Abstract :
The rapid adoption of artificial intelligence (AI)-based assessment systems in Pakistani elementary schools has produced a distinct and under-researched psychological phenomenon: AI-assessment anxiety. Characterised by fears of algorithmic bias, opaque decision-making, emotionally barren feedback, and perceived loss of agency, this construct differs substantially from classical test anxiety in its triggers, cognitive content, and clinical requirements. For elementary students in grades 3 through 6 (ages 8-12), who occupy Erikson's critical Industry versus Inferiority stage, exposure to impersonal algorithmic evaluation at the precise moment of foundational competence-belief formation carries significant developmental risk. Drawing on cognitive-behavioural theory (Beck, 2011), developmental psychology (Erikson, 1950), and the emerging literature on algorithmic anxiety (Baker & Hawn, 2022), this paper examines the specific characteristics and developmental implications of AI-assessment anxiety among elementary students in Karachi, evaluates school counsellors' preparedness and competency gaps, and proposes an evidence-informed counselling framework incorporating AI literacy education, adapted cognitive-behavioural strategies, preventative psychoeducation, and relational restoration approaches. A mixed-methods sequential explanatory design guides the empirical investigation across 12 Karachi elementary schools. This study aims to investigate whether AI-assessment anxiety constitutes a pressing concern warranting professional development, institutional policy reform, and targeted counselling intervention in Pakistan's rapidly AI-integrated educational landscape.