Introduction
Job search is considered an essential activity that individuals engage in at various stages of their careers. Artificial Intelligence (AI) is revolutionising this landscape, yet very little is known about the motivations driving early-career individuals to adopt AI tools in their job search process.


Purpose
Therefore, this study aimed to investigate how perceptions and emotions influence behavioural intentions to use AI-based job search tools. Drawing on the Theory of Reasoned Action, the Technology Acceptance Model, and the Career Self-Management framework, we tested a moderated serial mediation model. Specifically, we examined whether Perceived Ease of Use (PEOU) predicts Behavioural Intention (BI) through Perceived Usefulness (PU) and Positive Attitude (PA), and whether Job Search Self-Efficacy (JSSE) moderates this indirect relationship.


Method
For the purpose of this study, the data were obtained from a sample of 179 university students and recent graduates in Italy, who were invited to complete an online questionnaire with the psychometric scales measuring the core variables.


Results
The results supported proposed serial mediation (PEOU → PU → PA → BI), highlighting the importance of combining cognitive and emotional variables in the adoption of AI in the Job search process. However, JSSE did not significantly moderate the indirect relationship, suggesting that although job search self-efficacy is essential to motivate job search behaviours, it might not shape early-career individuals' decisions to adopt AI tools for job seeking.


Conclusions
The findings from this research extend the existing models by showing that cognitive, emotional, and motivational factors might help in shaping job seekers' intentions to use technology. They also suggest some practical ways to improve AI-based job search tools, making them more user-friendly while catering to job seekers' emotional and psychological needs.