Adoption of Artificial Intelligence Technologies in SMEs: A Study of Kathmandu valley
TL;DR
The research provides a comprehensive overview of AI adoption patterns among SMEs in the Kathmandu Valley, highlighting both the opportunities for digital transformation and the challenges impeding widespread implementation.
Abstract
Purpose: This study examines the adoption of Artificial Intelligence (AI) among Small and Medium Enterprises (SMEs) in the Kathmandu Valley. Design/Methodology/Approach: The study employs an explanatory research design to investigate causal relationships among variables. The target population comprises owners, managers, and employees directly involved in decision-making or daily operations within SMEs in the Kathmandu Valley. A probability sampling technique was used to ensure representativeness, yielding a robust sample of 318 respondents. Data were analyzed using Structural Equation Modeling (SEM), a multi-factor statistical framework capable of examining relationships between latent (unobservable) and observed variables. Findings: The research provides a comprehensive overview of AI adoption patterns among SMEs in the Kathmandu Valley, highlighting both the opportunities for digital transformation and the challenges impeding widespread implementation. Originality/Value: This study contributes to the limited empirical literature on AI adoption in developing economies, particularly within Nepal’s SME sector. Keywords: artificial intelligence, attitude, AI adoption, SMEs, Kathmandu valley, structural equation modeling