Journal of Wellbeing Management and Applied Psychology (웰빙융합연구)

Korea Wellbeing Convergence Association (한국웰빙융합학회)
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Food Industry AI Service Adoption Process from a Wellness Perspective: A Case Study

  • Kapseon KIM (Faculty of Liberal Art, Jungwon University) ;
  • Seunghyeon LEE (Department of Food Science & Service, Eulji University) ;
  • Seong-Soo CHA (Food Biotechnology Major, Eulji University)
  • Received : 2025.02.11
  • Accepted : 2025.02.15
  • Published : 2025.02.28
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Abstract

This study presents a comprehensive analysis of AI service adoption in the food industry through a wellness-oriented perspective, utilizing a systematic literature review of publications from 2014 to 2024. Through an extensive examination of relevant literature, we identify three critical dimensions: the transformative impact of AI on consumer health and well-being, the fundamental challenges in AI service implementation, and strategic frameworks for successful adoption. Our findings demonstrate that AI services manifest primarily in three distinct forms: process automation, cognitive insights, and cognitive engagement, with cognitive insights emerging as the predominant form, particularly in quality control and supply chain optimization. The research reveals significant challenges, including data quality management, organizational resistance, and workforce adaptation, while emphasizing the critical importance of balancing technical innovation with wellness value creation. We contribute to the existing literature by developing an integrated theoretical framework that synthesizes technological, organizational, and wellness perspectives in AI adoption. The study provides both theoretical contributions through a novel wellness-centric approach to AI adoption research and practical implications by offering strategic guidelines for food industry practitioners. Our findings suggest that successful AI implementation requires a holistic strategy that encompasses technological advancement, organizational transformation, and sustainable wellness value creation, thereby advancing the theoretical understanding of AI.

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Acknowledgement

This work was supported by the research grant of the KODISA Scholarship Foundation in 2025.

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