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Field: Strukturomvandling

Drivers of AI adoption - a literature review

This paper examines the literature and identifies the drivers of AI adoption. The main results are synthesised in a conceptual framework that highlight the AI capabilities needed to impact firm performance and deliver competitive advantage.

Artificial intelligence (AI) has attracted significant attention in the academic literature and in businesses in the last decade. To gain business value, managers of private firms increase the adoption of AI systems. However, research on the drivers of AI adoption is still scarce, and knowledge needs to be systematised. In this context, the present study aims to fill this gap by providing a literature review to identify the drivers of AI adoption by firms. Research articles on AI adoption are analysed. In addition to gaps for future studies, a conceptual framework is proposed and discussed according to the drivers, i.e., the AI capabilities that firms need to gain a competitive advantage from their AI investments. This study identifies and describes seven AI resources that can drive AI adoption: (i) data, (ii) AI technology, (iii) AI skills, (iv) intrafirm coordination, (v) AI business models, (vi) AI innovation ecosystems, and (vii) coordination across organisational boundaries. These findings contribute to both theoretical and managerial perspectives, with opportunities for generating novel theories and new forms of management practices.


Drivers of AI adoption - a literature review

Serial number: Rapport 2021:07

Reference number: 2020/250

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