Skip to content

The Procurement Professional in the AI Era: Procurement Capability under Technological Change and Strategic Supply Uncertainty

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research)
Public Procurement and Policy

Abstract

This independent professional research paper examines whether established procurement competency frameworks sufficiently articulate the capabilities required of practitioners operating in an environment shaped by artificial intelligence, changing international trade relationships and strategic supply uncertainty. Using a comparative analysis of the Government of Canada's Procurement Community Competencies and the United Kingdom's Government Commercial Function People Standards, the paper identifies areas in which existing professional standards may benefit from more explicit, observable and assessable behaviours. The research proposes a three-part capability architecture that retains established procurement competencies while introducing seven AI-related practice areas and four wider strategic practice areas. These address AI-supported decision-making, governance, evidence verification, trade and policy interpretation, supply-chain resilience, public-value trade-offs and integrated commercial judgement. An Ontario procurement-policy case study illustrates how these capabilities may be applied within a provincial environment. The paper also considers transferability across Canadian jurisdictions, recognising differences in legislation, trade obligations, policy requirements and institutional governance. A worked procurement decision exercise, proposed assessment criteria and an independent validation methodology provide a practical basis for professional discussion and future pilot testing. The proposed framework has not yet been empirically validated. Related publication This research builds upon the professional-development architecture explored in Rajbinder Kaur's book, The Procurement Professional: A Career Guide for the AI Era (2026). The book provides a structured learning pathway across procurement practice, commercial judgement, leadership, risk, resilience and digital transformation, while the research paper examines how those capabilities may be articulated and assessed in contemporary procurement environments. Book available in Canada:https://www.amazon.ca/PROCUREMENT-PROFESSIONAL-Career-Guide-Era-ebook/dp/B0HKL51DBV/ Author: Rajbinder KaurVersion: 2.0Research type: Independent professional analysis.

View source

Similar papers

#artificial intelligence Open access May 2023

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...

Xiaotian Zhang, Chun-yan Li, Yi Zong et al. · 216 citations · ⚡17

KTO: Model Alignment as Prospect Theoretic Optimization

This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.

Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff et al. · 195 citations · ⚡28
#artificial intelligence Open access Jul 2024

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.

Kyra Wilson, Aylin Caliskan · 131 citations · ⚡8
#artificial intelligence Review Nov 2024

How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits

This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...

Masoud Mohseni, Artur Scherer, K. Johnson et al. · 121 citations · ⚡9
#artificial intelligence Review Oct 2025

Ultralytics YOLO Evolution: An Overview of YOLO26, YOLO11, YOLOv8 and YOLOv5 Object Detectors for Computer Vision and Pattern Recognition

This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 through YOLO27, and examines detection, segmentation, depth, classification, pose, oriented detection, tracking, export, quantization, and deplo...

Ranjan Sapkota, Manoj Karkee · 112 citations · ⚡10

Related blog posts

Hugging Face Blog Oct 20, 2026

MPS in PyTorch 2.15

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.