Faroleiro, PauloBisceglia, Rosalia2025-07-222025-07-222025-03-072025-01-06http://hdl.handle.net/10362/185430This research explores the development of artificial intelligence (AI) and machine learning (ML) in supply chain management (SCM), taking into consideration their transformational potential and inherent risks. By analyzing data from surveys and interviews conducted with managers of various sectors, the research identifies three critical risks: data quality, cyber security and transparency. The findings provide the need for strong data governance, proactive cybersecurity measures and the adoption of AI frameworks that can be explained to improve confidence and efficiency. Recommendations include sector-specific risk management strategies, inter-departmental collaboration and ethical guidelines. This research provides insights to optimize AI and ML adoption in SCM, mitigating associated risks.engAI risksSupply chain managementMachine learning transparencyData governanceCybersecurity in SCMmaster thesis203958900