Examining of factors influencing AI acceptance: self-efficacy, trust and hindrance Appraisal
Yuxin Mao, Yalan Liu · 2024
Artificial intelligence is disruptive and novel in changing the structure of businesses and interactions globally. Several bottlenecks hinder the widespread acceptance of AI, with common acceptance based on user acceptance being a primary factor. More specifically, the current work shows how AI self-efficacy helps acceptance of AI, which in turn influences attitude towards AI learning. This study uses a hybrid data collection approach to gather 390 valid responses from a diverse demographic across China's 23 provinces. It investigates AI self-efficacy's influence on AI acceptance, highlighting user trust's mediating role and AI hindrance evaluation's moderating effect. From the theoretical standpoint, the paper shall ignite a different view of AI acceptance. In practice, it supports sweeping acceptance of AI throughout such industries.