The Impact of Generative AI-Based Data Analytics Solutions on Enterprise Adoption

doi:10.22716/sckt.2026.14.3.004

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2026 Vol.14, Issue 3 Preview Page Next Page

Research Article

The Impact of Generative AI-Based Data Analytics Solutions on Enterprise Adoption 생성형 AI 기반 데이터 분석 솔루션이 기업 수용에 미치는 영향: Joong-An Kim¹, Jong-Pil Yu², and Young-Eun Jo³
김중안¹, 우종필², 조영은³; ¹Director, BIMATRIX Co., Ltd.
²Professor, Department of Business Administration, Sejong University
³Researcher, Thermo Fisher Scientific Korea Ltd.

¹비아이매트릭스 이사, ²세종대학교 경영학 교수, ³써모피셔사이언티픽코리아 연구원

30 September 2026. pp. 51-64

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Abstract

본 연구는 생성형 AI 기반 데이터 분석 솔루션의 기업 수용에 미치는 영향을 규명하기 위해 확장된 기술수용모델(ETAM)을 적용하여 실증분석을 수행하였다. 본 연구에서는 생성형 AI 환경의 특성을 반영하여 조직적합성, 생산성, 편의성, 신뢰성, 인지된 위험을 외부 변수로 포함한 연구모형을 구성하였으며, 활용의도와 수용의도를 구분하여 기술 수용 과정을 분석하였다. 분석 결과, 생산성과 편의성은 인지된 유용성에 유의한 정(+)의 영향을 미치는 것으로 나타났으며, 사용용이성 또한 인지된 유용성에 강한 영향을 미치는 것으로 확인되었다. 반면 조직적합성과 신뢰성은 유의한 영향을 미치지 않는 것으로 나타났다. 또한 인지된 유용성은 활용의도에 강한 영향을 미치며, 활용의도는 수용의도에 유의한 영향을 미치는 핵심 매개 변수로 확인되었다. 본 연구는 생성형 AI 기반 분석 환경에서 실제 업무 활용성과 유용성 인식이 기술 수용의 핵심 요인임을 실증적으로 제시하였으며, 기업의 생성형 AI 도입 전략 수립에 실무적 시사점을 제공한다.

This study conducted an empirical analysis using the Extended Technology Acceptance Model (ETAM) to examine the factors influencing corporate acceptance of generative AI-based data analytics solutions. The research model included organizational fit, productivity, convenience, reliability, and perceived risk as external variables reflecting the characteristics of generative AI environments. In addition, usage intention and acceptance intention were distinguished to analyze the technology acceptance process. The results showed that productivity and convenience had significant positive effects on perceived usefulness, while perceived ease of use also strongly influenced perceived usefulness. In contrast, organizational fit and reliability did not show significant effects. Furthermore, perceived usefulness significantly affected usage intention, and usage intention had a significant effect on acceptance intention. This study empirically demonstrates that practical usability and perceived usefulness are key factors in the acceptance of generative AI-based analytics solutions and provides practical implications for establishing corporate AI adoption strategies.

Keywords

Generative AI

Data analytics

Extended Technology Acceptance Model (ETAM)

Organizational fit

Adoption intention

References

F.D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol.13, No.3, pp.319-340, 1989.
10.2307/249008
V. Venkatesh, and F.D. Davis, “A theoretical extension of the technology acceptance model: Four longitudinal field studies”, Management Science, Vol.46, No.2, pp.186-204, 2000.
10.1287/mnsc.46.2.186.11926
V. Venkatesh, M.G. Morris, G.B. Davis, and F.D. Davis, “User acceptance of information technology: Toward a unified view”, MIS Quarterly, Vol.27, No.3, pp.425-478, 2003.
10.2307/30036540
I. Ajzen, “The theory of planned behavior”, Organizational Behavior and Human Decision Processes, Vol.50, No.2, pp.179-211, 1991.
10.1016/0749-5978(91)90020-T
D.L. Goodhue, and R.L. Thompson, “Task–technology fit and individual performance”, MIS Quarterly, Vol.19, No.2, pp.213-236, 1995.
10.2307/249689
L.L. Berry, K. Seiders, and D. Grewal, “Understanding service convenience”, Journal of Marketing, Vol.66, No.3, pp.1-17, 2002.
10.1509/jmkg.66.3.1.18505
D. Gefen, E. Karahanna, and D. Straub, “Trust and TAM in online shopping: An integrated model”, MIS Quarterly, Vol.27, No.1, pp.51-90, 2003.
10.2307/30036519
W.H. DeLone, and E.R. McLean, “The DeLone and McLean model of information systems success: A ten-year update”, Journal of Management Information Systems, Vol.19, No.4, pp.9-30, 2003.
10.1080/07421222.2003.11045748
M.S. Featherman, and P.A. Pavlou, “Predicting e-services adoption: A perceived risk facets perspective”, International Journal of Human–Computer Studies, Vol.59, No.4, pp.451-474, 2003.
10.1016/S1071-5819(03)00111-3
V. Venkatesh, J.Y.L. Thong, and X. Xu, “Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology”, MIS Quarterly, Vol.36, No.1, pp.157-178, 2012.
10.2307/41410412
A. Bhattacherjee, “Understanding information systems continuance: An expectation-confirmation model”, MIS Quarterly, Vol.25, No.3, pp.351-370, 2001.
10.2307/3250921
이관섭, 우종필, 임설아, “인공지능(AI) 스피커 이용의향에 영향을 미치는 요인 연구: 확장된 기술수용모델(E-TAM)을 중심으로”, 융복합지식학회논문지, 제8권 제4호, pp.59-69, 2020.
이용혁, 신승우, “TAM 확장모형을 활용한 공공부문 AI 시스템 도입요인 연구”, 정보정책연구, 제29권 제3호, pp.45-72, 2022.
김규석, 정진우, 박수정, “AI 기반 업무자동화 도입요인 분석: 기술수용모형 확장 연구”, 정보시스템연구, 제32권 제2호, pp.111-132, 2023.

Information

Publisher :The Society of Convergence Knowledge
Publisher(Ko) :융복합지식학회
Journal Title :The Society of Convergence Knowledge Transactions
Journal Title(Ko) :융복합지식학회논문지
Volume : 14
No :3
Pages :51-64
DOI :https://doi.org/10.22716/sckt.2026.14.3.004

[1] F.D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol.13, No.3, pp.319-340, 1989.
10.2307/249008

[2] V. Venkatesh, and F.D. Davis, “A theoretical extension of the technology acceptance model: Four longitudinal field studies”, Management Science, Vol.46, No.2, pp.186-204, 2000.
10.1287/mnsc.46.2.186.11926

[3] V. Venkatesh, M.G. Morris, G.B. Davis, and F.D. Davis, “User acceptance of information technology: Toward a unified view”, MIS Quarterly, Vol.27, No.3, pp.425-478, 2003.
10.2307/30036540

[4] I. Ajzen, “The theory of planned behavior”, Organizational Behavior and Human Decision Processes, Vol.50, No.2, pp.179-211, 1991.
10.1016/0749-5978(91)90020-T

[5] D.L. Goodhue, and R.L. Thompson, “Task–technology fit and individual performance”, MIS Quarterly, Vol.19, No.2, pp.213-236, 1995.
10.2307/249689

[6] L.L. Berry, K. Seiders, and D. Grewal, “Understanding service convenience”, Journal of Marketing, Vol.66, No.3, pp.1-17, 2002.
10.1509/jmkg.66.3.1.18505

[7] D. Gefen, E. Karahanna, and D. Straub, “Trust and TAM in online shopping: An integrated model”, MIS Quarterly, Vol.27, No.1, pp.51-90, 2003.
10.2307/30036519

[8] W.H. DeLone, and E.R. McLean, “The DeLone and McLean model of information systems success: A ten-year update”, Journal of Management Information Systems, Vol.19, No.4, pp.9-30, 2003.
10.1080/07421222.2003.11045748

[9] M.S. Featherman, and P.A. Pavlou, “Predicting e-services adoption: A perceived risk facets perspective”, International Journal of Human–Computer Studies, Vol.59, No.4, pp.451-474, 2003.
10.1016/S1071-5819(03)00111-3

[10] V. Venkatesh, J.Y.L. Thong, and X. Xu, “Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology”, MIS Quarterly, Vol.36, No.1, pp.157-178, 2012.
10.2307/41410412

[11] A. Bhattacherjee, “Understanding information systems continuance: An expectation-confirmation model”, MIS Quarterly, Vol.25, No.3, pp.351-370, 2001.
10.2307/3250921

[12] 이관섭, 우종필, 임설아, “인공지능(AI) 스피커 이용의향에 영향을 미치는 요인 연구: 확장된 기술수용모델(E-TAM)을 중심으로”, 융복합지식학회논문지, 제8권 제4호, pp.59-69, 2020.

[13] 이용혁, 신승우, “TAM 확장모형을 활용한 공공부문 AI 시스템 도입요인 연구”, 정보정책연구, 제29권 제3호, pp.45-72, 2022.

[14] 김규석, 정진우, 박수정, “AI 기반 업무자동화 도입요인 분석: 기술수용모형 확장 연구”, 정보시스템연구, 제32권 제2호, pp.111-132, 2023.

The Society of Convergence Knowledge Transactions ISSN:2287-8920(Print) 융복합지식학회논문지

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