In God We Trust - All others Must Bring Data
Sammanfattning: The goal of this study is to investigate the organisational and managerial gaps impeding the successful adoption and deployment of machine learning in many organisations. The aim is to narrow the research gap on why the adoption of machine learning is slow, and provide further insights on what actions organisations must take to encourage advancements. The findings build on qualitative data from in-depth interviews with data scientists, analysts and analytics managers in 16 different organisations in Sweden. The results show that there are essential gaps in resources and capabilities which are delaying advancements of machine learning. This study make use of technology innovation theory and resource-based theory to analyse the identified gaps and suggest capabilities organisations should build to bridge them. The study concludes that two of the most important capabilities to develop to promote the adoption of machine learning is the ability to systematically educate management and business units, and the ability to connect analytics to strategy.
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