Master thesis 'Barriers to AI adoption faced by enterprises in the European Union' is a framework for companies on the path of AI adoption. I begin by presenting definitions to limit the scope of considered technologies. In the following chapter, I study relevant theories to limit the field of study, build its structure and outline its basic elements. Chapter Environments of AI adoption completes the basic theoretical elements with concrete measures to show environmental conditions for AI adoption at the global level as well as at the level of selected representative countries. In the fifth chapter, I focus on the European Union and selected member states by adding more precise, qualitative explanations to complement the quantitative measures in the previous chapter. The reader will find the essence of this master thesis in Chapter 6. By examining available international studies on AI adoption, basic theoretical elements are attributed weights. Thereby, I provide organizations willing to adopt AI with a system of prioritization for successful AI adoption. The most widely recognized barriers are lack of workforce with sufficient skills, costs of adoption and cybersecurity.
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