MAJLINDA ÇAKALLI1*
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1Department of Economics and Rural Development Policies, Agricultural University of Tirana, Albania
Abstract Digital transformation and e-government are strategic priorities worldwide. In Albania, adoption of digital public services has been slow, and procurement procedures remain a hotspot for corruption. This study assesses the potential of AI-driven tools to support smart governance in Albania’s public procurement system. We first organize existing evidence on AI in government, highlighting applications like anomaly detection, risk scoring and automated monitoring in procurement. Using a mixed-method approach, we then design a quantitative pilot analysis on simulated procurement data: for example, a logistic regression model shows how contract value and bid patterns can predict suspicious tenders. We also present a comparative table of possible analysis methods. Our findings suggest AI can markedly improve anomaly detection and reduce opaque practices, but effectiveness depends on data quality, institutional capacity and governance safeguards. We discuss policy implications and recommend a phased, transparent AI integration strategy, combining algorithmic monitoring with strong human oversight. This approach could enhance Albania’s procurement integrity and support public service modernization. Keywords: e-procurement, digitalization, AI, transparency, corruption, machine learning, AI governance |