| Autor: |
Solaimani, Sam, Dabestani, Reza, Harrison-Prentice, Thomas, Ellis, Edward, Kerr, Michael, Choudhury, Abhishek, Bakhshi, Naser |
| Zdroj: |
International Journal of Business Information Systems; 2024, Vol. 45 Issue: 4 p429-453, 25p |
| Abstrakt: |
Artificial intelligence (AI) is becoming a strategic asset for businesses across all sectors. While most large companies have taken their first steps towards AI adoption, the success has remained strikingly limited. The current underdeveloped understanding of the critical success factors (CSFs) is argued to be one of the reasons for failing AI adoption. This study applies a mixed-methods approach, in which a broad information systems (IS) literature is systematically reviewed to identify CSFs relevant to AI adoption, including management support, business casing, problem orientation, data quality, data governance, cyber security and regulations. Next, an analytic hierarchy process (AHP) survey is combined with expert interviews to empirically rank and refine the identified CSFs across a multi-stage AI adoption model. The findings contribute to the scholarly discourse on CSFs relevant to AI adoption and help firms sharpen their focus and leverage their resources efficiently towards a more effective adoption of AI. |
| Databáze: |
Supplemental Index |
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