Exploring the AI Adoption Challenges in Small Enterprises in Non-Technology Industries
Au, Hoan
Au, Hoan
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2024-12-18
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Abstract
This study examines the challenges and strategies associated with adopting artificial intelligence (AI) in small enterprises within non-technology industries. Utilizing a mixed-methods approach, the research integrates quantitative analysis of datasets, including AI risk repositories and tools, with qualitative insights from case studies of GetTransfer, FC Beauty, and PhoenixFire. The findings reveal that while AI tools like productivity and chat applications dominate due to their accessibility and utility, small businesses face significant hurdles, including resource constraints, technical expertise deficits, and vague ethical standards. Case studies highlight contrasting approaches: internal AI development versus strategic partnerships with external experts. This study underscores the importance of resource allocation, leadership, and ethical frameworks in mitigating AI adoption barriers. The implications extend to providing actionable recommendations for small enterprises, while the study acknowledges limitations such as the narrow case study scope and reliance on secondary data. Future research opportunities include broader longitudinal studies and exploration of advanced AI applications across diverse non-technology sectors.