multiple-case study in Scandinavian organisations offering HR services. Grounded theory guided our data collection and analysis. Input-Process-Output framework and affordance theory supported the analysis of specific information processing constraints and enablers. We developed a framework to explain how AI affordances enable digital innovation and address the calls about definitional boundaries between innovation processes and outcomes. We showed how AI affordances are actualised and how this leads to reontologising decision-making and providing data driven legitimisation. Our study contributes to digital innovation research by elucidating AI affordances and their actualisation in organisations. We conclude with the implications to theory and practice, limitations, and suggestions for future research.

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  • Trocin, Cristina & Hovland, Ingrid Våge & Mikalef, Patrick & Dremel, Christian, 2021. "How Artificial Intelligence affords digital innovation: A cross-case analysis of Scandinavian companies," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    • Handle: RePEc:eee:tefoso:v:173:y:2021:i:c:s0040162521005138
    DOI: 10.1016/j.techfore.2021.121081
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    8. Plantec, Quentin & Deval, Marie-Alix & Hooge, Sophie & Weil, Benoit, 2023. "Big data as an exploration trigger or problem-solving patch: Design and integration of AI-embedded systems in the automotive industry," Technovation, Elsevier, vol. 124(C).
    9. Liu, Yang & Dong, Jiuyu & Mei, Liang & Shen, Rui, 2023. "Digital innovation and performance of manufacturing firms: An affordance perspective," Technovation, Elsevier, vol. 119(C).
    10. Abdelmohsen A. Nassani & Asad Javed & Joanna Rosak-Szyrocka & Ladislav Pilar & Zahid Yousaf & Mohamed Haffar, 2023. "Major Determinants of Innovation Performance in the Context of Healthcare Sector," IJERPH, MDPI, vol. 20(6), pages 1-14, March.
    11. Colombelli, Alessandra & Belitski, Maksim & D’Amico, Elettra, 2023. "Artificial Intelligence and Firm Innovation: The Resource-Allocation Perspective," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 202304, University of Turin.
    12. Zhang, Yu & Su, Jiafu & Guo, Honggui & Lee, Jeoung Yul & Xiao, Yan & Fu, Mingqiu, 2022. "Transformative value co-creation with older customers in e-services: Exploring the influence of customer participation on appreciation of digital affordances and well-being," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    13. Johnson, Prince Chacko & Laurell, Christofer & Ots, Mart & Sandström, Christian, 2022. "Digital innovation and the effects of artificial intelligence on firms’ research and development – Automation or augmentation, exploration or exploitation?," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    14. Emmanouil Papagiannidis & Ida Merete Enholm & Chirstian Dremel & Patrick Mikalef & John Krogstie, 2023. "Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes," Information Systems Frontiers, Springer, vol. 25(1), pages 123-141, February.
    15. Colombelli, Alessandra & Belitski, Maksim & D’Amico, Elettra, 2023. "Artificial Intelligence and Firm Innovation: The Resource-Allocation Perspective," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202316, University of Turin.
    16. Mariani, Marcello M. & Machado, Isa & Nambisan, Satish, 2023. "Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda," Journal of Business Research, Elsevier, vol. 155(PB).

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