A Framework for Adopting Generative AI in Small and Medium-Sized Enterprises to Achieve Sustainable Value
Open Access
- Author:
- Wells, Ryan
- Area of Honors:
- Enterprise Technology Integration
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Rosalie Ocker, Thesis Supervisor
Edward J Glantz, Thesis Honors Advisor - Keywords:
- Generative Artificial Intelligence
Gen AI
Small and Medium-Sized Enterprises
SMEs
Value Creation
Gen AI-SME Value Framework
GSVF
Technology Adoption
Semi-Structured Interviews - Abstract:
- Since 2022, the rapid advancement of Generative Artificial Intelligence (Gen AI) has offered substantial benefits for both small and medium-sized enterprises (SMEs). However, ambiguity surrounding how SMEs should approach Gen AI adoption presents significant barriers to successfully realizing its potential value. This thesis addresses these barriers by developing the Gen AI-SME Value Framework (GSVF): a practical tool that can support SMEs looking to maximize the value of Gen AI adoption. Research used to ground the framework, which divides the adoption process into five layers, comes from a systematic review of current academic literature and practitioner insights. To evaluate its utility, the GSVF was applied to 12 organizational contexts through semi-structured interviews with SME employees. Together, the extensive literature review paired with the practical applications enable SMEs to confidently use this framework for making more informed decisions that help them achieve net benefits from adopting Gen AI.
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