This article reviews existing literature on automation and AI in procurement and explores the boundaries and opportunities for the application of artificial intelligence (AI) in electronic procurement systems, considering the ongoing digital transformation in both public and corporate sectors (Vital IT Pros, 2024). The distinction between rule-based automation and intelligent machine learning (ML) – based algorithms is emphasized. The study substantiates the areas where AI solutions can be effectively applied in procurement processes – from predictive analytics to tender documentation processing through natural language processing (NLP) tools. The regulatory and methodological foundations for AI implementation are analyzed, including the EU AI Act, ISO 20400, and the Open Contracting Data Standard (OCDS), while key barriers are identified – technical, ethical, and legal. The risks of algorithmic bias, opacity, and decision-making delegation to autonomous systems are discussed. A set of recommendations is proposed for transparent, ethically grounded, and functionally relevant AI implementation in e-procurement platforms, taking into account stakeholder perspectives.
Zorina et al. (Fri,) studied this question.