Numerous publications have expressed concerns regarding the use of artificial intelligence (AI) in business decision-making. These concerns encompass bias, competence, the absence of an AI development strategy, and the limited attention given to strategic and legal issues and explainability of AI decisions. Therefore, this thesis aims to explore these concerns and examine how companies can address the associated challenges by focusing on the perspectives of the interviewees.Apart from theoretical research and literature review, this thesis relies on qualitative research through semi-structured interviews to collect empirical data. The study involved four respondents who participated in the interviews and provided valuable insights contributing to the findings.The results highlight privacy, explainability, bias fairness, and competence and education as the major legal and strategic concerns associated with AI in business decision-making. The respondents suggested various solutions, including promoting diverse and inclusive decisionmaking processes, data classification, and the utilization of AI models to explain the decisions made by AI systems. In addition, outside the direct focus of the study, some respondents mentioned challenges to knowledge transfer and the use of cloud solutions for data storage.The study’s contributions provide companies that are implementing or have already implemented AI technologies for business decision-making with knowledge about the current challenges in this domain. It also offers insights into how the interviewees ranked these challenges in terms of priority and their perspectives on potential solutions and actions to achieve a balance between efficiency and responsibility. However, the study has limitations, such as a small number of respondents, which restricted the analysis of correlations between their answers and potential relations with their roles or company size. Companies should be mindful of these limitations for further research in this area.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kau-95075 |
| Date | January 2023 |
| Creators | Lundberg, Filippa |
| Publisher | Karlstads universitet, Handelshögskolan (from 2013) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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