Analysis of Generative AI Technologies' Adoption Using Interpretive Structural Modeling: Empirical Findings from Small and Medium-Sized IT Enterprises in Türkiye

Date

2025-12-22

Author

Şimşek, Buse

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In today’s evolving technological landscape, Generative Artificial Intelligence (GenAI) has emerged as a transformative component within digitalization processes across industries. In the IT sector, GenAI is increasingly being integrated into operations, yet its adoption presents distinct challenges, particularly for 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, offering a systematic 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.

Subject Keywords

Generative Artificial Intelligence (GenAI), Interpretive Structural Modelling, Adoption, IT Sector, Small and Medium-Sized Enterprises (SMEs)

URI

https://hdl.handle.net/11511/117424

Collections

Graduate School of Informatics, Thesis