AI has revolutionized the world and begun to influence an increasing number of industries worldwide. The pressure to implement AI has been evident at both EU and national levels. AI has demonstrated significant benefits in many companies, such as improved financial performance and efficiency. However, despite this, there are still many companies,particularly manufacturing companies, that have not implemented AI. Interestingly, manufacturing companies are among those that stand to benefit the most from AI. Therefore, exploring the intentions to adopt AI in manufacturing companies becomes relevant. The concept of adopting innovation and to some extent AI adoption, is theoretically explored. However, there is a lack of empirical evidence of what hindersmanufacturing companies from adopting and implementing AI. Furthermore, Swedish companies are less positive towards AI compared to global leaders. To address the identified research gap, the following research question has been formulated:  “What are the barriers and determinants that manufacturing companies in the northern part of Sweden face during the adoption and implementation of AI? “ The aim of this thesis is to investigate the factors influencing the adoption and implementation of AI solutions in manufacturing companies located in the northern part of Sweden, based on previous research and the empirical findings. To fulfill the purpose, we designed an exploratory qualitative study and conducted seven semi-structured interviews based on themes derived from TOE and TAM along with Rogers InnovationDiffusion. The key findings from the study revealed that the combined TOE-TAM model along with Rogers theory and other factors like leadership and external actors can explain the intention to adopt AI technology. Further, the significant barriers to AI adoption arethe lack of sufficient competence both internally and externally, another barrier was the costs of the implementation. Although we identified barriers to AI adoption, a lot of opportunities emerged as well. The determinants to adopt AI or not was the internal attitude and understanding of how the company can utilize AI. This thesis contributes with knowledge concerning the factors affecting AI adoption in manufacturing companies in the northern part of Sweden. It resulted in a revised conceptual framework that provides valuable insights for managers to consider when adopting AI. Finally, the thesis contributes with social implications that can assist in the rising concerns regarding AIs role in society.