CERESResearch Repository

Investigating the Impact of Artificial Intelligence on Procurement & SCM Strategies. A study of the International Automotive Sector

dc.contributor.advisorHabib, Farooq
dc.contributor.authorGovorukhin, Stanislav
dc.date.accessioned2026-06-19T14:49:49Z
dc.date.available2026-06-19T14:49:49Z
dc.date.freetoread2026-06-19
dc.date.issued2025-09
dc.description.abstractPurpose of the research The purpose of this research is to explore the impact and role of artificial intelligence in the procurement and supply chain operations of the international automotive sector. More specifically, this research aims to explore key artificial intelligence applications in the supplier selection, evaluation and supply chain resilience operations, identify key barriers to AI implementation, analyze key strategic benefits and tactical measurable impacts derived from AI adoption, and develop key implementation recommendations. Methodology This research adopts systematic literature review methodology, including its major five steps: planning, screening, searching, extraction & synthesis and reporting of the descriptive and thematic findings. In total, it employs 70 academic sources and 14 industrial sources. Key Findings In general, automotive supplier selection and supply chain resilience are significantly impacted by the use of artificial intelligence, but the set of applied tools and practices remains limited. Although advanced technologies such as GenAI and NLP are already being applied selectively in the supplier selection and evaluation process, basic machine learning applications remain the key tools at this stage. In terms of supply chain resilience, deep learning tools are the primary technology in use, while GenAI is employed fragmentally. On the path to AI implementation, organisations face many organisational, regulatory and technical barriers, but with proper data and change management, technical architecture setup, high-ROI use cases prioritisation, and effective AI governance, the effect of AI implementation is significant, resulting in improved supply chain resilience, a more accurate, scalable and reliable supplier selection process and significant time and cost savings. Practical value This work has a high practical value, as it not only provides an overview of the main AI applications in supplier selection, evaluation, and resilience, but it also represents a multi-phase structured framework for AI implementation based on the synthesis of academic and industrial sources, taking into account the main barriers and steps for mitigating them.
dc.description.coursenameMSc in Logistics and Supply Chain Management
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/25355
dc.language.isoen
dc.publisherCranfield University
dc.publisher.departmentBAM
dc.subjectSupplier Selection
dc.subjectSupplier Evaluation
dc.subjectSupply Chain Resilience
dc.subjectArtificial Intelligence
dc.titleInvestigating the Impact of Artificial Intelligence on Procurement & SCM Strategies. A study of the International Automotive Sector
dc.typeThesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMSc

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Stanislav-Govorukhin-2025.pdf
Size:
4.42 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description: