AI 준비도 핵심 요인 도출을 위한 메타연구: 체계적 문헌고찰과 텍스트 분석의 통합적 접근

초록

The purpose of this study is to systematically identify the key factors that small and medium-sized enterprises (SMEs) need to prepare for the adoption of artificial intelligence (AI) technologies and to provide an analytical framework for diagnosing such readiness. To this end, this study employs a combined approach using a Systematic Literature Review (SLR) and text analysis techniques (TF-IDF and LDA) to derive AI readiness factors. Through the SLR, theoretically discussed AI readiness elements are organized, while text analysis based on interview question data actually used in prior studies is conducted to identify the core factors that have been emphasized in relation to technology adoption. This approach complements the existing theoretical discussions and aims to derive AI readiness factors that are more appropriate to the SME context. Although the two methodologies differ in their points of departure, they commonly identify innovation, infrastructure, compatibility, top management, strategy, resources, organizational culture, competitive environment, government regulation, data, and ethics as key factors. Based on these findings, the Technology-Organization-Environment (TOE) framework is reconfigured, and "data" and "ethics," reflecting the distinctive characteristics of AI, are added to propose an AI Readiness Matrix (AIR-Matrix) consisting of 11 factors. This matrix can be utilized by SMEs to assess their level of readiness and set priorities at the AI adoption stage, and it is expected to provide both practical and academic implications by helping to mitigate trial-and-error processes and initial risks associated with AI adoption. In particular, the importance of organizational factors and the cross-cutting role of data and ethics offer critical insights for formulating AI adoption strategies in SMEs.

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