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Adoption of artificial intelligence: A TOP framework-based checklist for digital leaders

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  • Tursunbayeva, Aizhan
  • Chalutz-Ben Gal, Hila

Abstract

In the evolving digital landscape, organizations and leaders face increasing pressure to adopt and effectively utilize artificial intelligence (AI), which is steadily entering the management, work, and organizational ecosystems and enabling digital transformations. We observe AI-based applications assisting employees in daily tasks, project management, decision-making, and collaboration. But the successful adoption of AI is a complex and multifaceted process that requires careful consideration of various factors. What are the specific factors affecting the full adoption of AI from a multilevel viewpoint? This article presents a framework-based checklist concerning technology, organizations, and people (TOP) designed to assist digital leaders in navigating the challenges associated with AI adoption. Drawing upon extensive research and industry insights, this checklist provides digital leaders with a comprehensive tool to assess and address critical considerations during the adoption of AI. By systematically evaluating the technology, organization, and people dimensions, organizations and digital leaders can enhance their chances of a successful digital transformation and gain a competitive advantage in the digital age.

Suggested Citation

  • Tursunbayeva, Aizhan & Chalutz-Ben Gal, Hila, 2024. "Adoption of artificial intelligence: A TOP framework-based checklist for digital leaders," Business Horizons, Elsevier, vol. 67(4), pages 357-368.
    • Handle: RePEc:eee:bushor:v:67:y:2024:i:4:p:357-368
    DOI: 10.1016/j.bushor.2024.04.006
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    1. Nam, Taewoo, 2019. "Technology usage, expected job sustainability, and perceived job insecurity," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 155-165.
    2. Ahmad Arslan & Cary Cooper & Zaheer Khan & Ismail Golgeci & Imran Ali, 2021. "Artificial intelligence and human workers interaction at team level: a conceptual assessment of the challenges and potential HRM strategies," International Journal of Manpower, Emerald Group Publishing Limited, vol. 43(1), pages 75-88, July.
    3. Aizhan Tursunbayeva & Raluca Bunduchi & Claudia Pagliari, 2020. "“Planned Benefits†Can Be Misleading in Digital Transformation Projects: Insights From a Case Study of Human Resource Information Systems Implementation in Healthcare," SAGE Open, , vol. 10(2), pages 21582440209, June.
    4. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    5. Gupta, Shaphali & Leszkiewicz, Agata & Kumar, V. & Bijmolt, Tammo & Potapov, Dmitriy, 2020. "Digital Analytics: Modeling for Insights and New Methods," Journal of Interactive Marketing, Elsevier, vol. 51(C), pages 26-43.
    6. Sarah Bankins & Paul Formosa & Yannick Griep & Deborah Richards, 2022. "AI Decision Making with Dignity? Contrasting Workers’ Justice Perceptions of Human and AI Decision Making in a Human Resource Management Context," Information Systems Frontiers, Springer, vol. 24(3), pages 857-875, June.
    7. Makarius, Erin E. & Mukherjee, Debmalya & Fox, Joseph D. & Fox, Alexa K., 2020. "Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization," Journal of Business Research, Elsevier, vol. 120(C), pages 262-273.
    8. Alex (Sandy) Pentland, 2008. "Honest Signals: How They Shape Our World," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262162563, April.
    9. Dan Avrahami & Dana Pessach & Gonen Singer & Hila Chalutz Ben-Gal, 2022. "A human resources analytics and machine-learning examination of turnover: implications for theory and practice," International Journal of Manpower, Emerald Group Publishing Limited, vol. 43(6), pages 1405-1424, March.
    10. Tursunbayeva, Aizhan & Di Lauro, Stefano & Pagliari, Claudia, 2018. "People analytics—A scoping review of conceptual boundaries and value propositions," International Journal of Information Management, Elsevier, vol. 43(C), pages 224-247.
    11. Nijs, Sanne & Gallardo-Gallardo, Eva & Dries, Nicky & Sels, Luc, 2014. "A multidisciplinary review into the definition, operationalization, and measurement of talent," Journal of World Business, Elsevier, vol. 49(2), pages 180-191.
    12. Ketevan Lomineishvili, 2021. "How Entrepreneurial Management and Continuous Learning Affect the Innovation and Competitiveness of Companies?," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 3, pages 459-468, September.
    13. Braganza, Ashley & Chen, Weifeng & Canhoto, Ana & Sap, Serap, 2021. "Productive employment and decent work: The impact of AI adoption on psychological contracts, job engagement and employee trust," Journal of Business Research, Elsevier, vol. 131(C), pages 485-494.
    14. Chowdhury, Soumyadeb & Budhwar, Pawan & Dey, Prasanta Kumar & Joel-Edgar, Sian & Abadie, Amelie, 2022. "AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework," Journal of Business Research, Elsevier, vol. 144(C), pages 31-49.
    15. Cubric, Marija, 2020. "Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study," Technology in Society, Elsevier, vol. 62(C).
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