Automation Vs. Intelligence: Limits And Opportunities of Ai in E-Procurement Platforms

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.

Authors

Institutions

Publication Details

Journal
The American Journal of Management and Economics Innovations
Published
2025-08-22
DOI
https://doi.org/10.37547/tajmei/volume07issue08-13
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Automation Vs. Intelligence: Limits And Opportunities of Ai in E-Procurement Platforms

Yuliia Zorina, Andrii Bikir
The American Journal of Management and Economics Innovations
Big Data and Business Intelligence
article

Automation Vs. Intelligence: Limits And Opportunities of Ai in E-Procurement Platforms

Yuliia Zorina, Andrii Bikir
article en

Abstract

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.

The American Journal of Management and Economics InnovationsVol. 7(08)
University of Wisconsin–Eau Claire (US), Global College (CY)
Openalex Percentile: Top 64%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Automation Vs. Intelligence: Limits And Opportunities of Ai in E-Procurement Platforms — Yuliia Zorina, Andrii Bikir · The American Journal of Management and Economics Innovations (2025) | TGRS Research Map | TGRS