Determining Factors Related to Artificial Intelligence Adoption Among Sri Lankan ICT Service Providers

Abstract

This study investigates the factors influencing Artificial Intelligence (AI) adoption among ICT service providers in Sri Lanka, a developing economy where AI integration remains in its early stages. Using the Technology-Organization-Environment (TOE) framework, six key determinants were examined, relative advantage, data quality, top management commitment, employee adaptability, competitive pressure, and external support. Data was collected via a structured questionnaire distributed to 146 ICT service providers, with the sample size determined using G*Power software for statistical robustness. Ordered probit regression was employed to analyze the data, as it offers precise insights for ordinal variables. The findings identify DQ and RA as significant drivers of AI adoption, underscoring the critical role of high-quality data and the operational benefits of AI technologies. However, TMC exhibited a negative impact, highlighting barriers in leadership awareness and alignment with AI strategies. Although CP, ES, and EA were not statistically significant, they demonstrated potential as mediators or moderators in specific contexts. This study bridges a critical gap by providing localized insights into AI adoption challenges and opportunities in Sri Lanka. It emphasizes the importance of data management, leadership commitment, and strategic alignment, offering actionable recommendations for policymakers and industry leaders to enhance competitiveness and digital transformation in the global economy.