Artificial Intelligence in the Pocket: Factors Influencing Generation Z's Intention to Use AI-Powered Mobile Banking Applications

The survey examines the factors affecting the intention to utilize AI-powered features in mobile banking among Generation Z customers. Technology Acceptance Method was extended with perceived trust (PT) and subjective norms (SN) to found users' intentions and attitudes towards using AI in mobile banking. An online google form was distributed to engineering graduate students to collect data. The suggested theories were tested with the use of structural equation modeling (SEM). The results display that views about AI and the intention to employ it in mobile banking are positively influenced by perceived usefulness (PU) and perceived ease of use (PEU). Additionally, it was discovered that the intention to employ AI in mobile banking was significantly positively impacted by SN and PT. There are significant theoretical and practical ramifications to the subject. Theoretically, it broadens the applicability of the technological acceptance method to m-banking powered by AI and offers a thorough grasp of the adoption determinants. Managerially, the findings guide banks in developing effective techniques to promote the adoption of AI-powered features, like emphasizing the usefulness and ease of use of these technologies, building trust, and leveraging social influences. The study underscores the significance of catering to the unique preferences of Generation Z customers to drive the successful integration of AI in mobile banking.

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Publication Details

Published
2024-11-29
DOI
https://doi.org/10.1109/icdcc62744.2024.10961558
Citations
2
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
2.10
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article

Artificial Intelligence in the Pocket: Factors Influencing Generation Z's Intention to Use AI-Powered Mobile Banking Applications

Ravi Sankar Pasupuleti, Deepthi Thiyyagura, Pradeesh Babu, Anitha Bhimavarapu
2 citations
Technology Adoption and User Behaviour
2.10
article

Artificial Intelligence in the Pocket: Factors Influencing Generation Z's Intention to Use AI-Powered Mobile Banking Applications

Ravi Sankar Pasupuleti, Deepthi Thiyyagura, Pradeesh Babu, Anitha Bhimavarapu
article en
2 citations

Abstract

The survey examines the factors affecting the intention to utilize AI-powered features in mobile banking among Generation Z customers. Technology Acceptance Method was extended with perceived trust (PT) and subjective norms (SN) to found users' intentions and attitudes towards using AI in mobile banking. An online google form was distributed to engineering graduate students to collect data. The suggested theories were tested with the use of structural equation modeling (SEM). The results display that views about AI and the intention to employ it in mobile banking are positively influenced by perceived usefulness (PU) and perceived ease of use (PEU). Additionally, it was discovered that the intention to employ AI in mobile banking was significantly positively impacted by SN and PT. There are significant theoretical and practical ramifications to the subject. Theoretically, it broadens the applicability of the technological acceptance method to m-banking powered by AI and offers a thorough grasp of the adoption determinants. Managerially, the findings guide banks in developing effective techniques to promote the adoption of AI-powered features, like emphasizing the usefulness and ease of use of these technologies, building trust, and leveraging social influences. The study underscores the significance of catering to the unique preferences of Generation Z customers to drive the successful integration of AI in mobile banking.

Arunai Engineering College (IN)
Decent work and economic growth
Openalex Percentile: Top 8%
Technology Adoption and User Behaviour
2.10
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Artificial Intelligence in the Pocket: Factors Influencing Generation Z's Intention to Use AI-Powered Mobile Banking Applications — Ravi Sankar Pasupuleti, Deepthi Thiyyagura, et al. · (2024) | TGRS Research Map | TGRS