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A Study on the Typology of Latent Profiles and Influencing Factors Based AI Service Usage by the Youth

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2026, 31(10), pp.225~234
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : September 7, 2026
  • Accepted : October 6, 2026
  • Published : October 30, 2026

Min Soo Kim 1,  Woo Hong Cho 1

1서원대학교

Accredited

ABSTRACT

The purpose of this study is to classify latent profiles based on the level of AI service usage across various domains among youth and to analyze the factors influencing these profiles. To this end, data from the ‘2024 Digital Divide Survey’ were utilized, with a final sample of 573 youth aged 19 to 34. A 3-step approach was applied to conduct a latent profile analysis(LPA) and a logistic regression analysis. The main fingdings of this study are as follows. First, based on the level of AI service usage, the youth were classified into three distinct latent profiles: a ‘Low AI service Usage Group’, a ‘Medium AI Service Usage Group’, and a ‘High AI Service Usage Group’. Second, the result of the logistic regression analysis, conducted to identify the characteristics associated with each latent profile, revealed that youth with more positive attitudes toward digital technology were more likely to belong to the ‘Medium AI Service Usage Group’. Furthermore, those who had a college degree or higher, higher monthly average income, and higher life satisfaction were also more likely to belong to the ‘High AI Service Usage Group’. Based on these findings, this study suggests the necessity of providing customized AI education and establishing institutional support systems to promote the active use of AI services among youth.

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