M.S. Candidate: Buse Şimşek
Program: Information Systems
Date: 22.12.2025 / 10:00
Place: B-116

Abstract: In today’s fast-evolving technological landscape, the adoption of Generative Artificial Intelligence (GenAI) technologies has become a crucial factor in the digital transformation of businesses across various sectors. In the IT sector, these technologies offer significant potential to enhance innovation, improve operational efficiency, and drive competitive advantage. Although generative AI technologies have various benefits for the IT sector, the adoption of generative AI can be hindered by various barriers, particularly in small and medium-sized enterprises (SMEs). This study aims to analyze the factors influencing the adoption of generative AI in SMEs within the IT sector in Türkiye. Using the Interpretive Structural Modeling (ISM) technique, the research examines the relationships between key barriers to AI adoption, providing a clearer understanding of how these barriers interconnect. The empirical analysis is based on data collected from a sample of SME workers, offering insights into the complex dynamics of AI integration. The study also identifies the interdependencies between these barriers, proposing a comprehensive model to better understand the adoption process. The study contributes to the theoretical framework on technology adoption, specifically within the context of generative AI, and provides the roadmap for policymakers and business leaders who want to facilitate AI implementation in the IT sector. This research enhances the understanding of AI adoption in the IT sector, particularly in the context of developing economies like Türkiye.