However, implementing AI/ML in procurement is complex and requires overcoming challenges such as data availability, securing supplier engagement, and ensuring compliance with regulatory frameworks. Companies need to manage data silos, build strong supplier relationships, and adhere to privacy regulations like GDPR. Despite these hurdles, the article suggests that AI-driven supplier selection can significantly reduce the time needed for supplier discovery and improve risk prediction, ultimately enhancing supply chain efficiency.
Key takeaways:
- AI and ML can streamline supplier selection by leveraging data for price optimization, quality assurance, and on-time delivery predictions.
- Incorporating ESG factors into supplier selection is crucial, and AI/ML can help identify environmental impacts, labor standards, and public sentiment.
- Challenges in implementing AI/ML in supplier procurement include data availability, securing supplier engagement, and ensuring regulatory compliance.
- Overcoming these challenges can lead to reduced supplier discovery time and better supplier risk prediction.