Enhancing AI Auto Efficacy: Role of AI Knowledge, Information Source, Behavioral Intention and Information & Communications Technology Learning

Abstract

This study examines how employees' AI knowledge and understanding affects their auto-efficacy, behavioural intents, and ICT learning in Saudi Arabian software houses. The study seeks to understand how AI knowledge affects these outcomes and discover moderating and mediating factors. A method of quantitative analysis was used with 289 software firm employees. Data were acquired using a structured questionnaire using research-based scales. Data analysis using Partial Least Squares Structural Equation Modelling (PLS-SEM) examined complex construct interactions. AI knowledge significantly affects auto-efficacy, behavioural intention, and ICT learning. Behavioural intention mediates AI knowledge, auto-efficacy, and ICT learning. The impact of AI knowledge on self-efficacy is moderated by information source quality. These findings emphasise AI knowledge and context of AI learning. This study integrates AI-specific features into technology adoption models to improve theory. It highlights how targeted AI training programs and high[1]quality information sources may raise employee engagement with AI technology, serving as practical advice for companies aiming to improve their technology and workforce readiness