Level of AI Usage in Mining Regions: The Case of The City of Kolwezi, Democratic Republic of Congo, Lualaba Province

Abstract

Purpose: This study assesses the level, determinants, and perceived impacts of Artificial Intelligence (AI) adoption across industrial mining workers, artisanal miners, and administrative personnel in Kolwezi, Democratic Republic of Congo. Methodology: Based on a mixed-methods design involving 250 survey respondents and 3 focus groups collected between February and May 2025, the analysis reveals pronounced disparities in AI literacy and use. Findings: Industrial employees—75% of whom possess tertiary education—reported significantly higher AI familiarity (Mean = 3.94/5) and usage intentions (Mean = 4.12/5) than artisanal miners (Mean familiarity = 2.21/5), reflecting strong educational and digital divides. Correlation tests show positive associations between digital experience and AI behavioral intention (r = .63, p < .001), while fear of automation negatively predicts acceptance (r = –.41, p < .01). Focus-group insights highlight perceptions of increased safety, improved planning, and production optimization among industrial users, contrasted with concerns over job displacement among artisanal miners. These findings indicate that AI adoption in Kolwezi is advancing but remains uneven, shaped by socioeconomic status, digital exposure, and institutional context. Unique Contribution to Theory, Practice and Policy: The study contributes evidence for designing equitable, context-specific digital strategies in African mining cities.

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