AI adoption in Icelandic tech startups : applications, barriers, and future opportunities

This mixed-methods study investigates the adoption of artificial intelligence (AI) within Iceland's tech startups, addressing a research gap in smaller economies. Leveraging the Technology-Organization-Environment (TOE) framework, the study examines current AI applications, barriers to adoption, and future opportunities among Icelandic tech startups. Data were collected through qualitative interviews and quantitative surveys, with purposive sampling ensuring the inclusion of participants offering diverse insights into AI adoption challenges and strategies. The findings reveal that AI adoption in Icelandic tech startups is viewed as transformative, offering potential for operational efficiency, product innovation, and enhanced customer engagement. However, the adoption process remains in its early stages, hindered by practical barriers including limited technical expertise, financial constraints, and data quality issues. Regulatory concerns, such as compliance with data protection laws, further complicate the integration of AI technologies. These challenges are compounded by the characteristics of small economy like Iceland's, which restricts resource availability and scalability compared to larger markets. Despite these obstacles, the research highlights a growing optimism within Icelandic tech startups, driven by a collaborative entrepreneurial culture and supportive government initiatives. Participants emphasized the importance of targeted interventions, including talent development programs, enhanced access to funding, and clearer regulatory guidance, to enable successful AI integration.

Author dc:creator

• Ásgeir Hólm Sævarsson 1989-

Contributors dc:contributor

• Háskólinn í Reykjavík

• Stjórnun nýsköpunar
• Meistaraprófsritgerðir
• Gervigreind
• Tækninýjungar
• Nýsköpun í atvinnulífi
• Innovation management
• Artificial intelligence
• Technological innovations

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/1946/49103

OAI identifier oai:identifier

oai:skemman.is:1946/49103