Perceptions vs Reality: Job Security in the Age of AI Evidenced from Public Organizations in Abuja, Nigeria - Mohammed Muson Yelwa; Manchien Leah Jelmak (Sociology Study Program, Faculty of Social Science and Law, Universitas Negeri Jakarta, 2025)
This study examines the perceived impact of artificial intelligence (AI) on job security among employees in the public sector in Abuja, revealing a critical dissonance between anticipated and actual workforce disruptions. Through a mixed-methods approach— combining quantitative surveys (323 respondents, sampled via Cochran’s formula from a population of 5,105) and qualitative interviews (4 purposively selected staff)—we found that 58.8% of employees perceived AI as a job security threat, despite 74.6% reporting no actual job losses. This misalignment, rooted in psychosocial anxieties rather than material displacement, aligns with socio-technical systems (STS) theory, highlighting how opaque communication and hierarchical inequities exacerbate fears. Managerial staff perceived significantly lower threats (p=0.018) than non-managerial employees, underscoring the role of institutional agency in shaping AI acceptance, while age-based technophobia myths were debunked (p=0.697). Qualitative insights revealed that participatory approaches, like the Directorate of Road Traffic Services’ phased AI integration, mitigated resistance by emphasising augmentation over replacement. The study challenges deterministic narratives of AI-driven job loss, arguing that perceived security hinges on socio-technical alignment—transparent dialogue, co-design, and universal upskilling—rather than technological inevitability. We propose policy levers to bridge this gap: (1) democratizing AI rollout decisions, (2) scaling role-specific literacy programs (e.g., Nigeria’s 3MTT initiative), and (3) instituting ethical oversight with worker representation. These findings offer a roadmap for Global South contexts navigating AI adoption, prioritising equitable workforce transitions through STS-informed governance. Public organisations can transform AI from a spectre of displacement into a tool for inclusive productivity by centring human dimensions alongside technical deployment.