Introduces a framework to enhance procurement through ethical AI in small businesses, suggesting improvements for implementation.
Small and Medium Enterprises (SME) in the U.S. face significant procurement challenges, like inefficiencies in supplier selection, cost inflation, and low bargaining power. While artificial intelligence (AI) offers transformative solutions, its adoption remains inconsistent due to ethical concerns, implementation barriers, and fears of workforce displacement. This paper introduces a three-pillar framework for AI-driven procurement in SMEs to address and mitigate these concerns. The framework consists of three pillars: Intelligent Automation & Decision Augmentation, which addresses how AI enhances, rather than replaces, human decision-making; Ethical Procurement Ecosystems, which incorporates practices ensuring fairness, transparency, and sustainability in AI-driven supplier networks; and lastly, Dynamic Regulatory Adaptation, which aligns AI use with evolving legal and industry standards. An implementation roadmap is provided along with suggested strategies for addressing anticipated challenges. The paper concludes with policy recommendations to guide SMEs in adopting AI responsibly in the context of best procurement practices, ensuring efficient supply chain management.
No takes yet. Share an insight, caveat, or question.
Amarasuriya et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: