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From Procurement Automation to Procurement Intelligence: An Integrated Framework for AI-Driven Procurement Transformation


Authors : Vijay Mittal

Volume/Issue : Volume 11 - 2026, Issue 9 - September


Google Scholar : https://tinyurl.com/3f44s66a

DOI : https://doi.org/10.38124/ijisrt/26sep571

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.


Abstract : Procurement is moving beyond transaction automation toward a new operating paradigm in which data, enterprise applications, artificial intelligence, governance, human judgment, and measurable value must function as an integrated system. Yet many organizations approach AI-enabled procurement through disconnected technology pilots, isolated process automation, or platform-led implementation programs. These approaches can produce local efficiency while leaving unresolved questions of enterprise readiness, capability maturity, architectural coherence, governance, and value realization.

Keywords : Intelligent Procurement; Artificial Intelligence; Procurement Transformation; Enterprise Architecture; AI Readiness; Maturity Model; SAP S/4HANA; SAP Ariba; SAP Business AI; Responsible AI; Digital Procurement; Agentic AI.

References :

  1. Bhattacharya, S., Govindan, K., Ghosh Dastidar, S., & Sharma, P. (2024). Applications of artificial intelligence in closed-loop supply chains: Systematic literature review and future research agenda. Transportation Research Part E: Logistics and Transportation Review, 184, 103455. https://doi.org/10.1016/j.tre.2024.103455
  2. International Organization for Standardization. (2023). ISO/IEC 42001:2023 Information technology — Artificial intelligence — Management system. ISO.
  3. Mittal, V. (2026). Architecting Intelligent Procurement: Designing AI-Driven Enterprise Procurement with SAP Business AI, SAP Ariba, SAP S/4HANA, SAP BTP, and Clean Core. Manuscript submitted for publication.
  4. NIST. (2024). Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (NIST AI 600-1). National Institute of Standards and Technology. https://doi.org/10.6028/NIST.AI.600-1
  5. Shahzadi, G., John, A., Jia, F., & collaborators. (2024). AI adoption in supply chain management: A systematic literature review. Journal of Manufacturing Technology Management, 35(6), 1125–1150. https://doi.org/10.1108/JMTM-09-2023-0431
  6. Tabassi, E. (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0) (NIST AI 100-1). National Institute of Standards and Technology. https://doi.org/10.6028/NIST.AI.100-1
  7. Artificial intelligence in supply chain management: A systematic literature review of empirical studies and research directions. (2024). Computers in Industry, 162, 104132. https://doi.org/10.1016/j.compind.2024.104132
  8. Artificial intelligence and machine learning in purchasing and supply management: A mixed-methods review of the state-of-the-art in literature and practice. (2024). Journal of Purchasing and Supply Management. https://doi.org/10.1016/j.pursup.2024.100896
  9. Assessing transformative procurement maturity: A general framework using a fuzzy model. (2025). Journal of Open Innovation: Technology, Market, and Complexity, 11(3), 100622. https://doi.org/10.1016/j.joitmc.2025.100622

Procurement is moving beyond transaction automation toward a new operating paradigm in which data, enterprise applications, artificial intelligence, governance, human judgment, and measurable value must function as an integrated system. Yet many organizations approach AI-enabled procurement through disconnected technology pilots, isolated process automation, or platform-led implementation programs. These approaches can produce local efficiency while leaving unresolved questions of enterprise readiness, capability maturity, architectural coherence, governance, and value realization.

Keywords : Intelligent Procurement; Artificial Intelligence; Procurement Transformation; Enterprise Architecture; AI Readiness; Maturity Model; SAP S/4HANA; SAP Ariba; SAP Business AI; Responsible AI; Digital Procurement; Agentic AI.

Paper Submission Last Date
30 - September - 2026

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