The role of artificial intelligence in enhancing supply chain performance: Insights from Tanzania brewery companies
Résumé
This study was deliberately designed to empirically examine how Artificial Intelligence (AI) enhances supply chain performance within Tanzanian brewery companies, addressing a critical gap between global theoretical potential and local practical realities. Using a mixed-methods, embedded single-case study approach, data were collected from 86 participants at Tanzania Breweries Limited (TBL) through questionnaires, semi-structured interviews, and focus group discussions. The findings revealed a fragmented yet influential adoption landscape, where tools like predictive analytics and machine learning significantly boosted service quality and certain efficiency measures; however, these benefits were notably limited by organizational resistance, weak data governance, and major external infrastructural barriers. As an original contribution, this study offers fresh, context-specific insights into the socio-technical dynamics of AI adoption in a lesser-studied Tanzanian industrial setting. Practically, managers are urged to prioritize core investments in change management and data integrity, while socially, effective integration can promote market stability and skills growth, contributing to wider socioeconomic progress. In conclusion, the study emphasizes that AI’s transformative promise is not assured by technology alone but depends on strong internal capacity and a supportive external environment. A noted limitation is the single-case focus, which may restrict generalization across other industries. Therefore, it is recommended that firms adopt a phased implementation strategy grounded in solid data governance and pilot projects, while fostering public-private partnerships to address the broader external challenges slowing digital transformation.
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