This study aims to help companies with efficient investment and marketing strategies by empirically verifying the impact on satisfaction and purchase intention for artificial intelligence-based digital technology supported shopping assistants introduced in e-commerce. Frequency, factor, SEM, and multiple group analysises were conducted using SPSS 26.0 and Amos 26.0. As a result, first, motivated consumer innovativeness elements of AI shopping assistant were derived into a total of four categories: functional, hedonic, rational, and reliable. Second, in the order of hedonic and rational, satisfaction with the AI shopping assistant was significantly affected, and in the order of rational and functional, purchase intention was significantly affected. The satisfaction with the AI shopping assistant did not affect the purchase intention. Third, in the case of hedonic, the AI-preferred group had a more significant effect on satisfaction than the human-preferred group, and in the case of rational, there was no difference by group in purchase intention. Thus, it was found that consumers prefer AI shopping helpers for e-commerce because they can shop reasonably and are functionally convenient. Therefore, when introducing AI shopping assistants, it is essential to include content that can compare and analyze fundamental information, such as product prices, as well as search functions and payment system compatibility that facilitate shopping.

I.􀀃 Introduction
Ⅱ.􀀃 Review􀀃 of􀀃 Literature􀀃 and􀀃 Hypothesis
    1.􀀎 AI􀀎 shopping􀀎 assistant
    2.􀀎 Motivated􀀎 consumer􀀎 innovativeness
Ⅲ.􀀃 Research􀀃 Method
    1.􀀎 Research􀀎 model􀀎 and􀀎 research􀀎 question
    2.􀀎 Instrument􀀎 development
    3.􀀎 Participants􀀎 and􀀎 procedure
    4.􀀎 Statistical􀀎 analysis
IV.􀀃 Results
    1.􀀎 Variables’􀀎 reliability􀀎 and􀀎 confirmatory􀀎 factor􀀎analyses
    2.􀀎 Verification􀀎 of􀀎 structural􀀎 equation􀀎 model
    3.􀀎Validation􀀎of􀀎preferred􀀎shopping􀀎assistant􀀎effect
V.􀀃 Conclusion

• 김해정(성신여자대학교 의류산업학과 겸임교수) | Hye Jung Kim (Adjunct Professor, Dept. of Fashion Industry, Sungshin Women’s University, Korea)
• 이영주(성신여자대학교 의류산업학과 교수) | Young-Ju Rhee (Professor, Dept. of Fashion Industry, Sungshin Women’s University, Korea) Corresponding author