The Impact of Artificial Intelligence on Digital Skills, Job Dissatisfaction, and Job Security Concerns: An Evidence Approach

This study investigated the impact of Artificial Intelligence (AI) adoption on digital skills, job dissatisfaction, and job security concerns among staff of Federal Polytechnic Damaturu, Yobe State, Nigeria. Despite the growing integration of AI-driven tools into academic and administrative operations across Nigerian tertiary institutions, limited empirical work has jointly examined these dimensions of the staff experience within a single institutional setting. Anchored on the Technology Acceptance Model, the Job Demands-Resources Model, and Herzberg's Two-Factor Theory, the study adopted a descriptive survey design within the positivist paradigm. A structured questionnaire was administered to a stratified random sample of 171 academic and non-academic staff drawn from five academic departments and two ICT-related units, determined using Yamane's formula from a population of 300; 150 valid responses (87.7%) were analysed using descriptive statistics benchmarked against a criterion mean of 3.0. Results showed that digital skills significantly and positively influenced effective AI utilisation (mean = 3.94), although staff reported inadequate AI-specific training despite general digital literacy. AI adoption did not, on the whole, significantly increase job dissatisfaction (mean = 2.83), except where transition support was inadequate and where AI reduced human interaction. Job security concerns were only mildly elevated overall (mean = 3.07) and were driven more by unclear institutional communication than by fear of outright job replacement. Staff strongly endorsed interventions such as clear AI policy, continuous upskilling, and human-complemented performance appraisal (mean = 3.98). The study concludes that successful, human-centred AI adoption in Nigerian polytechnics depends less on staff resistance to technology and more on the presence of adequate organisational resources, communication, and support.