Mind Over Machine: Understanding Engineers’ AI Opportunity and Risk Perceptions through Psychological Capital - Singh, Deeksha; Sharma, Parul; Gupta, Shelleka; Sharma, Bonia (Journal of Engineering Education Transformations, 2026)
The rapid spread of artificial intelligence (AI) is reshaping the workplace, generating responses that range from optimism about new opportunities to concerns over job insecurity. This study explores how engineers perceive AI opportunities (AIOP) and their associated unemployment risk perceptions (URP), with a focus on the mediating role of psychological capital (PsyCap). PsyCap comprising resilience, self-efficacy, optimism, and hope is positioned as a vital psychological resource enabling engineers to adapt to AI-driven disruptions, drawing upon Cognitive Appraisal Theory. The analysis was conducted using SmartPLS-4 with reliability indices (α, CR, AVE) and SRMR-based model fit. The sample consisted of 221 engineers (60% male, 50% aged 23–33 years) from Punjab, J&K and NCR-Delhi. The findings indicate that Psychological Capital exerts a significant indirect effect, confirming its mediating role between AIOP and URP. Higher levels of PsyCap appear to lessen anxiety regarding technological displacement by enabling individuals to perceive AI as an opportunity rather than a threat. These insights emphasize that preparing engineers for a digital and sustainable world requires more than technical upskilling; it also necessitates strengthening psychological preparedness. By integrating psychological empowerment with digital competence, the study highlights a dual pathway toward building resilient, future-ready engineers aligned with the vision of Industry 5.0. The results hold practical implications for educators, industry leaders, and policymakers in designing holistic strategies that merge emerging technologies with future skills to foster sustainable employability.