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.
Maigari et al. (Mon,) studied this question.