The Impact of AI on Enhancing Supply Chain Forecasting and Demand Planning
Yusuf Ali, Isra (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025051912994
https://urn.fi/URN:NBN:fi:amk-2025051912994
Tiivistelmä
This study examined how artificial intelligence and machine learning affect supply chain management, focusing on forecasting, sustainability, and operational efficiency. It aimed to assess how AI-powered solutions are changing traditional practices and to explore the advantages, challenges, and implications of adopting AI, especially for SMEs. The author used secondary data from peer-reviewed publications, scholarly journals, and industry reports to integrate existing conclusions and highlight trends in AI and ML applications, particularly in forecasting, sustainability efforts, and optimisation.
Findings showed that AI and ML enhance operational efficiency, forecasting accuracy, and support sustainability through improved resource planning and reduced waste. Challenges included high costs, data privacy, and a talent gap, especially for SMEs. The author recommends SMEs begin with pilot projects and scale gradually, while policymakers and leaders support training and establish stronger data governance for secure AI use in supply chains.
Findings showed that AI and ML enhance operational efficiency, forecasting accuracy, and support sustainability through improved resource planning and reduced waste. Challenges included high costs, data privacy, and a talent gap, especially for SMEs. The author recommends SMEs begin with pilot projects and scale gradually, while policymakers and leaders support training and establish stronger data governance for secure AI use in supply chains.