Artificial Intelligence and Its Application in Procurement
Ho, Anh (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025051310973
https://urn.fi/URN:NBN:fi:amk-2025051310973
Tiivistelmä
Procurement undergoes revolutionary change through Artificial Intelligence (AI) because it helps automate processes and enhances both decision quality and operational efficiency. By assessing AI implementation in procurement operations, the research analyzes both the advantages and difficulties of this technology and proposes ways to adopt AI in practice accordingly.
The study combined interpretive and numerical data examination through its dual-methodology framework. The analysis combined both qualitative pattern extraction from employee feedback and quantitative measurement of adoption statistics.
AI implementation in the procurement process delivered multiple essential advantages, according to the research results. AI technologies improved decision-making speed, reduced operational expenses, enhanced supplier performance tracking and data accuracy. However, the thesis indicated the main obstacles, including high integration expenses, shortage of skilled AI manpower, insufficient data infrastructure, ethical concerns, and employee opposition. The analysis revealed that AI tools deliver benefits to procurement efficiency despite existing obstacles.
The author recommends that organizations implement a systematic method to address these obstacles. Organizations should start by running pilot tests to determine AI system feasibility before they expand AI application use. The implementation of AI tools requires thorough training programs to build employee competence. The integration of new systems into current operational frameworks requires essential workflow redesign. It is recommended that future studies should extend their analysis to more diverse regions and industries to improve data generalizability and develop industry-specific solutions.
The study combined interpretive and numerical data examination through its dual-methodology framework. The analysis combined both qualitative pattern extraction from employee feedback and quantitative measurement of adoption statistics.
AI implementation in the procurement process delivered multiple essential advantages, according to the research results. AI technologies improved decision-making speed, reduced operational expenses, enhanced supplier performance tracking and data accuracy. However, the thesis indicated the main obstacles, including high integration expenses, shortage of skilled AI manpower, insufficient data infrastructure, ethical concerns, and employee opposition. The analysis revealed that AI tools deliver benefits to procurement efficiency despite existing obstacles.
The author recommends that organizations implement a systematic method to address these obstacles. Organizations should start by running pilot tests to determine AI system feasibility before they expand AI application use. The implementation of AI tools requires thorough training programs to build employee competence. The integration of new systems into current operational frameworks requires essential workflow redesign. It is recommended that future studies should extend their analysis to more diverse regions and industries to improve data generalizability and develop industry-specific solutions.