Aare, Lisell (2025) Understanding the Challenges and Opportunities for Small and Medium-Sized Enterprises Under the EU Artificial Intelligence Act. Bachelor thesis, Data Science and Society (DSS).
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Abstract
Regulating artificial intelligence (AI) technologies through the European Union’s Artificial Intelligence Act brings both challenges and opportunities for small and medium-sized enterprises (SMEs) across Member States. The Act introduces a risk-based framework that requires taking specific steps to ensure compliance. This includes the establishment of risk management systems, quality management processes, and detailed technical documentation. These are meant to promote safety, transparency, and accountability, especially concerning high-risk AI applications. However, SMEs often lack the legal expertise and financial resources to deal with these complex requirements, including implementing human oversight mechanisms or carrying out conformity assessments. At the same time, simplified documentation, regulatory sandboxes, and access to European Digital Innovation Hubs (EDIHs) aim to lower the compliance burden by offering practical support and shared infrastructure. Still, the availability of these support tools is uneven, and awareness among SMEs varies, leading to inconsistent levels of preparedness. Many smaller firms are unsure about their obligations or how to classify their AI systems, which increases the risk of unintentional non-compliance and financial penalties. This study reviews academic and policy literature to explore how legal complexity, limited internal resources, and uneven awareness contribute to uncertainty and create barriers to compliance. It also looks at the role of current support mechanisms, such as regulatory sandboxes and EDIHs, and how accessible, consistent, and usable they are for SMEs in different Member States.
| Item Type: | Thesis (Bachelor) |
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| Name supervisor: | Gstrein, O.J. |
| Date Deposited: | 24 Jul 2025 09:52 |
| Last Modified: | 24 Jul 2025 09:52 |
| URI: | https://campus-fryslan.studenttheses.ub.rug.nl/id/eprint/723 |
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